From e9024087cbc6a1b6bffd6881fee72affa4676116 Mon Sep 17 00:00:00 2001
From: Paul Heubel <paul_heubel@web.de>
Date: Thu, 4 Jul 2024 14:11:49 +0200
Subject: [PATCH 01/34] Video and slide link update, creator addition.

---
 .../Projects_Tutorial8.ipynb                       | 14 ++++++--------
 1 file changed, 6 insertions(+), 8 deletions(-)

diff --git a/tutorials/Projects_GoodResearchPractices/Projects_Tutorial8.ipynb b/tutorials/Projects_GoodResearchPractices/Projects_Tutorial8.ipynb
index a7f4f83d2..d96775bbe 100644
--- a/tutorials/Projects_GoodResearchPractices/Projects_Tutorial8.ipynb
+++ b/tutorials/Projects_GoodResearchPractices/Projects_Tutorial8.ipynb
@@ -19,7 +19,7 @@
     "\n",
     "**Good Research Practices**\n",
     "\n",
-    "**Content creators:** Marguerite Brown, Zane Mitrevica, Natalie Steinemann, Yuxin Zhou\n",
+    "**Content creators:** Marguerite Brown, Zane Mitrevica, Aakash Sane, Natalie Steinemann, Yuxin Zhou\n",
     "\n",
     "**Content reviewers:** Katrina Dobson, Sloane Garelick, Maria Gonzalez, Nahid Hasan, Paul Heubel, Sherry Mi, Beatriz Cosenza Muralles, Cheng Zhang\n",
     "\n",
@@ -55,8 +55,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "form",
-    "execution": {}
+    "cellView": "form"
    },
    "outputs": [],
    "source": [
@@ -99,7 +98,7 @@
     "  return tab_contents\n",
     "\n",
     "\n",
-    "video_ids = [('Youtube', 'XZfqyancNpk'), ('Bilibili', 'BV1494y1B7qs')]\n",
+    "video_ids = [('Youtube', 'HEsrjlyza5o'), ('Bilibili', 'BV1494y1B7qs')]\n",
     "tab_contents = display_videos(video_ids, W=730, H=410)\n",
     "tabs = widgets.Tab()\n",
     "tabs.children = tab_contents\n",
@@ -112,15 +111,14 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "form",
-    "execution": {}
+    "cellView": "form"
    },
    "outputs": [],
    "source": [
     "# @title Tutorial slides\n",
     "# @markdown These are the slides for the videos in all tutorials today\n",
     "from IPython.display import IFrame\n",
-    "link_id = \"9s6ub\"\n",
+    "link_id = \"648nt\"\n",
     "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
     "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
    ]
@@ -227,7 +225,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.19"
+   "version": "3.9.18"
   }
  },
  "nbformat": 4,

From cb67050ea5a43f30f7ee7ac5e02667dfa7c74204 Mon Sep 17 00:00:00 2001
From: Paul Heubel <paul_heubel@web.de>
Date: Thu, 4 Jul 2024 16:38:23 +0200
Subject: [PATCH 02/34] Slide cell simplification and deletion of ; that aimed
 to suppress exercise explanation output as it might increase processing time.

---
 .../W1D1_Tutorial1.ipynb                      | 12 ++-----
 .../W1D1_Tutorial2.ipynb                      | 12 ++-----
 .../W1D1_Tutorial3.ipynb                      | 12 ++-----
 .../W1D1_Tutorial4.ipynb                      | 35 ++++---------------
 .../W1D1_Tutorial5.ipynb                      | 34 ++++--------------
 .../W1D1_Tutorial6.ipynb                      | 20 ++---------
 .../W1D1_Tutorial7.ipynb                      | 32 +++--------------
 .../W1D1_Tutorial8.ipynb                      | 28 +++------------
 .../W1D1_Tutorial9.ipynb                      | 32 ++++-------------
 9 files changed, 40 insertions(+), 177 deletions(-)

diff --git a/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial1.ipynb b/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial1.ipynb
index 9900b2e00..0f4f69be0 100644
--- a/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial1.ipynb
+++ b/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial1.ipynb
@@ -243,14 +243,8 @@
     "\n",
     "link_id = \"4suf5\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
    ]
   },
   {
@@ -830,7 +824,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.19"
+   "version": "3.9.18"
   },
   "toc-autonumbering": false
  },
diff --git a/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial2.ipynb b/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial2.ipynb
index 656a938f3..21df1533c 100644
--- a/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial2.ipynb
+++ b/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial2.ipynb
@@ -182,14 +182,8 @@
     "\n",
     "link_id = \"gh5us\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
    ]
   },
   {
@@ -691,7 +685,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.19"
+   "version": "3.9.18"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial3.ipynb b/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial3.ipynb
index 3f0bd4614..0753437a1 100644
--- a/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial3.ipynb
+++ b/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial3.ipynb
@@ -212,14 +212,8 @@
     "\n",
     "link_id = \"cnfwz\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
    ]
   },
   {
@@ -795,7 +789,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.19"
+   "version": "3.9.18"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial4.ipynb b/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial4.ipynb
index 8282fb0be..0f57bf7c7 100644
--- a/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial4.ipynb
+++ b/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial4.ipynb
@@ -86,9 +86,7 @@
    "cell_type": "code",
    "execution_count": null,
    "id": "5e22563d-1148-4079-9f92-5f2e780b9119",
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# installations ( uncomment and run this cell ONLY when using google colab or kaggle )\n",
@@ -100,7 +98,6 @@
    "execution_count": null,
    "id": "06073287-7bdb-45b5-9cec-8cdf123adb49",
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -117,7 +114,6 @@
    "id": "ed6bcdfe-d18b-42a4-96d6-2f921d9ce3fd",
    "metadata": {
     "cellView": "form",
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -137,7 +133,6 @@
    "id": "1712a218-1c6b-4ae9-9b89-5843bdde1d96",
    "metadata": {
     "cellView": "form",
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -196,7 +191,6 @@
    "id": "682c6f71-edc2-4088-bd74-fb526e667ba7",
    "metadata": {
     "cellView": "form",
-    "execution": {},
     "pycharm": {
      "name": "#%%\n"
     },
@@ -212,14 +206,8 @@
     "\n",
     "link_id = \"hmqfr\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
    ]
   },
   {
@@ -240,7 +228,6 @@
    "execution_count": null,
    "id": "7837f8bd-da89-4718-ab02-d5107576d2d6",
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 303,
      "status": "ok",
@@ -274,9 +261,7 @@
    "cell_type": "code",
    "execution_count": null,
    "id": "cbe80157",
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "ds.tos"
@@ -297,7 +282,6 @@
    "execution_count": null,
    "id": "09542eab-998d-4b2d-807c-dccd5bd4329e",
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 14,
      "status": "ok",
@@ -334,7 +318,6 @@
    "execution_count": null,
    "id": "78c1ffc2-45cb-40cc-962e-c76021d9ab1c",
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 12,
      "status": "ok",
@@ -396,7 +379,6 @@
    "execution_count": null,
    "id": "06e3bfff",
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -419,7 +401,6 @@
    "execution_count": null,
    "id": "400c3dab",
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -442,7 +423,6 @@
    "execution_count": null,
    "id": "5d397f30",
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -465,7 +445,6 @@
    "execution_count": null,
    "id": "59b84034-7d42-4080-932f-0eefd165953d",
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 297,
      "status": "ok",
@@ -498,7 +477,6 @@
    "execution_count": null,
    "id": "a49b957e-ea24-414e-a422-c40a3723fbae",
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 815,
      "status": "ok",
@@ -536,7 +514,6 @@
    "execution_count": null,
    "id": "589b4cf2-9431-43e9-ad76-9acbc7bde892",
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -545,7 +522,7 @@
     "\n",
     "\"\"\"\n",
     "1.  Upwelling is a process in which deep, cold water rises toward the surface. This can be identified in a sea surface temperature (SST) map as areas where the SST is colder than the surrounding waters. We note off the west coast of South America there is a 'tongue' of colder water from about -40 S northward. The strength of upwelling can often vary seasonally, and thus in our annual mean SST map above, the effects of this are likely more subtle.\n",
-    "\"\"\";"
+    "\"\"\""
    ]
   },
   {
@@ -609,7 +586,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.19"
+   "version": "3.9.18"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial5.ipynb b/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial5.ipynb
index 6c918bf93..6b77ba4e2 100644
--- a/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial5.ipynb
+++ b/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial5.ipynb
@@ -79,9 +79,7 @@
    "cell_type": "code",
    "execution_count": null,
    "id": "9226796c-2eca-44c2-9dc7-5cf2ba93836d",
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# installations ( uncomment and run this cell ONLY when using google colab or kaggle )\n",
@@ -93,7 +91,6 @@
    "execution_count": null,
    "id": "06073287-7bdb-45b5-9cec-8cdf123adb49",
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 2358,
      "status": "ok",
@@ -122,7 +119,6 @@
    "id": "72e04965-e982-444d-b3da-4e1e639c6899",
    "metadata": {
     "cellView": "form",
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -142,7 +138,6 @@
    "id": "21725d4b-ee68-42aa-af76-70392b4ab6ac",
    "metadata": {
     "cellView": "form",
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -201,7 +196,6 @@
    "id": "1bfcf3bd-6805-4cfb-90c4-a9067f6ce91c",
    "metadata": {
     "cellView": "form",
-    "execution": {},
     "pycharm": {
      "name": "#%%\n"
     },
@@ -217,14 +211,8 @@
     "\n",
     "link_id = \"9z6km\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
    ]
   },
   {
@@ -263,7 +251,6 @@
    "execution_count": null,
    "id": "7837f8bd-da89-4718-ab02-d5107576d2d6",
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 388,
      "status": "ok",
@@ -298,7 +285,6 @@
    "execution_count": null,
    "id": "c0348ee8-6e9b-4f50-a844-375ae00d2771",
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 959,
      "status": "ok",
@@ -345,7 +331,6 @@
    "execution_count": null,
    "id": "6e4fb25e-165f-4350-a93d-46a344f2d175",
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 160,
      "status": "ok",
@@ -392,7 +377,6 @@
    "execution_count": null,
    "id": "c6990393-fb5f-4a10-b8e2-fd9c6917d9d2",
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 215,
      "status": "ok",
@@ -439,7 +423,6 @@
    "execution_count": null,
    "id": "7e568c2f-7143-4346-85ce-a430db03316e",
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 2695,
      "status": "ok",
@@ -475,7 +458,6 @@
    "execution_count": null,
    "id": "f908c377-67fa-449c-b8d1-82ba6a14baff",
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 363,
      "status": "ok",
@@ -520,7 +502,6 @@
    "execution_count": null,
    "id": "fb839b81-6bc3-4cf8-8d06-748a3770cd22",
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -530,7 +511,7 @@
     "\"\"\"\n",
     "1. This location's strong seasonality suggests that it experiences significant seasonal changes in incoming solar radiation received at the surface over the course of a year.\n",
     "2. Seasonal variations in sea surface temperature (SST) would differ at different latitudes. At the equator, the seasonal variations in SST tend to be relatively small. This is because the equatorial region experiences a relatively constant amount of solar radiation throughout the year, resulting in a relatively stable SST. At the poles, however, the seasonal variations in SST are more pronounced. At 50ºS, the seasonal cycle would be opposite that shown here because the northern and southern hemispheres experience their seasons at different times of year (that is northern hemisphere summer is southern hemisphere winter).\n",
-    "\"\"\";"
+    "\"\"\""
    ]
   },
   {
@@ -558,7 +539,6 @@
    "execution_count": null,
    "id": "22c61c11-2a48-4c6c-8009-6f20e0101237",
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 584,
      "status": "ok",
@@ -592,7 +572,6 @@
    "execution_count": null,
    "id": "19a2808b-81f9-40e5-ab31-d63bfce85eae",
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 1075,
      "status": "ok",
@@ -628,7 +607,6 @@
    "execution_count": null,
    "id": "1ce210a0-f392-448d-a2bf-cd27ad370d99",
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -639,7 +617,7 @@
     "1. Generally the difference is negative in the Northern Hemisphere and positive in the Southern Hemisphere.\n",
     "2. The hemispheres have opposing signs, which is because of Earth's tilt and how it affects the timing of the seasons in each hemisphere (i.e. Northern Hemisphere summer is Southern Hemisphere winter). In the Northern Hemisphere, the difference is negative because the Northern Hemisphere July is warmer than the Northern Hemisphere January. In the Southern Hemisphere, the opposite is true.\n",
     "3. The ITCZ shifts with the seasons. When the Sun is directly overhead at the Northern Tropics (June), the ITCZ moves northwards, and when the Sun is directly overhead at the Southern Tropics (December), the ITCZ shifts southwards. This migration can affect the distribution of rain, leading to wet and dry seasons in many tropical regions.\n",
-    "\"\"\";"
+    "\"\"\""
    ]
   },
   {
@@ -705,7 +683,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.19"
+   "version": "3.9.18"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial6.ipynb b/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial6.ipynb
index 98bf0df64..5c28fd17c 100644
--- a/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial6.ipynb
+++ b/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial6.ipynb
@@ -79,9 +79,7 @@
    "cell_type": "code",
    "execution_count": null,
    "id": "b3ea206d-56dd-43fe-a1e3-01b2235c9f51",
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# installations ( uncomment and run this cell ONLY when using google colab or kaggle )\n",
@@ -93,7 +91,6 @@
    "execution_count": null,
    "id": "06073287-7bdb-45b5-9cec-8cdf123adb49",
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -110,7 +107,6 @@
    "id": "b4cabcfc-2cc0-450a-8e94-4f8e635213c5",
    "metadata": {
     "cellView": "form",
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -130,7 +126,6 @@
    "id": "e941ab00-bac3-4fbb-a582-9a73da96b617",
    "metadata": {
     "cellView": "form",
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -189,7 +184,6 @@
    "id": "a1ac91c8-11f3-4bb0-86ee-8eff1e61187c",
    "metadata": {
     "cellView": "form",
-    "execution": {},
     "pycharm": {
      "name": "#%%\n"
     },
@@ -232,7 +226,6 @@
    "execution_count": null,
    "id": "7837f8bd-da89-4718-ab02-d5107576d2d6",
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 303,
      "status": "ok",
@@ -267,7 +260,6 @@
    "execution_count": null,
    "id": "4c9940df-5174-49bf-9117-eef1e14abec0",
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 303,
      "status": "ok",
@@ -308,7 +300,6 @@
    "execution_count": null,
    "id": "35fc2054-df48-4ea2-8433-632ba8755c61",
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 970,
      "status": "ok",
@@ -342,7 +333,6 @@
    "execution_count": null,
    "id": "5d3abf06-a341-45ac-a3f2-76131016c0b3",
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 661,
      "status": "ok",
@@ -394,7 +384,6 @@
    "execution_count": null,
    "id": "a5878de6-f3ab-43e0-8f0d-12ab51631450",
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 1450,
      "status": "ok",
@@ -429,7 +418,6 @@
    "execution_count": null,
    "id": "b8f7e3a5-0748-4395-95b0-0e31d0a5d4d1",
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -453,7 +441,6 @@
    "execution_count": null,
    "id": "802c5e99-7223-49b5-a867-91d943075d52",
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 985,
      "status": "ok",
@@ -493,7 +480,6 @@
    "execution_count": null,
    "id": "5b3181b8-e3a2-4740-aac7-8ba205e12e52",
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -503,7 +489,7 @@
     "\"\"\"\n",
     "1. An area-weighted mean global temperature anomaly provides a more accurate representation of global temperature changes by accounting for the uneven distribution of grid cell sizes across latitudes. It ensures each region's contribution to the global mean is proportional to its surface area, avoiding any disproportionate influence from smaller areas at higher latitudes. Both weighted and unweighted SST means show the similar increasing trend in temperature from 2000 to 2014, although by eye, it appears that the trend would be slightly lower for the unweighted mean.\n",
     "2. The observed SST warming trend from 2000 to 2014 is similar to the rate of change observed from 1980 to 2000, which fits into the larger context of the substantial warming trend observed over the past century. Over this period, global average temperatures have risen rapidly, at a rate that is not typical in the context of most longer-term naturally driven temperature variations.\n",
-    "\"\"\";"
+    "\"\"\""
    ]
   },
   {
@@ -569,7 +555,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.19"
+   "version": "3.9.18"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial7.ipynb b/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial7.ipynb
index 35371d2d2..46a5b9e98 100644
--- a/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial7.ipynb
+++ b/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial7.ipynb
@@ -81,9 +81,7 @@
    "cell_type": "code",
    "execution_count": null,
    "id": "9fa2315d-13a8-4499-b962-4434934b39ed",
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# installations ( uncomment and run this cell ONLY when using google colab or kaggle )\n",
@@ -95,7 +93,6 @@
    "execution_count": null,
    "id": "06073287-7bdb-45b5-9cec-8cdf123adb49",
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -112,7 +109,6 @@
    "id": "5c385e97-285f-45d4-88e2-26ee76b8d039",
    "metadata": {
     "cellView": "form",
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -132,7 +128,6 @@
    "id": "2fd1ee75-9e23-4204-a896-9a08da3e794f",
    "metadata": {
     "cellView": "form",
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -191,7 +186,6 @@
    "id": "c9027490-8086-41a3-9489-0f164b6375a2",
    "metadata": {
     "cellView": "form",
-    "execution": {},
     "pycharm": {
      "name": "#%%\n"
     },
@@ -207,14 +201,8 @@
     "\n",
     "link_id = \"sb3n5\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
    ]
   },
   {
@@ -241,7 +229,6 @@
    "execution_count": null,
    "id": "7837f8bd-da89-4718-ab02-d5107576d2d6",
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -270,7 +257,6 @@
    "execution_count": null,
    "id": "a9cfb76b-c4ab-441e-a474-c66b7af944ad",
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 499,
      "status": "ok",
@@ -295,7 +281,6 @@
    "execution_count": null,
    "id": "6927f5be-d313-4d03-bab8-d22b3cb13899",
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 312,
      "status": "ok",
@@ -336,7 +321,6 @@
    "execution_count": null,
    "id": "342acbf1-4eee-4d0d-bb52-b394ffcd556d",
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 791,
      "status": "ok",
@@ -361,7 +345,6 @@
    "execution_count": null,
    "id": "0eb0cc4e-661a-4ab1-96ad-e096917ef104",
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 1333,
      "status": "ok",
@@ -401,7 +384,6 @@
    "execution_count": null,
    "id": "118df2c7",
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -416,7 +398,6 @@
    "execution_count": null,
    "id": "f0b9ef33",
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -441,7 +422,6 @@
    "execution_count": null,
    "id": "1517017a",
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -454,7 +434,6 @@
    "execution_count": null,
    "id": "daf709a8",
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -493,7 +472,6 @@
    "execution_count": null,
    "id": "34f4c5ba-8a12-4472-b482-4ca4f2948a2c",
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -503,7 +481,7 @@
     "\"\"\"\n",
     "1. In general, by examining the data at these different time scales, you can get a more comprehensive understanding of the SST variations and their potential causes.\n",
     "2. The original monthly data gives you the most granular view of the data, allowing you to see monthly variations in SST. Coarsening the data over 4-month periods reduces the temporal resolution but provides a slightly smoothed series that could help identify patterns or trends over this larger time period. A 6-month moving average could be useful for identifying semi-annual trends and reducing the impact of short-term noise in the data. The annually resampled (12 months) data provides a high-level view of the SST data, emphasizing the annual pattern. This can be useful for identifying long-term trends or changes in the data over the span of years.\n",
-    "\"\"\";"
+    "\"\"\""
    ]
   },
   {
@@ -566,7 +544,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.19"
+   "version": "3.9.18"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial8.ipynb b/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial8.ipynb
index 7acd6e530..5197d6b3d 100644
--- a/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial8.ipynb
+++ b/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial8.ipynb
@@ -77,9 +77,7 @@
    "cell_type": "code",
    "execution_count": null,
    "id": "5d7768f4-c27d-4502-a975-934632c1d9b3",
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# installations ( uncomment and run this cell ONLY when using google colab or kaggle )\n",
@@ -91,7 +89,6 @@
    "execution_count": null,
    "id": "06073287-7bdb-45b5-9cec-8cdf123adb49",
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 1691,
      "status": "ok",
@@ -118,7 +115,6 @@
    "id": "994efaf1-a38b-42f4-ac31-40b747e6b806",
    "metadata": {
     "cellView": "form",
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -138,7 +134,6 @@
    "id": "7bc232cf-a917-49e3-93b9-77afb5fb3f20",
    "metadata": {
     "cellView": "form",
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -197,7 +192,6 @@
    "id": "bc214dbf-b28f-44c4-bb53-8d8e852610e6",
    "metadata": {
     "cellView": "form",
-    "execution": {},
     "pycharm": {
      "name": "#%%\n"
     },
@@ -213,14 +207,8 @@
     "\n",
     "link_id = \"zhb3c\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
    ]
   },
   {
@@ -260,7 +248,6 @@
    "execution_count": null,
    "id": "7837f8bd-da89-4718-ab02-d5107576d2d6",
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 4386,
      "status": "ok",
@@ -305,7 +292,6 @@
    "execution_count": null,
    "id": "ac3e42eb-1852-4580-9c52-e7237135ed01",
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 166,
      "status": "ok",
@@ -341,7 +327,6 @@
    "execution_count": null,
    "id": "61abc5b3-aadf-4a96-98a2-c9c36094a863",
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 159,
      "status": "ok",
@@ -376,7 +361,6 @@
    "execution_count": null,
    "id": "eced16af",
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -401,7 +385,6 @@
    "execution_count": null,
    "id": "ca1e150f-c422-4f0c-8f64-9c734bcbdee3",
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -435,7 +418,6 @@
    "execution_count": null,
    "id": "e6518686-8d6b-41be-adbb-b8b121894fd7",
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -447,7 +429,7 @@
     "2. In the Antarctic, they are roughly the same. In the Artic, there is more area with warmer SST in 2014.\n",
     "3. The ice-albedo feedback could be amplifying the ocean warming noted in Question 2. The polar regions examined here are the only places where waters can be cold enough to sustain sea ice. In a warming world where sea ice is melting, areas of the ocean that were once covered by reflective ice are replaced by darker water, which absorbs more sunlight, warms and hinders sea-ice growth.\n",
     "\n",
-    "\"\"\";"
+    "\"\"\""
    ]
   },
   {
@@ -514,7 +496,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.19"
+   "version": "3.9.18"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial9.ipynb b/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial9.ipynb
index 950d05ad2..6310a5dec 100644
--- a/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial9.ipynb
+++ b/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial9.ipynb
@@ -77,9 +77,7 @@
    "cell_type": "code",
    "execution_count": null,
    "id": "a3d3f235-a5bf-4445-be5b-0aba0c3c1f7e",
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# installations ( uncomment and run this cell ONLY when using google colab or kaggle )\n",
@@ -91,7 +89,6 @@
    "execution_count": null,
    "id": "06073287-7bdb-45b5-9cec-8cdf123adb49",
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 521,
      "status": "ok",
@@ -118,7 +115,6 @@
    "id": "b389f92a-2998-494d-a58c-f582a91c6b95",
    "metadata": {
     "cellView": "form",
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -138,7 +134,6 @@
    "id": "51f0a30a-35f7-4b29-a1d6-5d242f6aefa7",
    "metadata": {
     "cellView": "form",
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -197,7 +192,6 @@
    "id": "af18aad1-ddc6-404c-bf27-978471fe2b70",
    "metadata": {
     "cellView": "form",
-    "execution": {},
     "pycharm": {
      "name": "#%%\n"
     },
@@ -213,14 +207,8 @@
     "\n",
     "link_id = \"dtgax\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
    ]
   },
   {
@@ -249,7 +237,6 @@
    "execution_count": null,
    "id": "7837f8bd-da89-4718-ab02-d5107576d2d6",
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 4331,
      "status": "ok",
@@ -284,7 +271,6 @@
    "execution_count": null,
    "id": "c9bf1c46-e7ed-43c1-8a45-e03d22295da1",
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 624,
      "status": "ok",
@@ -331,7 +317,6 @@
    "execution_count": null,
    "id": "505bbd2d",
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -366,7 +351,6 @@
    "execution_count": null,
    "id": "090f1997-8dea-4eed-aa55-ab3a180ecdd5",
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 728,
      "status": "ok",
@@ -402,7 +386,6 @@
    "execution_count": null,
    "id": "aae12476-4802-42a2-993b-29da6c383535",
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 567,
      "status": "ok",
@@ -428,9 +411,7 @@
    "cell_type": "code",
    "execution_count": null,
    "id": "c12ef69c-b730-486c-9300-286cc2e338ae",
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "nino_mean.plot()"
@@ -463,7 +444,6 @@
    "execution_count": null,
    "id": "c8986c67",
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -476,7 +456,7 @@
     "3. In the equatorial region, the grid cells are usually very similar in size. You could compute the weighted average and compare to be sure this is the case with our reanalysis product.\n",
     "\n",
     "These questions are just to get you thinking....note from this time series alone we can not attribute processes to the observed SST.\n",
-    "\"\"\";"
+    "\"\"\""
    ]
   },
   {
@@ -543,7 +523,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.19"
+   "version": "3.9.18"
   }
  },
  "nbformat": 4,

From a3096d7f746b0aebc30daf59e70ac8c741426fcc Mon Sep 17 00:00:00 2001
From: Paul Heubel <paul_heubel@web.de>
Date: Thu, 4 Jul 2024 17:06:42 +0200
Subject: [PATCH 03/34] Added feedback widget.

---
 .../W1D1_Intro.ipynb                          | 67 ++++++++++++----
 .../W1D1_Tutorial2.ipynb                      | 56 ++++++++++++++
 .../W1D1_Tutorial3.ipynb                      | 76 +++++++++++++++++++
 .../W1D1_Tutorial4.ipynb                      | 60 +++++++++++++++
 .../W1D1_Tutorial5.ipynb                      | 73 +++++++++++++++++-
 .../W1D1_Tutorial6.ipynb                      | 70 +++++++++++++++--
 .../W1D1_Tutorial7.ipynb                      | 60 +++++++++++++++
 .../W1D1_Tutorial8.ipynb                      | 60 +++++++++++++++
 .../W1D1_Tutorial9.ipynb                      | 60 +++++++++++++++
 9 files changed, 560 insertions(+), 22 deletions(-)

diff --git a/tutorials/W1D1_ClimateSystemOverview/W1D1_Intro.ipynb b/tutorials/W1D1_ClimateSystemOverview/W1D1_Intro.ipynb
index 66fad600e..18f7f3d73 100644
--- a/tutorials/W1D1_ClimateSystemOverview/W1D1_Intro.ipynb
+++ b/tutorials/W1D1_ClimateSystemOverview/W1D1_Intro.ipynb
@@ -46,6 +46,33 @@
     "3. Identify the main concepts covered in the course."
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "d8266b33-da1b-43a9-927f-ab629de4a10b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D1_Intro\""
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "452816ee",
@@ -61,8 +88,7 @@
    "execution_count": null,
    "id": "afe1b307",
    "metadata": {
-    "cellView": "form",
-    "execution": {}
+    "cellView": "form"
    },
    "outputs": [],
    "source": [
@@ -123,6 +149,17 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "48f83cbb-fe30-4ed9-bfe2-c13792e81502",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Climate_Solutions_Video\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "168f8f55",
@@ -138,8 +175,7 @@
    "execution_count": null,
    "id": "c044d10e",
    "metadata": {
-    "cellView": "form",
-    "execution": {}
+    "cellView": "form"
    },
    "outputs": [],
    "source": [
@@ -148,14 +184,19 @@
     "\n",
     "link_id = \"ghmn5\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "f22cd6b1-37ca-4da3-9ea8-d2a4d65d3c1f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Climate_Solutions_Slides\")"
    ]
   }
  ],
@@ -186,7 +227,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.19"
+   "version": "3.9.18"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial2.ipynb b/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial2.ipynb
index 21df1533c..b404efa12 100644
--- a/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial2.ipynb
+++ b/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial2.ipynb
@@ -88,6 +88,32 @@
     "import matplotlib.pyplot as plt"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D1_T2\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -161,6 +187,16 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Solar_Radiation_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -186,6 +222,16 @@
     "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Solar_Radiation_Slides\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -377,6 +423,16 @@
     "coordinate_selection"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Coding_Exercise_1_2\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
diff --git a/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial3.ipynb b/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial3.ipynb
index 0753437a1..d86d59b46 100644
--- a/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial3.ipynb
+++ b/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial3.ipynb
@@ -105,6 +105,32 @@
     "import matplotlib.pyplot as plt"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D1_T3\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -191,6 +217,16 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Atmospheric_Climate_Systems_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -216,6 +252,16 @@
     "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Atmospheric_Climate_Systems_Slides\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -319,6 +365,16 @@
     "\"\"\""
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_1\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -654,6 +710,16 @@
     "\"\"\""
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_2_2\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -726,6 +792,16 @@
     "\"\"\""
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_2_3\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
diff --git a/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial4.ipynb b/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial4.ipynb
index 0f57bf7c7..cd416ccc4 100644
--- a/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial4.ipynb
+++ b/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial4.ipynb
@@ -108,6 +108,33 @@
     "import matplotlib.pyplot as plt"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "754caab0-66fc-4e23-bd60-6de2ff7d3b0a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D1_T4\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -185,6 +212,17 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "65eb3752-2e77-4024-9f6e-6cdbd66337a5",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Oceanic_Climate_Systems_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -210,6 +248,17 @@
     "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "bb3c61b6-544e-422a-be4c-ee7c6a2e2164",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Oceanic_Climate_Systems_Slides\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "b3f4e108-f55e-4c25-a00d-99dc00ba849a",
@@ -525,6 +574,17 @@
     "\"\"\""
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "1115cecf-9d73-4ac1-a6d3-9425342dc642",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_2\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "9ac2925a-9b96-4b0a-b2b6-24f6b4151d4c",
diff --git a/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial5.ipynb b/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial5.ipynb
index 6b77ba4e2..b2a891eef 100644
--- a/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial5.ipynb
+++ b/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial5.ipynb
@@ -113,6 +113,33 @@
     "import matplotlib.pyplot as plt"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "2ad30cf1-5467-4010-ac68-5046fb316018",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D1_T5\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -190,6 +217,17 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "a2371121-637e-4517-9db2-1c5faab01348",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Terrestrial_Temperature_Rainfall_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -215,6 +253,17 @@
     "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "c28bb25a-1852-4477-b932-41fdecbe42ef",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Terrestrial_Temperature_Rainfall_Slides\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "8704803f-300d-4631-a2fa-f62d18726d1c",
@@ -514,6 +563,17 @@
     "\"\"\""
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "68b7485b-5ca4-47fd-8009-32376b4b5049",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_1_2_1\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "d7c540b2-c707-4d51-8cc7-3ea51b8a505f",
@@ -595,7 +655,7 @@
     "execution": {}
    },
    "source": [
-    "#### Questions 1.2.1: Climate Connection\n",
+    "#### Questions 1.2.2: Climate Connection\n",
     "\n",
     "1. What patterns do you observe in this map?\n",
     "2. Why is there such an apparent difference between the Northern and Southern Hemisphere SST changes?\n",
@@ -620,6 +680,17 @@
     "\"\"\""
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "78e2905e-cb34-4ca0-b17a-2defe5ec0630",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_1_2_2\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "ee5f2987-d7e3-4b0d-a5ad-abfae5a98072",
diff --git a/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial6.ipynb b/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial6.ipynb
index 5c28fd17c..8e9d619d6 100644
--- a/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial6.ipynb
+++ b/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial6.ipynb
@@ -101,6 +101,33 @@
     "import matplotlib.pyplot as plt"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "e05b62d2-e46f-4d85-af57-72213527248a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D1_T6\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -178,6 +205,17 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "93161e14-e3a3-4bf2-8448-ecd35e1ee7c8",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Orbital_Cycles_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -199,14 +237,19 @@
     "\n",
     "link_id = \"tcb2q\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "ba94f7c9-1871-449d-ad5c-6a13612e7748",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Orbital_Cycles_Slides\")"
    ]
   },
   {
@@ -492,6 +535,17 @@
     "\"\"\""
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "96461dcd-f5b7-409a-bb95-da0c2600938e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_1\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "bbbe7478-dd54-4bb1-9e82-226a655a26d0",
diff --git a/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial7.ipynb b/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial7.ipynb
index 46a5b9e98..fb9ae6086 100644
--- a/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial7.ipynb
+++ b/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial7.ipynb
@@ -103,6 +103,33 @@
     "from pythia_datasets import DATASETS"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "21b5614e-3a3f-46d1-a926-283e9458da74",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D1_T7\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -180,6 +207,17 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "43bfb42a-8ce6-44b6-9a88-6bca2000bd7e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Carbon_Cycle_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -205,6 +243,17 @@
     "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "3918492b-f1c5-4b8e-8479-748a1652f724",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Carbon_Cycle_Slides\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "3045c67e-21cd-4ef9-a49f-e12ae7db23cf",
@@ -484,6 +533,17 @@
     "\"\"\""
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "b026c173-582c-48e1-8504-ef1c13acee9e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_1_4\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "c18bb57b-63f2-4f9d-ac8d-32d0231d02fa",
diff --git a/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial8.ipynb b/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial8.ipynb
index 5197d6b3d..1c842d76f 100644
--- a/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial8.ipynb
+++ b/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial8.ipynb
@@ -109,6 +109,33 @@
     "from pythia_datasets import DATASETS"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "d041a3d6-01af-42cc-bdc0-7e62eb272bc9",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D1_T8\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -186,6 +213,17 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "6647e202-05cd-490c-b694-8ca6bad2ccdd",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Climate_Feedbacks_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -211,6 +249,17 @@
     "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "09bb8a72-a965-4598-9b34-8341b293776f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Climate_Feedbacks_Slides\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "da76db37-e833-42c5-a740-5dcf0877b43c",
@@ -432,6 +481,17 @@
     "\"\"\""
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "a7722baa-1de1-4bc3-937c-398c43ecf953",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_1_1\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "4ce1373d-e4fc-437e-a445-13dd8fa5f22f",
diff --git a/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial9.ipynb b/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial9.ipynb
index 6310a5dec..0ab92bcb7 100644
--- a/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial9.ipynb
+++ b/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial9.ipynb
@@ -109,6 +109,33 @@
     "import matplotlib.pyplot as plt"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "07974de6-0957-45b3-9e77-895af3c459c8",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D1_T9\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -186,6 +213,17 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "bf18fa96-f99f-420c-95aa-5b18704fac8a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Past_Present_Future_Climate_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -211,6 +249,17 @@
     "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "6a5f6a63-2185-448e-9a94-104977794bb0",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Past_Present_Future_Climate_Slides\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "4dd6b000-b079-461c-9a0e-8fd2bced814b",
@@ -459,6 +508,17 @@
     "\"\"\""
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "601b5358-8df2-4b1e-9576-bb5323d6b9ce",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_3\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "5f6c15ba-b7d3-4ef9-a100-44057a2cefce",

From d5b207c834fc94c130a7155704b1da69b3aa3557 Mon Sep 17 00:00:00 2001
From: Paul Heubel <paul_heubel@web.de>
Date: Thu, 4 Jul 2024 18:23:21 +0200
Subject: [PATCH 04/34] Removed duplications, added feedback widgets,
 simplified slide cells, and removed ;s .

---
 .../W1D2_Intro.ipynb                          |  61 ++++-
 .../W1D2_Tutorial1.ipynb                      | 217 +++++-------------
 .../W1D2_Tutorial2.ipynb                      | 204 +++++++---------
 .../W1D2_Tutorial3.ipynb                      | 150 ++++++++----
 .../W1D2_Tutorial4.ipynb                      | 169 +++++++-------
 .../W1D2_Tutorial5.ipynb                      | 144 ++++++------
 .../W1D2_Tutorial6.ipynb                      | 190 ++++++---------
 7 files changed, 538 insertions(+), 597 deletions(-)

diff --git a/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/W1D2_Intro.ipynb b/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/W1D2_Intro.ipynb
index cdbc50e55..834c3610e 100644
--- a/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/W1D2_Intro.ipynb
+++ b/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/W1D2_Intro.ipynb
@@ -66,6 +66,33 @@
     "3. Analyze ocean and atmosphere reanalysis products on different spatial and temporal scales."
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "cda25c98-a47f-403b-8aeb-d2d34e3c0f8e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D2_Intro\""
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "a79a31b2",
@@ -144,6 +171,17 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "d1cd2985-22ed-4de3-8f2d-e825f18433e8",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Oceans_in_Climate_Video\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "8249df54",
@@ -169,14 +207,19 @@
     "\n",
     "link_id = \"2pxs6\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "5492dc34-28d1-47ef-bc82-609b4b208424",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Oceans_in_Climate_Slides\")"
    ]
   }
  ],
@@ -207,7 +250,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.19"
+   "version": "3.9.18"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/W1D2_Tutorial1.ipynb b/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/W1D2_Tutorial1.ipynb
index 5b0311994..78c58f523 100644
--- a/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/W1D2_Tutorial1.ipynb
+++ b/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/W1D2_Tutorial1.ipynb
@@ -85,7 +85,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "tags": [
      "colab"
     ]
@@ -102,9 +101,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# imports\n",
@@ -119,27 +116,34 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "cellView": "form",
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
-    "# @title Figure Settings\n",
-    "import ipywidgets as widgets  # interactive display\n",
+    "# @title Install and import feedback gadget\n",
     "\n",
-    "%config InlineBackend.figure_format = 'retina'\n",
-    "plt.style.use(\n",
-    "    \"https://raw.githubusercontent.com/neuromatch/climate-course-content/main/cma.mplstyle\"\n",
-    ")"
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D2_T1\""
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "form",
-    "execution": {}
+    "cellView": "form"
    },
    "outputs": [],
    "source": [
@@ -157,7 +161,6 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -219,12 +222,21 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_ENSO_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
     "cellView": "form",
-    "execution": {},
     "pycharm": {
      "name": "#%%\n"
     },
@@ -240,14 +252,18 @@
     "\n",
     "link_id = \"t65v8\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_ENSO_Slides\")"
    ]
   },
   {
@@ -337,7 +353,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 5921,
      "status": "ok",
@@ -385,7 +400,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 5137,
      "status": "ok",
@@ -436,21 +450,6 @@
     "</details>"
    ]
   },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "execution": {}
-   },
-   "source": [
-    "<details>\n",
-    "<summary><font color='orangered'>Click here for a description of the plot  </font></summary>\n",
-    "A map plot showing the sea surface temperature (SST) in January 2000 ranging from -2°C to 30°C from the CESM Earth system model's historical simulation for the Sixth Phase of the Coupled Intercomparison Project (CMIP6). Equatorial regions show the warmest temperatures, and polar regions the lowest. A few larger patterns indicate that more than just the latitude is important to create the spatial SST distribution.\n",
-    "\n",
-    "*** \n",
-    "\n",
-    "</details>"
-   ]
-  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -472,9 +471,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# a bit more complicated code that allows interactive plots\n",
@@ -508,21 +505,6 @@
     "</details>"
    ]
   },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "execution": {}
-   },
-   "source": [
-    "<details>\n",
-    "<summary><font color='orangered'>Click here for a description of the plot  </font></summary>\n",
-    "An interactive map plot showing the sea surface temperature (SST) from January 2000 until October 2000  ranging from -2°C to 30°C from the CESM Earth system model's historical simulation for the Sixth Phase of the Coupled Intercomparison Project (CMIP6). Over the annual cycle, the warm and cold SST regions shift depending on the solar input. A few larger patterns indicate that more than just the latitude is important to create the spatial SST distribution, e.g. the equatorial pacific shows a cooler SST trench over the entire year compared to the surrounding subtropical waters.\n",
-    "\n",
-    "*** \n",
-    "\n",
-    "</details>"
-   ]
-  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -538,7 +520,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -570,7 +551,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 842,
      "status": "ok",
@@ -602,7 +582,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 492,
      "status": "ok",
@@ -638,9 +617,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# SST in just the Niño 3.4 region\n",
@@ -660,7 +637,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 797,
      "status": "ok",
@@ -731,84 +707,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
-   "outputs": [],
-   "source": [
-    "# again more complicated code that allows interactive plots\n",
-    "gv.extension(\"bokeh\")  # load Bokeh\n",
-    "dataset_plot = gv.Dataset(\n",
-    "    ds_SST.where(\n",
-    "    (ds_SST.lat > -5) & (ds_SST.lat < 5) & (ds_SST.lon > 190) & (ds_SST.lon < 240)\n",
-    ").isel(time=slice(0, 10))\n",
-    ")  # slice only the first 10 timepoint, as it is a time consuming task\n",
-    "images = dataset_plot.to(gv.Image, [\"longitude\", \"latitude\"], \"tos\", \"time\")\n",
-    "# aesthetics\n",
-    "images.opts(\n",
-    "    cmap=\"coolwarm\",\n",
-    "    colorbar=True,\n",
-    "    width=600,\n",
-    "    height=400,\n",
-    "    projection=ccrs.Robinson(central_longitude=180),\n",
-    "    clabel=\"Sea Surface Temperature [˚C]\",\n",
-    ") * gf.coastline"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "execution": {}
-   },
-   "source": [
-    "<details>\n",
-    "<summary><font color='orangered'>Click here for a description of the plot  </font></summary>\n",
-    "An interactive map plot showing the sea surface temperature (SST) from January 2000 until October 2000  ranging from 23.5°C to 30.5°C from the CESM Earth system model's historical simulation for the Sixth Phase of the Coupled Intercomparison Project (CMIP6). Over the annual cycle, the SST increases in the northern hemispherical summer. The closer to the equator, the colder the water masses at the surface caused by upwelling induced by easterly winds and consequent Ekman transport. The more west in the region the warmer the water masses also caused by this transport.\n",
-    "\n",
-    "*** \n",
-    "\n",
-    "</details>"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "execution": {}
-   },
-   "source": [
-    "<details>\n",
-    "<summary><font color='orangered'>Click here for a description of the plot  </font></summary>\n",
-    "A map plot zoomed into the Pacific Ocean showing the sea surface temperature (SST) in the Niño3.4 region in January 2000 ranging from -2°C to 30°C from the CESM Earth system models historical simulation for the Sixth Phase of the Coupled Intercomparison Project (CMIP6). The closer to the equator, the colder the water masses at the surface caused by upwelling from below induced by easterly winds and consequent Ekman transport.\n",
-    "\n",
-    "*** \n",
-    "\n",
-    "</details>"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "execution": {}
-   },
-   "source": [
-    "### Interactive Demo 2.2"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "execution": {}
-   },
-   "source": [
-    "Below we plot an interactive version of the Niño 3.4 region. You can explore the data by zooming in with the tools from the righthand toolbar and visualize what the next few time steps look like in the model by using the interactive slider bar on the most right. Note that the color bar and the corresponding SST scale have changed to make the changing pattern more visible. \n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# again more complicated code that allows interactive plots\n",
@@ -859,9 +758,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# group the dataset by month\n",
@@ -903,9 +800,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# smooth using a centered 3 month running mean\n",
@@ -916,7 +811,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 975,
      "status": "ok",
@@ -989,7 +883,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 1326,
      "status": "ok",
@@ -1071,9 +964,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# to_remove explanation\n",
@@ -1085,6 +976,16 @@
     "\"\"\""
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_3\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -1141,7 +1042,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.19"
+   "version": "3.9.18"
   },
   "toc-autonumbering": false,
   "toc-showcode": false,
diff --git a/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/W1D2_Tutorial2.ipynb b/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/W1D2_Tutorial2.ipynb
index 5b8ab8e30..11eaa6e29 100644
--- a/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/W1D2_Tutorial2.ipynb
+++ b/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/W1D2_Tutorial2.ipynb
@@ -64,7 +64,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "tags": [
      "colab"
     ]
@@ -81,9 +80,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "import cdsapi\n",
@@ -105,12 +102,37 @@
     "warnings.filterwarnings('ignore')"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D2_T2\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "form",
-    "execution": {}
+    "cellView": "form"
    },
    "outputs": [],
    "source": [
@@ -138,26 +160,6 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
-    "execution": {},
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "# @title Figure Settings\n",
-    "import ipywidgets as widgets  # interactive display\n",
-    "\n",
-    "%config InlineBackend.figure_format = 'retina'\n",
-    "plt.style.use(\n",
-    "    \"https://raw.githubusercontent.com/neuromatch/climate-course-content/main/cma.mplstyle\"\n",
-    ")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "cellView": "form",
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -176,7 +178,6 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -229,6 +230,16 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_ECMWF_Reanalysis_Video\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -250,7 +261,7 @@
    "source": [
     "## Section 1.1: Accessing ERA5 Data\n",
     "\n",
-    "You will access the data through our OSF cloud storage to simplify the downloading process. If you are keen to download the data yourself or are simply interested in exploring other variables, please have a look into the ```get_ERA5_reanalysis_data.ipynb``` notebook, where we use the Climate Data Store (CDS) API to get a subset of the huge [ECMWF ERA5 Reanalysis](https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-single-levels?tab=overview) data set.\n",
+    "You will access the data through our OSF cloud storage to simplify the downloading process. If you are keen to download the data yourself or are simply interested in exploring other variables, please have a look into the [```get_ERA5_reanalysis_data.ipynb```](https://github.com/neuromatch/climate-course-content/blob/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/get_ERA5_reanalysis_data.ipynb) notebook, where we use the Climate Data Store (CDS) API to get a subset of the huge [ECMWF ERA5 Reanalysis](https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-single-levels?tab=overview) data set.\n",
     "\n",
     "Let's select a specific year and month to work with, March of 2018:"
    ]
@@ -258,9 +269,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# load data: 5 variables of ERA5 reanalysis, subregion, hourly, March 2018\n",
@@ -272,9 +281,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "ERA5_allvars"
@@ -317,9 +324,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# compute ten-meter wind speed, the magnitude of the wind vector\n",
@@ -348,9 +353,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "ds_surface_temp_2m = ERA5_allvars.t2m\n",
@@ -369,9 +372,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "holoviews.extension(\"bokeh\")\n",
@@ -414,7 +415,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -427,46 +427,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "# interactive plot of hourly frequency of surface temperature\n",
-    "# this cell may take a little longer as it contains several maps in a single plotting function\n",
-    "dataset_plot = gv.Dataset(\n",
-    "    ds_surface_temp_2m_hour.isel(hour=slice(0, 12))\n",
-    ")  # only the first 12 time steps (midnight to noon), as it is a time-consuming task\n",
-    "images = dataset_plot.to(\n",
-    "    gv.Image, [\"longitude\", \"latitude\"], [\"t2m\"], \"hour\"\n",
-    ")\n",
-    "images.opts(\n",
-    "    cmap=\"coolwarm\",\n",
-    "    colorbar=True,\n",
-    "    width=600,\n",
-    "    height=400,\n",
-    "    projection=ccrs.PlateCarree(),\n",
-    "    clabel=\"2m Air Temperature (K)\",\n",
-    ") * gf.coastline"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
-   "outputs": [],
-   "source": [
-    "# average temperatures over the whole day after grouping by the day\n",
-    "ds_surface_temp_2m_day = ds_surface_temp_2m.groupby(\"time.day\").mean()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -492,9 +452,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# average temperatures over the whole day after grouping by the day\n",
@@ -504,9 +462,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# interactive plot of daily frequency of surface temperature\n",
@@ -533,23 +489,32 @@
     "execution": {}
    },
    "source": [
-    "### Question 2\n",
+    "### Questions 2\n",
+    "\n",
     "1. What differences do you notice between the hourly and daily interactive plots, and are there any interesting spatial patterns of these temperature changes?"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# to_remove explanation\n",
     "\n",
     "\"\"\"\n",
     "1. On hourly timescales, the largest changes are over land because it responds faster than the ocean to the diurnal cycle of solar radiation. This is because the ocean has a higher heat capacity than the land surface. On daily timescales, the surface atmospheric temperature shows comparable variations across both the ocean and land.\n",
-    "\"\"\";"
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_2\")"
    ]
   },
   {
@@ -573,7 +538,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -589,9 +553,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# plot the time series of surface temperature\n",
@@ -621,9 +583,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# to_remove explanation\n",
@@ -631,7 +591,17 @@
     "1. The high-frequency variability can largely be attributed to the diurnal cycle or the differences in solar radiation between night and day. This causes large variations in surface temperature, particularly over land and shallow water.\n",
     "2. The low-frequency variability can be attributed to synoptic patterns (e.g., weather) which can move cold or warm air around on timescales of days to weeks.\n",
     "3. We do not have a long enough time series for ENSO to show up, but ENSO could indirectly affect this time series by changing weather patterns on shorter timescales.\n",
-    "\"\"\";"
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_3_1\")"
    ]
   },
   {
@@ -648,9 +618,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "ERA5_allvars_ts = ERA5_allvars.weighted(weights).mean([\"longitude\", \"latitude\"])\n",
@@ -660,9 +628,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "plot_vars = [\n",
@@ -703,9 +669,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# to_remove explanation\n",
@@ -714,7 +678,17 @@
     "2. The surface pressure, which is usually associated with storms, is dominated by the synoptic scale.\n",
     "3. The 10-meter wind speed shows influences from both the diurnal cycle and the synoptic scale.\n",
     "4. The ocean surface temperature shows some sensitivity to the diurnal cycle but is dominated by longer timescale (>weeks) variations than the atmospheric variables.\n",
-    "\"\"\";"
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_3_2\")"
    ]
   },
   {
@@ -738,7 +712,7 @@
    "source": [
     "# Resources\n",
     "\n",
-    "Data for this tutorial can be accessed [here](https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-single-levels?tab=overview). We summarized the download procedure in a separate notebook named ```get_ERA5_reanalysis_data.ipynb```."
+    "Data for this tutorial can be accessed [here](https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-single-levels?tab=overview). We summarized the download procedure in a separate notebook named [```get_ERA5_reanalysis_data.ipynb```](https://github.com/neuromatch/climate-course-content/blob/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/get_ERA5_reanalysis_data.ipynb)."
    ]
   }
  ],
@@ -770,7 +744,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.19"
+   "version": "3.9.18"
   },
   "toc-autonumbering": true
  },
diff --git a/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/W1D2_Tutorial3.ipynb b/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/W1D2_Tutorial3.ipynb
index 4d7491ca5..bb690544a 100644
--- a/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/W1D2_Tutorial3.ipynb
+++ b/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/W1D2_Tutorial3.ipynb
@@ -96,6 +96,32 @@
     "warnings.filterwarnings(\"ignore\")"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D2_T3\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -249,6 +275,16 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Wind_Driven_Circulation_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -269,14 +305,18 @@
     "\n",
     "link_id = \"t6c78\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Wind_Driven_Circulation_Slides\")"
    ]
   },
   {
@@ -499,6 +539,16 @@
     "</details>"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Coding_Exercise_1_1\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -520,7 +570,17 @@
     "'''\n",
     "1. The Hadley Cell is the tropical region containing the easterlies (a.k.a. trade winds), and the Ferrel Cell is the mid-latitude region containing the westerlies.\n",
     "2. Meridional winds are typically weaker and less variable than zonal winds. This is due to the general circulation of the atmosphere, which primarily moves air in the east-west direction rather than north-south.TODO add smt here regarding longtiude and latitude\n",
-    "''';"
+    "'''"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_1_1\")"
    ]
   },
   {
@@ -596,22 +656,7 @@
     "\n",
     "\"\"\"\n",
     "1. The continents influence the strength of the winds, and since the continents are so unevenly distributed on the planet, the winds are weaker in the North than in the South. The strongest winds occur in the Southern Ocean, where there is little land, and must become very strong to create the same drag as over the large land masses of the Northern Hemisphere.\n",
-    "\"\"\";"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "execution": {}
-   },
-   "source": [
-    "# Section 2: Monthly Climatology\n",
-    "\n",
-    "Now, you should examine how the zonal mean winds vary throughout the seasons. You will focus on the zonal wind component and create a special type of diagram called a Hovmöller diagram. In this diagram, the horizontal axis represents latitude, while the vertical axis represents time.\n",
-    "\n",
-    "By using the [Hovmöller diagram](https://en.wikipedia.org/wiki/Hovm%C3%B6ller_diagram), you can visualize how the average east-west winds change over the annual cycle.\n",
-    "\n",
-    "At first, we average our original dataset over all longitudes to get the zonal mean of all variables. We then temporally average it with respect to all months, resulting in a data set with twelve time steps which represent the mean of every month over the whole period of January 1980 to December 2005 for all three variables (`u10`, `v10` and `si10`)."
+    "\"\"\""
    ]
   },
   {
@@ -620,21 +665,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Note how we use several commands in one line.\n",
-    "# Python performs them in order. First, calculate the zonal mean, then group by month, and lastly calculate the mean.\n",
-    "# The groupby method hereby regroups the data by month, such that all Januarys, all Februaries, .. can be averaged.\n",
-    "\n",
-    "ERA5_zmean_mmean = ERA5_mm.mean(\"longitude\").groupby(\"time.month\").mean()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Have a look at our new dataset, which incorporates the zonal mean and the temporal mean of every month\n",
-    "ERA5_zmean_mmean"
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_1_2\")"
    ]
   },
   {
@@ -643,11 +675,13 @@
     "execution": {}
    },
    "source": [
-    "We plot the zonal wind component `u10` of the wind vector versus month and latitude, i.e. the aforementioned Hovmöller diagram, which is a special type of [heatmap](https://en.wikipedia.org/wiki/Heat_map) and might remind you of the [Warming Stripes](https://en.wikipedia.org/wiki/Warming_stripes).\n",
+    "# Section 2: Monthly Climatology\n",
     "\n",
-    "It allows us to recognize both spatial (abscissa/ x-axis) and temporal changes (ordinate/ y-axis) in our variables. \n",
+    "Now, you should examine how the zonal mean winds vary throughout the seasons. You will focus on the zonal wind component and create a special type of diagram called a Hovmöller diagram. In this diagram, the horizontal axis represents latitude, while the vertical axis represents time.\n",
     "\n",
-    "Note that xarray uses the metadata of the dataset to label the axes, hence it does not look as pretty and insightful as our previous plots. If you have difficulties to interpret the output, perhaps it helps to look at the previous blue line plot, to compare the axes and to try to understand how the shown extrema translate into colors of the Hovmöller diagram."
+    "By using the [Hovmöller diagram](https://en.wikipedia.org/wiki/Hovm%C3%B6ller_diagram), you can visualize how the average east-west winds change over the annual cycle.\n",
+    "\n",
+    "At first, we average our original dataset over all longitudes to get the zonal mean of all variables. We then temporally average it with respect to all months, resulting in a data set with twelve time steps which represent the mean of every month over the whole period of January 1980 to December 2005 for all three variables (`u10`, `v10` and `si10`)."
    ]
   },
   {
@@ -759,6 +793,16 @@
     "</details>"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Coding_Exercises_2\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -814,6 +858,16 @@
     "ERA5_season_u10 = ERA5_mm.u10.sel(time=slice('2000','2005')).groupby('time.season').mean()"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Bonus_Coding_Exercise_3_1\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -892,6 +946,16 @@
     "plt.show()"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Bonus_Coding_Exercise_3_2\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
diff --git a/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/W1D2_Tutorial4.ipynb b/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/W1D2_Tutorial4.ipynb
index d988f5741..94649902b 100644
--- a/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/W1D2_Tutorial4.ipynb
+++ b/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/W1D2_Tutorial4.ipynb
@@ -66,7 +66,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "tags": [
      "colab"
     ]
@@ -75,16 +74,13 @@
    "source": [
     "# installations ( uncomment and run this cell ONLY when using google colab or kaggle )\n",
     "\n",
-    "# !pip install cartopy\n",
-    "# !pip install geoviews"
+    "# !pip install cartopy"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "import matplotlib.pyplot as plt\n",
@@ -99,12 +95,37 @@
     "warnings.filterwarnings(\"ignore\")"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D2_T4\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "form",
-    "execution": {}
+    "cellView": "form"
    },
    "outputs": [],
    "source": [
@@ -131,8 +152,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "form",
-    "execution": {}
+    "cellView": "form"
    },
    "outputs": [],
    "source": [
@@ -150,25 +170,6 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
-    "execution": {}
-   },
-   "outputs": [],
-   "source": [
-    "# @title Figure Settings\n",
-    "import ipywidgets as widgets  # interactive display\n",
-    "\n",
-    "%config InlineBackend.figure_format = 'retina'\n",
-    "plt.style.use(\n",
-    "    \"https://raw.githubusercontent.com/neuromatch/climate-course-content/main/cma.mplstyle\"\n",
-    ")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "cellView": "form",
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -221,12 +222,21 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Ocean_Wind_Driven_Circulation_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
     "cellView": "form",
-    "execution": {},
     "pycharm": {
      "name": "#%%\n"
     },
@@ -242,14 +252,18 @@
     "\n",
     "link_id = \"f8c5r\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Ocean_Wind_Driven_Circulation_Slides\")"
    ]
   },
   {
@@ -277,8 +291,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "both",
-    "execution": {}
+    "cellView": "both"
    },
    "outputs": [],
    "source": [
@@ -293,9 +306,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# wind in north/south direction labeled here as 'v'\n",
@@ -308,9 +319,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# load data: oceanic surface current from ECCO\n",
@@ -326,12 +335,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
-    "#TODO file contains wrong variable EVEL instead of nvel CHECK ipynb file from Aurora\n",
     "# current in east/west direction labeled here as 'v'\n",
     "fname_ocn_surface_current_v = \"nvel_monthly_2016.nc\"\n",
     "url_ocn_surface_current_v = \"https://osf.io/vzdn4/download\"\n",
@@ -357,9 +363,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "atm_wind_u.time"
@@ -379,9 +383,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# to_remove explanation\n",
@@ -389,7 +391,17 @@
     "\"\"\"\n",
     "1. The atmospheric dataset has a higher output frequency than the oceanic dataset because of the different timescales on which the atmosphere and the ocean change significantly. The atmosphere has a lower heat capacity (i.e., thermal inertia) and density than the ocean. This means that the temperature and wind speed (which is related to momentum) of the atmosphere can change rapidly (over minutes to hours), while the ocean temperature and currents change more slowly.\n",
     "2. The atmosphere plays a faster, more immediate role in the climate system than the ocean. It reacts quickly to heat and pressure differences, driving weather and synoptic features. The ocean, on the other hand, plays a longer-term role in the climate system and provides a buffering effect against rapid atmospheric changes.\n",
-    "\"\"\";"
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_1_1\")"
    ]
   },
   {
@@ -409,9 +421,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# compute the annual mean of atm_wind_u\n",
@@ -422,9 +432,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# take the annual mean of atm_wind_stress_v\n",
@@ -456,9 +464,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "fname_surface_temp = \"surface_theta.nc\"\n",
@@ -472,9 +478,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# longitude ad latitude coordinates for plotting\n",
@@ -533,7 +537,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -546,9 +549,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# take the annual mean of ocn_surface_current_v\n",
@@ -568,9 +569,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# longitude ad latitude coordinates for plotting\n",
@@ -639,9 +638,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# to_remove explanation\n",
@@ -649,7 +646,17 @@
     "\"\"\"\n",
     "1. Yes, the surface currents are deflected relative to the surface winds, and this seems to happen globally.\n",
     "2. The deflection of the ocean surface current is to the left of the wind in the Southern Hemisphere, and is to the right of the wind in the Northern Hemisphere. This property is predicted by Ekman flow.\n",
-    "\"\"\";"
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_3\")"
    ]
   },
   {
@@ -714,7 +721,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.19"
+   "version": "3.9.18"
   },
   "toc-autonumbering": true
  },
diff --git a/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/W1D2_Tutorial5.ipynb b/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/W1D2_Tutorial5.ipynb
index 1e27bba4c..aeb789442 100644
--- a/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/W1D2_Tutorial5.ipynb
+++ b/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/W1D2_Tutorial5.ipynb
@@ -61,7 +61,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "tags": [
      "colab"
     ]
@@ -80,7 +79,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 2058,
      "status": "error",
@@ -107,12 +105,37 @@
     "import gsw"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D2_T5\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "form",
-    "execution": {}
+    "cellView": "form"
    },
    "outputs": [],
    "source": [
@@ -139,26 +162,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "form",
-    "execution": {}
-   },
-   "outputs": [],
-   "source": [
-    "# @title Figure Settings\n",
-    "import ipywidgets as widgets  # interactive display\n",
-    "\n",
-    "%config InlineBackend.figure_format = 'retina'\n",
-    "plt.style.use(\n",
-    "    \"https://raw.githubusercontent.com/neuromatch/climate-course-content/main/cma.mplstyle\"\n",
-    ")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "cellView": "form",
-    "execution": {}
+    "cellView": "form"
    },
    "outputs": [],
    "source": [
@@ -176,7 +180,6 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -229,12 +232,21 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Thermohaline_Circulation_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
     "cellView": "form",
-    "execution": {},
     "pycharm": {
      "name": "#%%\n"
     },
@@ -250,14 +262,18 @@
     "\n",
     "link_id = \"vdeq6\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Thermohaline_Circulation_Slides\")"
    ]
   },
   {
@@ -280,9 +296,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# import preprocessed ecco data. This is surface data of monthly resolution over the period 2014 to 2016.\n",
@@ -297,9 +311,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# load salinity\n",
@@ -313,9 +325,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# make land points NaN (not a number)\n",
@@ -330,9 +340,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# plot Sea Surface Temprature - similar to plots we used in tutorials 2+3\n",
@@ -378,9 +386,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# plot Sea Surface Salinity\n",
@@ -445,7 +451,7 @@
    },
    "source": [
     "## Section 2.1: Linearized Equation of State\n",
-    "Here we take the linearized equation of state from equation 1.57 in Vallis' textbook [\"*Atmospheric and Oceanic Fluid Dynamics*\"](https://www.cambridge.org/core/books/atmospheric-and-oceanic-fluid-dynamics/41379BDDC4257CBE11143C466F6428A4)\n",
+    "Here we take the linearized equation of state from equation 1.57 in Vallis' textbook [\"*Atmospheric and Oceanic Fluid Dynamics*\"](https://www.cambridge.org/core/books/atmospheric-and-oceanic-fluid-dynamics/41379BDDC4257CBE11143C466F6428A4) (not Open-access)\n",
     "\n",
     "$$ \\rho=\\rho_0[1-\\beta_T(T-T_0)+\\beta_S(S-S_0)+\\beta_p(p-p_0)] $$\n",
     "\n",
@@ -457,9 +463,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "rho_linear = 1027 * (\n",
@@ -471,9 +475,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# plot linearized density\n",
@@ -517,9 +519,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "CT = gsw.CT_from_pt(\n",
@@ -531,9 +531,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# plot density from full nonlinear equation\n",
@@ -566,9 +564,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# plot difference between linear and non-linear equations of state\n",
@@ -626,9 +622,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# to_remove explanation\n",
@@ -636,7 +630,17 @@
     "\"\"\"\n",
     "1. When salinity rises, the water's capacity to contract in response to added salt (haline contraction coefficient) generally increases. Similarly, as temperature decreases, water's volume expansion due to heating (thermal expansion coefficient) generally decreases. These variations can significantly affect seawater density, creating pressure gradients that in turn influence the intensity and direction of ocean currents.\n",
     "2. The surface water in this region has a larger density than the surface water surrounding it, making it relatively likely that this surface water will be dense enough to sink and mix with the waters below. Conversely, the same latitude in the Pacific is much less dense (due to fresher water) and there is no deep water formation that takes place here.\n",
-    "\"\"\";"
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_2_2\")"
    ]
   },
   {
@@ -690,7 +694,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.19"
+   "version": "3.9.18"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/W1D2_Tutorial6.ipynb b/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/W1D2_Tutorial6.ipynb
index 88cf37124..705df059d 100644
--- a/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/W1D2_Tutorial6.ipynb
+++ b/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/W1D2_Tutorial6.ipynb
@@ -66,7 +66,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "tags": [
      "colab"
     ]
@@ -82,9 +81,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "import xarray as xr\n",
@@ -97,12 +94,37 @@
     "import tempfile"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D2_T6\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "form",
-    "execution": {}
+    "cellView": "form"
    },
    "outputs": [],
    "source": [
@@ -129,26 +151,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "form",
-    "execution": {}
-   },
-   "outputs": [],
-   "source": [
-    "# @title Figure Settings\n",
-    "import ipywidgets as widgets  # interactive display\n",
-    "\n",
-    "%config InlineBackend.figure_format = 'retina'\n",
-    "plt.style.use(\n",
-    "    \"https://raw.githubusercontent.com/neuromatch/climate-course-content/main/cma.mplstyle\"\n",
-    ")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "cellView": "form",
-    "execution": {}
+    "cellView": "form"
    },
    "outputs": [],
    "source": [
@@ -166,7 +169,6 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -224,7 +226,6 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
-    "execution": {},
     "pycharm": {
      "name": "#%%\n"
     },
@@ -240,14 +241,8 @@
     "\n",
     "link_id = \"vyb68\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
    ]
   },
   {
@@ -266,9 +261,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# import preprocessed ECCO data. This data is full depth temperature data over 1992 to 2016 (annual mean)\n",
@@ -296,32 +289,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
-   "outputs": [],
-   "source": [
-    "# Quick plot of the ocean temperature in Kelvin\n",
-    "theta_annual.sel(year=1992,Z=-5.0).plot(cmap=cmo.cm.thermal,\n",
-    "                                        add_labels=True\n",
-    "                                       )"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "execution": {}
-   },
-   "source": [
-    "The ECCO ocean temperature (`THETA`) is provided in the [SI unit](https://en.wikipedia.org/wiki/International_System_of_Units) Kelvin (K), which might be less intuitive to us. So let us now slice a few years from the data, average it temporally and convert it to degrees Celsius (°C)."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# Quick plot of the ocean temperature in Kelvin\n",
@@ -342,9 +310,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# take the temporal mean over the period 1992 to 1994\n",
@@ -366,9 +332,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# plot the zonal mean section of this data\n",
@@ -408,9 +372,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "theta_area_int = (\n",
@@ -421,9 +383,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# define reference density of salt water and the specific heat capacity\n",
@@ -462,22 +422,6 @@
     "</details>"
    ]
   },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "execution": {}
-   },
-   "source": [
-    "<details>\n",
-    "<summary><font color='orangered'>Click here for a description of the plot  </font></summary>\n",
-    "Heat content that is contained in the water mass from the surface to the respective depth, for all depths calculated with a cumulative sum. \n",
-    "Hence, the overall global ocean heat, integrated from 6000m to the surface, is approximately 0.02 * 10^6 ZJ.\n",
-    "\n",
-    "***\n",
-    "\n",
-    "</details>"
-   ]
-  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -494,9 +438,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "area_of_ocean = (\n",
@@ -518,7 +460,7 @@
     "execution": {}
    },
    "source": [
-    "## Question 1\n",
+    "## Questions 1\n",
     "\n",
     "1. Based on the last two plots, are depth-variations in ocean heat content primarily due to vertical changes in the temperature or area of the ocean?\n"
    ]
@@ -526,16 +468,24 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# to_remove explanation\n",
     "\n",
     "\"\"\"\n",
     "1. The volume as a function of depth has a shape that is almost identical to the ocean heat content plot, which indicates that the ocean heat content above each depth is primarily shaped by depth-variations in the global ocean's area.\n",
-    "\"\"\";"
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_1\")"
    ]
   },
   {
@@ -561,9 +511,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# this cell may take a while to run!\n",
@@ -645,9 +593,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "fig, ax = plt.subplots()\n",
@@ -688,16 +634,24 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# to_remove explanation\n",
     "\n",
     "\"\"\"\n",
     "1. The total heat gain is around 190 ZJ, while the upper layers have gained roughly 130 ZJ (above 700 m) and 35 ZJ (700-2000 m). This means the upper 2000 m contain (130+35)/190 = 87% of the ocean's heat gain, despite containing only ~50% of the ocean's water (see the volume plot you created in Section 1).\n",
-    "\"\"\";"
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_2\")"
    ]
   },
   {
@@ -721,9 +675,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# first let's plot where heat is stored in the mean\n",
@@ -777,9 +729,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# we already defined an object that's the mean over years 1992 to 1994 (subset_theta)\n",
@@ -807,9 +757,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# plot 2 maps to compare changes in heat content in those two layers\n",
@@ -928,7 +876,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.19"
+   "version": "3.9.18"
   }
  },
  "nbformat": 4,

From 231b22022fe445c88b01c63cb032f1c250581b6e Mon Sep 17 00:00:00 2001
From: Paul Heubel <paul_heubel@web.de>
Date: Fri, 5 Jul 2024 15:54:18 +0200
Subject: [PATCH 05/34] Added Lipd package for Paleoclimate day.

---
 environment.yml  | 3 ++-
 requirements.txt | 1 +
 2 files changed, 3 insertions(+), 1 deletion(-)

diff --git a/environment.yml b/environment.yml
index 9c14c9bcd..14a86c06d 100644
--- a/environment.yml
+++ b/environment.yml
@@ -123,8 +123,9 @@ dependencies:
  - zarr
  - pip:
    - afinn
+   - lipd
    - pyleoclim
    - "mystatsfunctions @ https://github.com/njleach/mystatsfunctions/archive/main.zip"
 #   - "SDFC @ https://github.com/yrobink/SDFC/archive/master.zip" # this is not working
-   -  https://github.com/mptouzel/PyDICE/archive/master.zip # for W2D3 Tutorial 2
+#   -  https://github.com/mptouzel/PyDICE/archive/master.zip # for W2D3 Tutorial 2
 
diff --git a/requirements.txt b/requirements.txt
index a263b610f..b342921d8 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -46,4 +46,5 @@ mystatsfunctions @ https://github.com/njleach/mystatsfunctions/archive/main.zip
 dicelib @ https://github.com/mptouzel/PyDICE/archive/master.zip
 cdsapi
 texttable
+lipd
 # cfgrib

From 9815c9e4376050be9bee69abd51b0127aaf603c6 Mon Sep 17 00:00:00 2001
From: Paul Heubel <paul_heubel@web.de>
Date: Mon, 8 Jul 2024 11:38:05 +0200
Subject: [PATCH 06/34] Added feedback widget.

---
 .../W1D3_Tutorial1.ipynb                      | 58 +++++++++++++---
 .../W1D3_Tutorial2.ipynb                      | 67 ++++++++++++++-----
 2 files changed, 100 insertions(+), 25 deletions(-)

diff --git a/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/W1D3_Tutorial1.ipynb b/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/W1D3_Tutorial1.ipynb
index d88ad51e7..2ed1f5667 100644
--- a/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/W1D3_Tutorial1.ipynb
+++ b/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/W1D3_Tutorial1.ipynb
@@ -50,6 +50,32 @@
     "- Appreciate the value and benefits of satellite remote sensing for climate studies through selected examples.\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D3_T1\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -117,6 +143,16 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Intro_Remote_Sensing_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -138,14 +174,18 @@
     "\n",
     "link_id = \"k6dre\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Intro_Remote_Sensing_Slides\")"
    ]
   },
   {
@@ -500,7 +540,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.19"
+   "version": "3.9.18"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/W1D3_Tutorial2.ipynb b/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/W1D3_Tutorial2.ipynb
index 1ee0f3178..bff68fa77 100644
--- a/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/W1D3_Tutorial2.ipynb
+++ b/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/W1D3_Tutorial2.ipynb
@@ -47,12 +47,37 @@
     "- Navigate and utilize these datasets in your own climate-related studies or projects.\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D3_T2\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
     "cellView": "form",
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -105,12 +130,21 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Satellite_Climate_Data_Records_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
     "cellView": "form",
-    "execution": {},
     "pycharm": {
      "name": "#%%\n"
     },
@@ -126,14 +160,18 @@
     "\n",
     "link_id = \"7vsqd\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Satellite_Climate_Data_Records_Slides\")"
    ]
   },
   {
@@ -252,7 +290,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -263,7 +300,7 @@
     "\n",
     "Option C would be preferred. You need data that overlaps with your timeframe of interest, which eliminates Option A. In order to use data from multiple sensored the 'inter-satellite' calibration described above should be completed.\n",
     "\n",
-    "\"\"\";"
+    "\"\"\""
    ]
   },
   {
@@ -420,9 +457,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "### Step 1: Describe your application interest. Be as specific as you can, this\n",
@@ -487,7 +522,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.19"
+   "version": "3.9.18"
   }
  },
  "nbformat": 4,

From a7f1db1298c744d9a6c7352663517550a8fdc91c Mon Sep 17 00:00:00 2001
From: Paul Heubel <paul_heubel@web.de>
Date: Mon, 8 Jul 2024 11:39:55 +0200
Subject: [PATCH 07/34] Added feedback widget, content edit due to changed
 naming conventions after quality control in 2024 data retrieval. Fixed typos,
 simplified slide cell.

---
 .../W1D3_Tutorial3.ipynb                      | 125 ++++++++++++------
 1 file changed, 82 insertions(+), 43 deletions(-)

diff --git a/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/W1D3_Tutorial3.ipynb b/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/W1D3_Tutorial3.ipynb
index 9b6071204..e8b578cbd 100644
--- a/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/W1D3_Tutorial3.ipynb
+++ b/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/W1D3_Tutorial3.ipynb
@@ -61,7 +61,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "tags": [
      "colab"
     ]
@@ -91,7 +90,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -109,12 +107,37 @@
     "import tempfile"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D3_T3\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
     "cellView": "form",
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -132,8 +155,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "form",
-    "execution": {}
+    "cellView": "form"
    },
    "outputs": [],
    "source": [
@@ -161,12 +183,11 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
-    "execution": {},
     "tags": []
    },
    "outputs": [],
    "source": [
-    "# @title Video 1: Access and Vizualise Satellite CDR\n",
+    "# @title Video 1: Access and Visualize Satellite CDR\n",
     "\n",
     "from ipywidgets import widgets\n",
     "from IPython.display import YouTubeVideo\n",
@@ -214,12 +235,21 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Access_Visualize_Satellite_CDR_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
     "cellView": "form",
-    "execution": {},
     "pycharm": {
      "name": "#%%\n"
     },
@@ -235,14 +265,18 @@
     "\n",
     "link_id = \"g9n5d\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Access_Visualize_Satellite_CDR_Slides\")"
    ]
   },
   {
@@ -280,38 +314,36 @@
     "execution": {}
    },
    "source": [
-    "TODO this needs major update! PH\n",
-    "\n",
     "If we go to the [cloud storage space (or a S3 bucket)](https://noaa-cdr-ndvi-pds.s3.amazonaws.com/index.html#data/) that hosts NOAA NDVI CDR data, you will see the pattern of how the NOAA NDVI CDR is organized:\n",
     "\n",
-    "`s3://noaa-cdr-ndvi-pds/data/2024/VIIRS-Land_v001-preliminary_NPP13C1_S-NPP_20240101_c20240110134720.nc`\n",
+    "`s3://noaa-cdr-ndvi-pds/data/2024/VIIRS-Land_v001_NPP13C1_S-NPP_20220101_c20240126162652.nc`\n",
     "\n",
     "We can take advantage of the pattern to search for the data file systematically. \n",
     "\n",
     "> Parent directory: `s3://noaa-cdr-ndvi-pds/data/`\n",
-    "> Sub-directory for each year: `2024/`\n",
-    "> File name of each day: `VIIRS-Land_v001-preliminary_NPP13C1_S-NPP_20240101_c20240110134720.nc`\n",
+    "> Sub-directory for each year: `2022/`\n",
+    "> File name of each day: `VIIRS-Land_v001_NPP13C1_S-NPP_20220101_c20240126162652.nc`\n",
     "\n",
     "The file name also has a clear pattern:\n",
     "\n",
     "> Sensor name: `VIIRS`  \n",
     "> Product category: `Land`  \n",
-    "> Product version: `v001-preliminary`  (*This might change soon*)\n",
-    "> Product type: `NPP13C1`  \n",
-    "> Satellite platform: `S-NPP`  \n",
-    "> Date of the data: `20240101`  \n",
-    "> Processing time: `c20240110134720` (*This will change for each file based on when the file was processed*)  \n",
+    "> Product version: `v001`\n",
+    "> Product type: `NPP13C1`  (*JP113C1 in 2024, so dependent on the satellite era*)\n",
+    "> Satellite platform: `S-NPP`  (*NOAA-20 in 2024, so dependent on the satellite era*)\n",
+    "> Date of the data: `20220101`  \n",
+    "> Processing time: `c20240126162652` (*This will change for each file based on when the file was processed*)  \n",
     "> File format: `.nc` (*netCDR-4 format*)\n",
     "\n",
     "In other words, if we are looking for the data of a specific day, we can easily locate where the file might be. \n",
     "\n",
-    "Note that the above example data is from 2024 and therefore very new, that is why it is called `v001-preliminary` at the moment. Quality control might soon lead to changes in the naming and availability.\n",
+    "Note that the above example data is from 2022, measurements from 2024 are very new, which is why there it was called `v001-preliminary` before. Quality control often leads to changes in the naming and availability. So be prepared that you have to check the data tree of your source regularly.\n",
     "\n",
-    "For example, if we want to find the VIIRS data for the day of *2014-03-12 (or March 12, 2014)*, you can use:\n",
+    "For example, if we now want to find the VIIRS data for the day of *2014-03-12 (or March 12, 2014)*, you can use:\n",
     "\n",
     "`s3://noaa-cdr-ndvi-pds/data/2014/VIIRS-Land_v001_NPP13C1_*_20140312_c*.nc`\n",
     "\n",
-    "You see, we had to remove the `preliminary` tag, as the `2014` data passed quality control already.\n",
+    "You see, we do not need a `preliminary` tag, as the `2014` data passed quality control already.\n",
     "\n",
     "The reason that we put `*` in the above directory is that we are not sure about what satellite platform this data is from and when the data was processed. The `*` is called a **wildcard**, and is used because we want *all* the files that contain our specific criteria, but do not want to have to specify all the other pieces of the filename we are not sure about yet. It should return all the data satisfying that initial criteria and you can refine further once you see what is available. Essentially, this first step helps to narrow down the data search.\n",
     "\n",
@@ -323,7 +355,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -364,7 +395,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -383,7 +413,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -407,6 +436,16 @@
     "# VIIRS-Land_v001_NPP13C1_S-NPP_20190901_c20240125203558.nc"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Coding_Exercise_1_1\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -423,7 +462,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -476,7 +514,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -500,7 +537,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -595,7 +631,6 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -642,7 +677,6 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -679,7 +713,6 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -708,7 +741,6 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -731,7 +763,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -766,7 +797,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -798,7 +828,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -842,6 +871,16 @@
     "# )"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Coding_Exercise_1_4\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -906,7 +945,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.19"
+   "version": "3.9.18"
   }
  },
  "nbformat": 4,

From f3fb2c121f84768af7fcde2b7da32ecd0b33ab12 Mon Sep 17 00:00:00 2001
From: Paul Heubel <paul_heubel@web.de>
Date: Mon, 8 Jul 2024 11:41:36 +0200
Subject: [PATCH 08/34] Added feedback widget, simplified slide cell, fixed
 typo in section header, removed figsizes kwargs due to ugly renderering in
 book.

---
 .../W1D3_Tutorial4.ipynb                      | 132 ++++++++++++------
 1 file changed, 93 insertions(+), 39 deletions(-)

diff --git a/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/W1D3_Tutorial4.ipynb b/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/W1D3_Tutorial4.ipynb
index 8a6bda3b2..c52dfa0f5 100644
--- a/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/W1D3_Tutorial4.ipynb
+++ b/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/W1D3_Tutorial4.ipynb
@@ -64,7 +64,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "tags": [
      "colab"
     ]
@@ -94,7 +93,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -111,12 +109,37 @@
     "import tempfile"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D3_T4\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
     "cellView": "form",
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -134,8 +157,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "form",
-    "execution": {}
+    "cellView": "form"
    },
    "outputs": [],
    "source": [
@@ -163,7 +185,6 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -216,12 +237,21 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Understanding_Climatology_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
     "cellView": "form",
-    "execution": {},
     "pycharm": {
      "name": "#%%\n"
     },
@@ -237,14 +267,18 @@
     "\n",
     "link_id = \"2ak68\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Understanding_Climatology_Slides\")"
    ]
   },
   {
@@ -285,7 +319,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -303,7 +336,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -325,7 +357,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -360,7 +391,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -382,7 +412,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -401,7 +430,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -431,7 +459,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -472,7 +499,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -497,7 +523,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -557,7 +582,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -582,7 +606,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -610,6 +633,16 @@
     ")"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Coding_Exercise_1_2\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -633,7 +666,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -646,6 +678,16 @@
     "'''"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_1_2\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -678,7 +720,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -727,7 +768,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -752,7 +792,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -775,7 +814,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -830,7 +868,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -845,6 +882,16 @@
     "\"\"\""
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_2_2\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -858,7 +905,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -894,7 +940,7 @@
     "execution": {}
    },
    "source": [
-    "### Coding Exercises 2.1\n",
+    "### Coding Exercises 2.2\n",
     "\n",
     "As climate changes, the climatology of precipitation may also change. In fact, climate researchers recalculate a climatology every 10 years. This allows them to monitor how the norms of our climate system change. In this exercise, you will visualize how the climatology of our dataset changes depending on the reference period used.\n",
     "\n",
@@ -905,7 +951,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -924,7 +969,7 @@
     "\n",
     "# Define the figure and each axis for the 2 rows and 2 columns\n",
     "fig, axs = plt.subplots(\n",
-    "    nrows=2, ncols=2, subplot_kw={\"projection\": ccrs.Robinson()}, figsize=(12, 8)\n",
+    "    nrows=2, ncols=2, subplot_kw={\"projection\": ccrs.Robinson()}#, figsize=(12, 8)\n",
     ")\n",
     "\n",
     "# axs is a 2-dimensional array of `GeoAxes`. We will flatten it into a 1-D array\n",
@@ -939,7 +984,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -960,7 +1004,7 @@
     "\n",
     "# Define the figure and each axis for the 2 rows and 2 columns\n",
     "fig, axs = plt.subplots(\n",
-    "    nrows=2, ncols=2, subplot_kw={\"projection\": ccrs.Robinson()}, figsize=(12, 8)\n",
+    "    nrows=2, ncols=2, subplot_kw={\"projection\": ccrs.Robinson()}#, figsize=(12, 8)\n",
     ")\n",
     "\n",
     "# axs is a 2-dimensional array of `GeoAxes`. We will flatten it into a 1-D array\n",
@@ -983,6 +1027,16 @@
     "    )"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Coding_Exercise_2_2\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -1046,7 +1100,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.19"
+   "version": "3.9.18"
   }
  },
  "nbformat": 4,

From 8602055387b2ae787735bf1323dd9e0171236ea4 Mon Sep 17 00:00:00 2001
From: Paul Heubel <paul_heubel@web.de>
Date: Mon, 8 Jul 2024 11:44:31 +0200
Subject: [PATCH 09/34] Added feedback widget, removed ";" that slows down
 processing, simplified slide cell

---
 .../W1D3_Tutorial5.ipynb                      | 174 +++++++++++-------
 .../W1D3_Tutorial6.ipynb                      | 110 +++++++----
 2 files changed, 180 insertions(+), 104 deletions(-)

diff --git a/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/W1D3_Tutorial5.ipynb b/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/W1D3_Tutorial5.ipynb
index 48fedd6c1..21f3cbe92 100644
--- a/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/W1D3_Tutorial5.ipynb
+++ b/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/W1D3_Tutorial5.ipynb
@@ -60,7 +60,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "tags": [
      "colab"
     ]
@@ -90,9 +89,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# imports\n",
@@ -112,12 +109,37 @@
     "from geoviews import Image as gvImage"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D3_T5\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "form",
-    "execution": {}
+    "cellView": "form"
    },
    "outputs": [],
    "source": [
@@ -134,8 +156,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "form",
-    "execution": {}
+    "cellView": "form"
    },
    "outputs": [],
    "source": [
@@ -163,7 +184,6 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -216,12 +236,21 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Calculating_Anomaly_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
     "cellView": "form",
-    "execution": {},
     "pycharm": {
      "name": "#%%\n"
     },
@@ -237,14 +266,18 @@
     "\n",
     "link_id = \"kvdgr\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Calculating_Anomaly_Slides\")"
    ]
   },
   {
@@ -276,9 +309,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# connect to the AWS S3 bucket for the GPCP Monthly Precipitation CDR data\n",
@@ -311,9 +342,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# calculate climatology using `.sel()` and `.groupby()` directly.\n",
@@ -339,9 +368,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# use `.groupby()` to calculate the monthly anomaly\n",
@@ -363,9 +390,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# an example of how to export the GPCP monthly anomaly data comparing to the climatology period of 1981-2010.\n",
@@ -386,9 +411,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# initate plot\n",
@@ -439,7 +462,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -472,9 +494,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# set up two subplots that share the x-axis to compare monthly precipitation and monthly anomaly\n",
@@ -540,9 +560,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# calculate 12-month rolling mean for the selected location\n",
@@ -553,9 +571,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# create the time series plot of monthly anomaly\n",
@@ -595,9 +611,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# calculate 24-month rolling mean\n",
@@ -621,9 +635,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# to_remove solution\n",
@@ -646,6 +658,16 @@
     "ax.grid(True)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Coding_Exercise_2_1\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -662,7 +684,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -677,6 +698,16 @@
     "\"\"\""
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_2_1\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -693,9 +724,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# calculate the weights using the latitude coordinates\n",
@@ -707,9 +736,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# calculate weighted global monthly mean\n",
@@ -721,9 +748,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# create the time series plot of global weighted monthly anomaly\n",
@@ -753,9 +778,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# calculate unweighted global mean\n",
@@ -780,9 +803,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# to_remove solution\n",
@@ -808,6 +829,16 @@
     "ax.grid(True)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Coding_Exercise_2_2\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -823,7 +854,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -837,6 +867,16 @@
     "\"\"\""
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_2_2\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -900,7 +940,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.19"
+   "version": "3.9.18"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/W1D3_Tutorial6.ipynb b/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/W1D3_Tutorial6.ipynb
index 1800c441a..8d832bcbd 100644
--- a/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/W1D3_Tutorial6.ipynb
+++ b/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/W1D3_Tutorial6.ipynb
@@ -61,7 +61,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "tags": [
      "colab"
     ]
@@ -90,7 +89,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -110,12 +108,37 @@
     "from geoviews import Image as gvImage"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D3_T6\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
     "cellView": "form",
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -133,8 +156,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "form",
-    "execution": {}
+    "cellView": "form"
    },
    "outputs": [],
    "source": [
@@ -162,7 +184,6 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -215,12 +236,21 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Satellite_Data_Climate_Variability_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
     "cellView": "form",
-    "execution": {},
     "pycharm": {
      "name": "#%%\n"
     },
@@ -236,14 +266,18 @@
     "\n",
     "link_id = \"zkbaf\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Satellite_Data_Climate_Variability_Slides\")"
    ]
   },
   {
@@ -289,7 +323,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -329,7 +362,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -346,7 +378,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -369,7 +400,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -410,7 +440,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -448,7 +477,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -462,7 +490,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -483,9 +510,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "nino34.to_netcdf('nino34_timeseries.nc')\n",
@@ -496,9 +521,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "nino34"
@@ -508,7 +531,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -535,7 +557,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -572,7 +593,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -626,7 +646,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -651,7 +670,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -689,7 +707,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -727,6 +744,16 @@
     "ax.legend()"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Coding_Exercise_1_2\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -744,7 +771,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -755,7 +781,17 @@
     "1. The index using the 1982-2011 reference period is always a little larger than the 1991-2020 reference period curve.\n",
     "2. This means that the climatology values for the 1991-2020 reference period were larger than that of 1982-2011.\n",
     "3. This can help remove long term trends (e.g. from warming) that can obscure the anomalies and ensures the anomaly is to the correct 'normal'.\n",
-    "''';"
+    "'''"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_1_2\")"
    ]
   },
   {
@@ -820,7 +856,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.19"
+   "version": "3.9.18"
   }
  },
  "nbformat": 4,

From 1c037e18b952f8935dd3f6d7e55ac9cb98342614 Mon Sep 17 00:00:00 2001
From: Paul Heubel <paul_heubel@web.de>
Date: Mon, 8 Jul 2024 11:46:44 +0200
Subject: [PATCH 10/34] Added feedback widget, simplified slide cells, removed
 figsize kwargs in plotting cells to improve rendering in book.

---
 .../W1D3_Tutorial7.ipynb                      | 101 ++++++++++++------
 .../W1D3_Tutorial8.ipynb                      |  96 +++++++++++------
 2 files changed, 132 insertions(+), 65 deletions(-)

diff --git a/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/W1D3_Tutorial7.ipynb b/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/W1D3_Tutorial7.ipynb
index 1bb920d39..61a415eb2 100644
--- a/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/W1D3_Tutorial7.ipynb
+++ b/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/W1D3_Tutorial7.ipynb
@@ -61,7 +61,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "tags": [
      "colab"
     ]
@@ -89,7 +88,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -104,12 +102,37 @@
     "from scipy import stats"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D3_T7\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
     "cellView": "form",
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -127,8 +150,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "form",
-    "execution": {}
+    "cellView": "form"
    },
    "outputs": [],
    "source": [
@@ -158,7 +180,6 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -221,12 +242,21 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Impact_of_Climate_Variability_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
     "cellView": "form",
-    "execution": {},
     "pycharm": {
      "name": "#%%\n"
     },
@@ -242,14 +272,18 @@
     "\n",
     "link_id = \"tyjwu\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Impact_of_Climate_Variability_Slides\")"
    ]
   },
   {
@@ -287,7 +321,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -304,7 +337,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -337,7 +369,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -353,7 +384,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -396,7 +426,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -461,7 +490,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -479,7 +507,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -495,7 +522,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -530,7 +556,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -589,7 +614,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -607,7 +631,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -656,7 +679,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -688,7 +710,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -701,6 +722,16 @@
     "\"\"\""
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_2\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -716,7 +747,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -784,7 +814,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -855,6 +884,16 @@
     "ax.set_ylabel(\"Precipitation Anomaly\\n(mm/day)\")"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Coding_Exercise_2\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -916,7 +955,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.19"
+   "version": "3.9.18"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/W1D3_Tutorial8.ipynb b/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/W1D3_Tutorial8.ipynb
index 9952f1a57..f3c644611 100644
--- a/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/W1D3_Tutorial8.ipynb
+++ b/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/W1D3_Tutorial8.ipynb
@@ -63,7 +63,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "tags": [
      "colab"
     ]
@@ -93,7 +92,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 128816,
      "status": "ok",
@@ -122,12 +120,37 @@
     "from scipy import stats"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D3_T8\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
     "cellView": "form",
-    "execution": {},
     "executionInfo": {
      "elapsed": 325,
      "status": "ok",
@@ -155,8 +178,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "form",
-    "execution": {}
+    "cellView": "form"
    },
    "outputs": [],
    "source": [
@@ -184,7 +206,6 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -237,12 +258,21 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Verification_Satellite_Data_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
     "cellView": "form",
-    "execution": {},
     "pycharm": {
      "name": "#%%\n"
     },
@@ -258,14 +288,18 @@
     "\n",
     "link_id = \"w3r49\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Verification_Satellite_Data_Slides\")"
    ]
   },
   {
@@ -303,7 +337,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 4091,
      "status": "ok",
@@ -348,7 +381,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 16,
      "status": "ok",
@@ -380,7 +412,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 461,
      "status": "ok",
@@ -413,7 +444,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 64910,
      "status": "ok",
@@ -437,7 +467,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 4538,
      "status": "ok",
@@ -479,7 +508,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 186915,
      "status": "ok",
@@ -515,7 +543,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 18,
      "status": "ok",
@@ -550,7 +577,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 10612,
      "status": "ok",
@@ -632,7 +658,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 19,
      "status": "ok",
@@ -657,7 +682,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 7721,
      "status": "ok",
@@ -693,7 +717,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 1508,
      "status": "ok",
@@ -743,7 +766,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 5,
      "status": "ok",
@@ -767,7 +789,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 20565,
      "status": "ok",
@@ -812,7 +833,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -836,7 +856,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -860,7 +879,7 @@
     "ax.legend()\n",
     "\n",
     "# plot the scatter plot between nClimGrid and GPCP monthly precipitation CDR\n",
-    "fig, ax = plt.subplots(figsize=(12, 6))\n",
+    "fig, ax = plt.subplots()\n",
     "fig.suptitle(\"GPCP Precipitaion v.s. nClimGrid\")\n",
     "# ax.scatter(sat_clim_anom, obs_clim_anom, alpha=0.6)\n",
     "# Add 1:1 line\n",
@@ -881,7 +900,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -915,7 +933,7 @@
     "ax.legend()\n",
     "\n",
     "# plot the scatter plot between nClimGrid and GPCP monthly precipitation CDR\n",
-    "fig, ax = plt.subplots(figsize=(12, 6))\n",
+    "fig, ax = plt.subplots()\n",
     "fig.suptitle(\"GPCP Precipitaion v.s. nClimGrid\")\n",
     "ax.scatter(sat_clim_anom, obs_clim_anom, alpha=0.6)\n",
     "# Add 1:1 line\n",
@@ -932,6 +950,16 @@
     "print(\"Corr Coef: \" + str(r) + \", p-val: \" + str(p))"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Coding_Exercise_1_5\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -996,7 +1024,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.19"
+   "version": "3.9.18"
   }
  },
  "nbformat": 4,

From 69e9c37c81d1688f221a4e306a359008a26f6635 Mon Sep 17 00:00:00 2001
From: Paul Heubel <paul_heubel@web.de>
Date: Mon, 8 Jul 2024 22:24:15 +0200
Subject: [PATCH 11/34] Added feedback widget, slide cell simplification, colab
 installation update after testing.

---
 .../W1D4_Paleoclimate/W1D4_Tutorial1.ipynb    | 96 +++++++++++++------
 1 file changed, 65 insertions(+), 31 deletions(-)

diff --git a/tutorials/W1D4_Paleoclimate/W1D4_Tutorial1.ipynb b/tutorials/W1D4_Paleoclimate/W1D4_Tutorial1.ipynb
index fba6c60db..8bae1dce3 100644
--- a/tutorials/W1D4_Paleoclimate/W1D4_Tutorial1.ipynb
+++ b/tutorials/W1D4_Paleoclimate/W1D4_Tutorial1.ipynb
@@ -60,14 +60,11 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# installations ( uncomment and run this cell ONLY when using google colab or kaggle )\n",
     "\n",
-    "# !pip install --no-binary shapely shapely --force # Add this to use cartopy. in this way it doesn't crush\n",
     "# !pip install cartopy\n",
     "# !pip install LiPD"
    ]
@@ -75,9 +72,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# imports\n",
@@ -94,12 +89,37 @@
     "import cartopy.feature as cfeature"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D4_T1\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "form",
-    "execution": {}
+    "cellView": "form"
    },
    "outputs": [],
    "source": [
@@ -116,8 +136,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "form",
-    "execution": {}
+    "cellView": "form"
    },
    "outputs": [],
    "source": [
@@ -236,7 +255,6 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -298,12 +316,21 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_What_is_Paleoclimate_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
     "cellView": "form",
-    "execution": {},
     "pycharm": {
      "name": "#%%\n"
     },
@@ -319,14 +346,18 @@
     "\n",
     "link_id = \"ae894\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_What_is_Paleoclimate_Slides\")"
    ]
   },
   {
@@ -377,9 +408,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# Set the name to save the PAGES2K data\n",
@@ -410,7 +439,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 139313,
      "status": "ok",
@@ -446,7 +474,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 628,
      "status": "ok",
@@ -488,7 +515,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 5407,
      "status": "ok",
@@ -597,9 +623,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# to_remove explanation\n",
@@ -610,6 +634,16 @@
     "\"\"\""
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_3\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -672,7 +706,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.19"
+   "version": "3.9.18"
   }
  },
  "nbformat": 4,

From 21c6baa32a51e770cf3fa01c00987c478779cf9f Mon Sep 17 00:00:00 2001
From: Paul Heubel <paul_heubel@web.de>
Date: Mon, 8 Jul 2024 22:26:06 +0200
Subject: [PATCH 12/34] Added feedback widget, slide cell simplification, ";"
 deletion to avoid slow processing, fixed section header.

---
 .../W1D4_Paleoclimate/W1D4_Tutorial2.ipynb    | 127 ++++++++++--------
 1 file changed, 74 insertions(+), 53 deletions(-)

diff --git a/tutorials/W1D4_Paleoclimate/W1D4_Tutorial2.ipynb b/tutorials/W1D4_Paleoclimate/W1D4_Tutorial2.ipynb
index 0cc0117f3..75b7de88e 100644
--- a/tutorials/W1D4_Paleoclimate/W1D4_Tutorial2.ipynb
+++ b/tutorials/W1D4_Paleoclimate/W1D4_Tutorial2.ipynb
@@ -84,9 +84,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# installations ( uncomment and run this cell ONLY when using google colab or kaggle )\n",
@@ -98,9 +96,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# imports\n",
@@ -116,12 +112,37 @@
     "from matplotlib import patches"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D4_T2\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "form",
-    "execution": {}
+    "cellView": "form"
    },
    "outputs": [],
    "source": [
@@ -138,8 +159,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "form",
-    "execution": {}
+    "cellView": "form"
    },
    "outputs": [],
    "source": [
@@ -167,7 +187,6 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -220,12 +239,21 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Ocean_Climate_Proxies_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
     "cellView": "form",
-    "execution": {},
     "pycharm": {
      "name": "#%%\n"
     },
@@ -241,14 +269,18 @@
     "\n",
     "link_id = \"qtkbv\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Ocean_Climate_Proxies_Slides\")"
    ]
   },
   {
@@ -280,9 +312,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# select data for the month of interest\n",
@@ -393,7 +423,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 1031,
      "status": "ok",
@@ -446,9 +475,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "ts_palmyra = pyleo.Series(\n",
@@ -474,9 +501,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "palmyra_stnd = ts_palmyra.standardize()\n",
@@ -497,9 +522,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# Download the data using the url\n",
@@ -527,9 +550,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "ts_line = pyleo.Series(\n",
@@ -546,9 +567,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "line_stnd = ts_line.standardize()\n",
@@ -569,9 +588,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# combine into a list\n",
@@ -581,9 +598,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# create multiseries\n",
@@ -594,7 +609,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 942,
      "status": "ok",
@@ -633,9 +647,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# to_remove explanation\n",
@@ -643,7 +655,17 @@
     "\"\"\"\n",
     "1. In general when there is a recorded ENSO event in the ONI, there is an agreement with the coral records.  During El Niño Phases captured by the ONI (where SSTs are anomalously warm), we typically see a more negative d18O and vice versa for La Niña events.\n",
     "2. ENSO is an interannual occurrence, happening every 2-7 years. Within the d18O records, there are high-frequency signals. One thing (among many) we could do is remove these by filtering. This would help resolve our dataset into something more comparable to what the ONI is tracking.\n",
-    "\"\"\";"
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_2\")"
    ]
   },
   {
@@ -652,7 +674,7 @@
     "execution": {}
    },
    "source": [
-    "# Section 1.3: Make Warming Stripes Plot"
+    "# Section 3: Make Warming Stripes Plot"
    ]
   },
   {
@@ -668,7 +690,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 409,
      "status": "ok",
@@ -756,7 +777,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.19"
+   "version": "3.9.18"
   }
  },
  "nbformat": 4,

From ac8333ce1327df11f2a99187c03e22ff78e9dae6 Mon Sep 17 00:00:00 2001
From: Paul Heubel <paul_heubel@web.de>
Date: Mon, 8 Jul 2024 22:29:41 +0200
Subject: [PATCH 13/34] Added feedback widget, slide cell simplification, ";"
 deletion to avoid slow processing. Colab installation cell update after
 testing,

---
 .../W1D4_Paleoclimate/W1D4_Tutorial3.ipynb    | 140 +++++++++------
 .../W1D4_Paleoclimate/W1D4_Tutorial4.ipynb    | 106 +++++++----
 .../W1D4_Paleoclimate/W1D4_Tutorial5.ipynb    | 164 ++++++++++--------
 3 files changed, 240 insertions(+), 170 deletions(-)

diff --git a/tutorials/W1D4_Paleoclimate/W1D4_Tutorial3.ipynb b/tutorials/W1D4_Paleoclimate/W1D4_Tutorial3.ipynb
index 92c8338dc..63de7db98 100644
--- a/tutorials/W1D4_Paleoclimate/W1D4_Tutorial3.ipynb
+++ b/tutorials/W1D4_Paleoclimate/W1D4_Tutorial3.ipynb
@@ -60,24 +60,20 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# installations ( uncomment and run this cell ONLY when using google colab or kaggle )\n",
     "\n",
     "# !pip install LiPD\n",
     "# !pip install cartopy\n",
-    "# !pip install pyleoclim"
+    "# !pip install pyleoclim==0.14.0"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# imports\n",
@@ -94,12 +90,37 @@
     "import sys"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D4_T3\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "form",
-    "execution": {}
+    "cellView": "form"
    },
    "outputs": [],
    "source": [
@@ -116,8 +137,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "form",
-    "execution": {}
+    "cellView": "form"
    },
    "outputs": [],
    "source": [
@@ -159,7 +179,6 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -221,12 +240,21 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Terrestrial_Climate_Proxies_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
     "cellView": "form",
-    "execution": {},
     "pycharm": {
      "name": "#%%\n"
     },
@@ -242,14 +270,18 @@
     "\n",
     "link_id = \"6gcsh\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Terrestrial_Climate_Proxies_Slides\")"
    ]
   },
   {
@@ -266,9 +298,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# set the name to save the Euro2k data\n",
@@ -287,9 +317,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# the LiPD object can be used to load datasets stored in the LiPD format.\n",
@@ -319,9 +347,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "def filter_data(dataset, archive_type, variable_name):\n",
@@ -366,9 +392,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "ts_list = d_euro.to_tso()"
@@ -386,9 +410,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# look at available entries for just one time-series\n",
@@ -398,9 +420,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# print relevant information for all entries\n",
@@ -422,7 +442,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 163,
      "status": "ok",
@@ -454,7 +473,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 187,
      "status": "ok",
@@ -485,7 +503,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 200,
      "status": "ok",
@@ -517,9 +534,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# initiate plot\n",
@@ -591,9 +606,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# to_remove solution\n",
@@ -659,6 +672,16 @@
     ")"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Coding_Exercises_2\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -671,9 +694,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# standardize the data\n",
@@ -697,7 +718,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 4905,
      "status": "ok",
@@ -768,9 +788,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# to_remove explanation\n",
@@ -783,6 +801,16 @@
     "\"\"\""
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_2\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -843,7 +871,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.19"
+   "version": "3.9.18"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/W1D4_Paleoclimate/W1D4_Tutorial4.ipynb b/tutorials/W1D4_Paleoclimate/W1D4_Tutorial4.ipynb
index 713f2e976..8280b8098 100644
--- a/tutorials/W1D4_Paleoclimate/W1D4_Tutorial4.ipynb
+++ b/tutorials/W1D4_Paleoclimate/W1D4_Tutorial4.ipynb
@@ -59,23 +59,18 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# installations ( uncomment and run this cell ONLY when using google colab or kaggle )\n",
     "\n",
-    "# !pip install pyleoclim\n",
-    "# !pip install cartopy"
+    "# !pip install pyleoclim"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# imports\n",
@@ -87,12 +82,37 @@
     "import pyleoclim as pyleo"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D4_T4\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "form",
-    "execution": {}
+    "cellView": "form"
    },
    "outputs": [],
    "source": [
@@ -109,8 +129,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "form",
-    "execution": {}
+    "cellView": "form"
    },
    "outputs": [],
    "source": [
@@ -138,7 +157,6 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -191,12 +209,21 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Atmospheric_Climate_Proxies_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
     "cellView": "form",
-    "execution": {},
     "pycharm": {
      "name": "#%%\n"
     },
@@ -212,14 +239,18 @@
     "\n",
     "link_id = \"szyhp\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Atmospheric_Climate_Proxies_Slides\")"
    ]
   },
   {
@@ -244,7 +275,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 853,
      "status": "ok",
@@ -283,9 +313,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "ts_co2 = pyleo.Series(\n",
@@ -312,7 +340,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 800,
      "status": "ok",
@@ -364,7 +391,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 1120,
      "status": "ok",
@@ -395,9 +421,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "dDts = pyleo.Series(\n",
@@ -415,7 +439,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 588,
      "status": "ok",
@@ -445,7 +468,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 690,
      "status": "ok",
@@ -492,9 +514,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# to_remove explanation\n",
@@ -505,7 +525,17 @@
     "3. The cooling periods tend to be more gradual while warming periods are relatively rapid. This pattern is especially apparent over the past 400,000 years.\n",
     "4. These glacial-interglacial cycles are primarily driven by variations in Earth’s orbital parameters. These parameters include eccentricity, obliquity, and precession, which vary on timescales of ~100,000 years, ~40,000 years, and ~21,000 years, respectively. In later tutorials, we’ll learn how to identify temporal cyclicity in paleoclimate reconstructions and assess possible forcings with similar timescales of variation.\n",
     "\n",
-    "\"\"\";"
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_2\")"
    ]
   },
   {
@@ -575,7 +605,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.19"
+   "version": "3.9.18"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/W1D4_Paleoclimate/W1D4_Tutorial5.ipynb b/tutorials/W1D4_Paleoclimate/W1D4_Tutorial5.ipynb
index 069c4a751..f38d1c03c 100644
--- a/tutorials/W1D4_Paleoclimate/W1D4_Tutorial5.ipynb
+++ b/tutorials/W1D4_Paleoclimate/W1D4_Tutorial5.ipynb
@@ -60,9 +60,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# installations ( uncomment and run this cell ONLY when using google colab or kaggle )\n",
@@ -73,9 +71,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# imports\n",
@@ -89,12 +85,37 @@
     "from sklearn.decomposition import PCA"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D4_T5\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "form",
-    "execution": {}
+    "cellView": "form"
    },
    "outputs": [],
    "source": [
@@ -111,8 +132,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "form",
-    "execution": {}
+    "cellView": "form"
    },
    "outputs": [],
    "source": [
@@ -140,7 +160,6 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -193,12 +212,21 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Proxy_Data_Analysis_Tools_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
     "cellView": "form",
-    "execution": {},
     "pycharm": {
      "name": "#%%\n"
     },
@@ -214,14 +242,18 @@
     "\n",
     "link_id = \"ujbqz\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Proxy_Data_Analysis_Tools_Slides\")"
    ]
   },
   {
@@ -240,9 +272,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "filename_tang = \"tanganyika_dD.csv\"\n",
@@ -264,7 +294,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 736,
      "status": "ok",
@@ -316,7 +345,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 138,
      "status": "ok",
@@ -355,9 +383,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "tang_linear = ts_tang.interp()  # default method = 'linear'"
@@ -367,7 +393,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 167,
      "status": "ok",
@@ -398,7 +423,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 443,
      "status": "ok",
@@ -431,9 +455,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "ts_tang"
@@ -442,9 +464,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "tang_linear"
@@ -462,9 +482,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "fig, ax = plt.subplots()  # assign a new plot axis\n",
@@ -497,9 +515,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "tang_bin = (\n",
@@ -511,7 +527,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 457,
      "status": "ok",
@@ -554,9 +569,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# bin size of 500\n",
@@ -576,9 +589,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# to_remove solution\n",
@@ -597,6 +608,16 @@
     "_ = tang_bin_1000.plot(ax=ax, label=\"Binned 1000 yrs\")"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Coding_Exercises_2_2\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -628,7 +649,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 484,
      "status": "ok",
@@ -653,7 +673,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 370,
      "status": "ok",
@@ -680,7 +699,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 354,
      "status": "ok",
@@ -713,9 +731,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "ts_tanganyika = pyleo.Series(\n",
@@ -764,9 +780,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "ts_list = [ts_tanganyika, ts_aden, ts_bosumtwi, ts_gc27]\n",
@@ -786,7 +800,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 756,
      "status": "ok",
@@ -818,7 +831,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 1048,
      "status": "ok",
@@ -852,9 +864,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "pca = PCA()\n",
@@ -876,7 +886,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 224,
      "status": "ok",
@@ -907,9 +916,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "africa_pc1 = africa_PCA.transform(africa_ct.to_pandas())"
@@ -918,9 +925,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "africa_mode1 = pyleo.Series(\n",
@@ -937,7 +942,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 1026,
      "status": "ok",
@@ -981,9 +985,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# to_remove explanation\n",
@@ -992,7 +994,17 @@
     "1. The overall trends are similar. However, there is more variability in the original δD records than in the PC1 time series. This makes sense because the principal component analysis identifies a common signal between original δD reconstructions and therefore is inherently less variable.\n",
     "2. The Gulf of Aden δD record is the most similar to the PC1 time series. The Lake Bosumtwi δD record is the least similar to the PC1 time series. This difference is particularly noticeable between 5,000-10,000 years ago.\n",
     "3. The PC1 time series suggests a drier climate (more positive δD) in Africa over the past 20,000 years. Recall that 20,000 years ago was the last glacial period. African rainfall increased ~15,000 years ago during the deglacial transition. There is a short period of drying ~12,000 years ago, which corresponds to the timing of the Younger Dryas (a millennial-scale, Northern Hemisphere high-latitude cooling event). This is followed by an increase in rainfall associated with what is known as the African Humid Period (a period of wet, humid conditions in northern and equatorial Africa, driven by intensification of the African monsoon). Finally, there is a decrease in rainfall over the past ~8,000 years towards the present. Note: δD only records qualitative changes in rainfall (i.e., wetter or drier relative to another time period), and does not provide quantitative measurements of the amount of rainfall.\n",
-    "\"\"\";"
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_3\")"
    ]
   },
   {
@@ -1067,7 +1079,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.19"
+   "version": "3.9.18"
   }
  },
  "nbformat": 4,

From 951d3cc2ac013e469affe6e7a7febdef82fa2936 Mon Sep 17 00:00:00 2001
From: Paul Heubel <paul_heubel@web.de>
Date: Mon, 8 Jul 2024 22:33:12 +0200
Subject: [PATCH 14/34] Added feedback widget, slide cell simplification, ";"
 deletion to avoid slow processing. Headers fixed.

---
 .../W1D4_Paleoclimate/W1D4_Tutorial6.ipynb    | 129 +++++++++++-------
 .../W1D4_Paleoclimate/W1D4_Tutorial7.ipynb    | 126 ++++++++++-------
 .../W1D4_Paleoclimate/W1D4_Tutorial8.ipynb    |  94 +++++++++++--
 .../W1D4_Paleoclimate/W1D4_Tutorial9.ipynb    |  84 ++++++++++--
 4 files changed, 315 insertions(+), 118 deletions(-)

diff --git a/tutorials/W1D4_Paleoclimate/W1D4_Tutorial6.ipynb b/tutorials/W1D4_Paleoclimate/W1D4_Tutorial6.ipynb
index ae29b18c9..8f617556b 100644
--- a/tutorials/W1D4_Paleoclimate/W1D4_Tutorial6.ipynb
+++ b/tutorials/W1D4_Paleoclimate/W1D4_Tutorial6.ipynb
@@ -60,9 +60,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# installations ( uncomment and run this cell ONLY when using google colab or kaggle )\n",
@@ -73,9 +71,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# imports\n",
@@ -88,12 +84,37 @@
     "import pyleoclim as pyleo"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D4_T6\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "form",
-    "execution": {}
+    "cellView": "form"
    },
    "outputs": [],
    "source": [
@@ -110,8 +131,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "form",
-    "execution": {}
+    "cellView": "form"
    },
    "outputs": [],
    "source": [
@@ -139,7 +159,6 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -192,12 +211,21 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Spectral_Analysis_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
     "cellView": "form",
-    "execution": {},
     "pycharm": {
      "name": "#%%\n"
     },
@@ -213,14 +241,18 @@
     "\n",
     "link_id = \"g7rp4\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Spectral_Analysis_Slides\")"
    ]
   },
   {
@@ -247,7 +279,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 388,
      "status": "ok",
@@ -284,9 +315,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "ts_lr04 = pyleo.Series(\n",
@@ -313,7 +342,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 1136,
      "status": "ok",
@@ -348,9 +376,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# to_remove explanation\n",
@@ -359,7 +385,17 @@
     "1. There are cyclical variations in d18O that record glacial and interglacial periods. Higher-than-standard global concentrations of light oxygen in ocean water indicate that global temperatures have warmed (i.e. an interglacial period), whereas higher-than-standard global concentrations of heavy oxygen in ocean water indicate that global temperatures were cooler (i.e. a glacial period).\n",
     "2. It appears as if the amplitudes of the glacial-interglacial cycles increased over the past 1 million years. Specifically, the amplitude changes ~700,000 years ago.\n",
     "3. It's difficult to determine the temporal frequency at which these glacial-interglacial cycles occur by just looking at the time series. We will explore a computational tool to more accurately determine the length of these cycles. By eye, you might note a ~100,000 year cycle however, among others that are harder to discern.\n",
-    "\"\"\";"
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_1\")"
    ]
   },
   {
@@ -400,9 +436,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "fig, ax = plt.subplots()\n",
@@ -448,9 +482,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# Lomb-Scargle periodogram\n",
@@ -481,7 +513,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 81823,
      "status": "ok",
@@ -501,9 +532,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "lr04_ls_sd_sig.plot(xlabel=\"Period [kyrs]\")"
@@ -524,7 +553,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 722,
      "status": "ok",
@@ -574,9 +602,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# create a scalogram\n",
@@ -587,7 +613,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 1623,
      "status": "ok",
@@ -630,9 +655,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# to_remove explanation\n",
@@ -642,6 +665,16 @@
     "\"\"\""
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_2_3\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -705,7 +738,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.19"
+   "version": "3.9.18"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/W1D4_Paleoclimate/W1D4_Tutorial7.ipynb b/tutorials/W1D4_Paleoclimate/W1D4_Tutorial7.ipynb
index b3b864c05..fae6fe3f8 100644
--- a/tutorials/W1D4_Paleoclimate/W1D4_Tutorial7.ipynb
+++ b/tutorials/W1D4_Paleoclimate/W1D4_Tutorial7.ipynb
@@ -60,9 +60,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# installations ( uncomment and run this cell ONLY when using google colab or kaggle )\n",
@@ -79,7 +77,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 7892,
      "status": "ok",
@@ -108,12 +105,37 @@
     "from climlab.solar.insolation import daily_insolation"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D4_T7\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "form",
-    "execution": {}
+    "cellView": "form"
    },
    "outputs": [],
    "source": [
@@ -130,8 +152,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "form",
-    "execution": {}
+    "cellView": "form"
    },
    "outputs": [],
    "source": [
@@ -159,7 +180,6 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -212,12 +232,21 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Interpreting_Climate_Forcings_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
     "cellView": "form",
-    "execution": {},
     "pycharm": {
      "name": "#%%\n"
     },
@@ -233,14 +262,18 @@
     "\n",
     "link_id = \"ztfwk\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Interpreting_Climate_Forcings_Slides\")"
    ]
   },
   {
@@ -276,7 +309,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 927,
      "status": "ok",
@@ -332,9 +364,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# standardize the data\n",
@@ -344,9 +374,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# calculate the WWZ spectral analysis\n",
@@ -357,7 +385,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 1575,
      "status": "ok",
@@ -389,9 +416,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# perform significance test with 5 surrogates\n",
@@ -404,9 +429,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# to_remove solution\n",
@@ -418,6 +441,16 @@
     "_ = d18O_wwz_sig.plot(xlabel=\"Period [kyrs]\")"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Coding_Exercises_1\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -434,9 +467,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# specify time interval and units\n",
@@ -466,7 +497,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 540,
      "status": "ok",
@@ -505,7 +535,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 819,
      "status": "ok",
@@ -542,9 +571,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# calculate the WWZ spectral analysis\n",
@@ -555,7 +582,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 602,
      "status": "ok",
@@ -587,9 +613,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# to_remove explanation\n",
@@ -597,7 +621,17 @@
     "\"\"\"\n",
     "1. The dominant spectral power for the insolation data is ~23,000 years, which is roughly the same signal observed in the spectral analysis of the speleothem d18O record.\n",
     "2. The relationship between solar insolation and monsoon intensity can be explained by the fact that solar insolation affects the temperature gradients between land and sea. During the summer, if there's high solar insolation, the land warms up more than the sea, leading to lower pressure over the land. This low pressure attracts moisture-rich air from the sea, causing the monsoon. Therefore, changes in solar insolation caused by Earth's orbital cycles could influence the intensity of monsoons. Specifically, the 23,000 year signal in these records suggests that precession-driven changes in insolation was the dominant forcing of monsoon intensity.\n",
-    "\"\"\";"
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_2\")"
    ]
   },
   {
@@ -658,7 +692,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.19"
+   "version": "3.9.18"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/W1D4_Paleoclimate/W1D4_Tutorial8.ipynb b/tutorials/W1D4_Paleoclimate/W1D4_Tutorial8.ipynb
index d316d6823..ee5aa441a 100644
--- a/tutorials/W1D4_Paleoclimate/W1D4_Tutorial8.ipynb
+++ b/tutorials/W1D4_Paleoclimate/W1D4_Tutorial8.ipynb
@@ -91,6 +91,32 @@
     "import pyleoclim as pyleo"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D4_T8\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -195,6 +221,16 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Paleoclimate_Models_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -216,14 +252,18 @@
     "\n",
     "link_id = \"7p3zv\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Paleoclimate_Models_Slides\")"
    ]
   },
   {
@@ -319,7 +359,17 @@
     "\"\"\"\n",
     "1. Until about 1850, the overall temperature is relatively constant with a ~1ºC decrease from 600-1000 and a ~1.5ºC warming from 1000-1300. However, from 1850 to the present, temperature has increased by ~2.5ºC.\n",
     "2. This recent increase in temperature is likely due to the impacts of anthropogenic activities.\n",
-    "\"\"\";"
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_1\")"
    ]
   },
   {
@@ -591,7 +641,17 @@
     "1. The reconstructed Global Mean Surface Temperature (GMST) anomalies from the collective time series displays a variation within the range of 1.5 ˚C. The consistency among the reconstructed values tends to increase as we approach the present day, with more substantial variation observed between the years 1200 and 1800. These differences can be attributed to several factors. For instance, each model's unique sensitivity to different forcings and their distinct representations of physical processes or spatial resolutions can lead to variations in outcomes.\n",
     "2. In order to obtain the \"best\" simulation, a comparative analysis is conducted against observational or proxy data. The simulation that best mirrors the observed or reconstructed climate trends and variability over the same time period is often deemed the most reliable. However, it's essential to note that all models possess their own strengths and weaknesses, and the \"best\" model can depend on the specific climate variable or region of interest.\n",
     "\n",
-    "\"\"\";"
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_2\")"
    ]
   },
   {
@@ -682,7 +742,17 @@
     "1. The model temperatures exhibit greater variability compared to the proxy records due to the significantly lower sampling frequency of the proxies.\n",
     "2. Despite the differences in variability and temporal resolution, the overall temperature trends seen in the proxy record and GMST anomaly reconstructions from all PMIP3 simulations are similar. Overall, both the model and the proxy show relatively constant temperatures until ~1850 when temperature rapidly increases due to the influence of anthropogenic forcings, particularly the increase in greenhouse gas concentrations due to human activities.\n",
     "\n",
-    "\"\"\";"
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_3\")"
    ]
   },
   {
@@ -758,7 +828,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.19"
+   "version": "3.9.18"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/W1D4_Paleoclimate/W1D4_Tutorial9.ipynb b/tutorials/W1D4_Paleoclimate/W1D4_Tutorial9.ipynb
index c1906c530..2e1e195c4 100644
--- a/tutorials/W1D4_Paleoclimate/W1D4_Tutorial9.ipynb
+++ b/tutorials/W1D4_Paleoclimate/W1D4_Tutorial9.ipynb
@@ -92,6 +92,32 @@
     "import cartopy.crs as ccrs"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D4_T9\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -196,6 +222,16 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Paleoclimate_Data_Assimilation_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -217,14 +253,18 @@
     "\n",
     "link_id = \"f2ynq\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Paleoclimate_Data_Assimilation_Slides\")"
    ]
   },
   {
@@ -367,7 +407,17 @@
     "1.In the span of the last 24,000 years, there has been a considerable shift in global temperatures, transitioning from the colder phase of the Last Glacial Maximum to the relatively warmer Holocene epoch we are currently experiencing. This transformation was not linear, with periods of rapid warming interspersed with intervals of relative stability or even temporary cooling.\n",
     "2.The increase in temperature around 17,000 years ago was likely driven by a combination of climate forcings: obliquity and eccentricity, both affect the amount of solar radiation reaching the Earth's surface.\n",
     "\n",
-    "\"\"\";"
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_1_1\")"
    ]
   },
   {
@@ -492,7 +542,7 @@
     "execution": {}
    },
    "source": [
-    "### Questions 1.1: Climate Connection\n",
+    "### Questions 1.2: Climate Connection\n",
     "\n",
     "Looking at both the map and zonal mean plot, consider the following questions: \n",
     "\n",
@@ -515,7 +565,17 @@
     "\n",
     "2. This pattern is known as polar amplification, which is caused by a number of factors including changes in albedo as ice sheets melt, changes in atmospheric and oceanic circulation, and changes in the distribution of solar insolation.\n",
     "\n",
-    "\"\"\";"
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_1_2\")"
    ]
   },
   {
@@ -578,7 +638,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.19"
+   "version": "3.9.18"
   }
  },
  "nbformat": 4,

From aa6e501ad3f75e2da4353ad7ef29aff545f59a86 Mon Sep 17 00:00:00 2001
From: Paul Heubel <paul_heubel@web.de>
Date: Tue, 9 Jul 2024 00:40:37 +0200
Subject: [PATCH 15/34] Feedback widget, slide cell simplification of Intro
 nbs.

---
 .../W1D3_Intro.ipynb                          | 67 +++++++++++++++----
 tutorials/W1D4_Paleoclimate/W1D4_Intro.ipynb  | 67 +++++++++++++++----
 .../W1D5_ClimateModeling/W1D5_Intro.ipynb     | 67 +++++++++++++++----
 3 files changed, 162 insertions(+), 39 deletions(-)

diff --git a/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/W1D3_Intro.ipynb b/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/W1D3_Intro.ipynb
index c4c52700f..50cc828bb 100644
--- a/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/W1D3_Intro.ipynb
+++ b/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/W1D3_Intro.ipynb
@@ -55,6 +55,33 @@
     "2. Access and analyze satellite remote sensing products for climate applications."
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "0f182426-9adb-4879-9d1d-99fa9cc66d6e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D3_Intro\""
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "52191a48",
@@ -70,8 +97,7 @@
    "execution_count": null,
    "id": "d745bf9b",
    "metadata": {
-    "cellView": "form",
-    "execution": {}
+    "cellView": "form"
    },
    "outputs": [],
    "source": [
@@ -132,6 +158,17 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "8721bc44-ac4c-45c4-b377-8243def60b82",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Introduction_to_Remote_Sensing_Video\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "765617f2",
@@ -147,8 +184,7 @@
    "execution_count": null,
    "id": "6158f5c7",
    "metadata": {
-    "cellView": "form",
-    "execution": {}
+    "cellView": "form"
    },
    "outputs": [],
    "source": [
@@ -158,14 +194,19 @@
     "\n",
     "link_id = \"py527\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "cf8ee68d-b35e-46d9-8e77-aa275a193ced",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Introduction_to_Remote_Sensing_Slides\")"
    ]
   }
  ],
@@ -196,7 +237,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.19"
+   "version": "3.9.18"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/W1D4_Paleoclimate/W1D4_Intro.ipynb b/tutorials/W1D4_Paleoclimate/W1D4_Intro.ipynb
index 92da4ca46..7cce61a03 100644
--- a/tutorials/W1D4_Paleoclimate/W1D4_Intro.ipynb
+++ b/tutorials/W1D4_Paleoclimate/W1D4_Intro.ipynb
@@ -58,6 +58,33 @@
     "3. Explain the benefits and limitations of reanalysis products for paleoclimate analysis."
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "eb2c1de5-858c-41e5-81b9-4909854dbd27",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D4_Intro\""
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "6695fea7",
@@ -73,8 +100,7 @@
    "execution_count": null,
    "id": "8cc5bcaf",
    "metadata": {
-    "cellView": "form",
-    "execution": {}
+    "cellView": "form"
    },
    "outputs": [],
    "source": [
@@ -126,6 +152,17 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "5794e217-8ac9-4391-becc-685aeaa33ba4",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Past_Climates_Inform_Our_Future_Video\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "a17e786a",
@@ -141,8 +178,7 @@
    "execution_count": null,
    "id": "9e57e0a2",
    "metadata": {
-    "cellView": "form",
-    "execution": {}
+    "cellView": "form"
    },
    "outputs": [],
    "source": [
@@ -152,14 +188,19 @@
     "\n",
     "link_id = \"2pvrs\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "2562974f-c9a0-4d70-91b6-87f22e0d2276",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Past_Climates_Inform_Our_Future_Slides\")"
    ]
   }
  ],
@@ -190,7 +231,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.19"
+   "version": "3.9.18"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/W1D5_ClimateModeling/W1D5_Intro.ipynb b/tutorials/W1D5_ClimateModeling/W1D5_Intro.ipynb
index 32d47a810..61496bc6e 100644
--- a/tutorials/W1D5_ClimateModeling/W1D5_Intro.ipynb
+++ b/tutorials/W1D5_ClimateModeling/W1D5_Intro.ipynb
@@ -56,6 +56,33 @@
     "* Access CMIP6 Earth system model data from cloud catalogs, and manipulate it by regridding and calculating global average properties."
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "2c799e08-2a4d-407e-bbc6-ce745e770fec",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D5_Intro\""
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "491d4b6d",
@@ -71,8 +98,7 @@
    "execution_count": null,
    "id": "a8dd85d1",
    "metadata": {
-    "cellView": "form",
-    "execution": {}
+    "cellView": "form"
    },
    "outputs": [],
    "source": [
@@ -124,6 +150,17 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "c7420af4-ba59-43b7-a946-8eeb4e5bff71",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Climate_Modeling_Video\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "f46af996",
@@ -139,8 +176,7 @@
    "execution_count": null,
    "id": "bd95be61",
    "metadata": {
-    "cellView": "form",
-    "execution": {}
+    "cellView": "form"
    },
    "outputs": [],
    "source": [
@@ -150,14 +186,19 @@
     "\n",
     "link_id = \"y2bdn\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "8341016f-e8ab-4a65-9ff8-c619041f3da3",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Climate_Modeling_Slides\")"
    ]
   }
  ],
@@ -188,7 +229,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.19"
+   "version": "3.9.18"
   }
  },
  "nbformat": 4,

From a373a771c711ecbd3a79821b04d039d11099f6cb Mon Sep 17 00:00:00 2001
From: Paul Heubel <paul_heubel@web.de>
Date: Tue, 9 Jul 2024 00:46:03 +0200
Subject: [PATCH 16/34] Added feedback widget, simplified slides cell, deletion
 of ;s to improve processing. Header fixed.

---
 .../W1D5_ClimateModeling/W1D5_Tutorial1.ipynb | 169 +++++++++++++-----
 .../W1D5_ClimateModeling/W1D5_Tutorial2.ipynb | 134 ++++++++++----
 2 files changed, 222 insertions(+), 81 deletions(-)

diff --git a/tutorials/W1D5_ClimateModeling/W1D5_Tutorial1.ipynb b/tutorials/W1D5_ClimateModeling/W1D5_Tutorial1.ipynb
index 67a02ece1..67fd912a3 100644
--- a/tutorials/W1D5_ClimateModeling/W1D5_Tutorial1.ipynb
+++ b/tutorials/W1D5_ClimateModeling/W1D5_Tutorial1.ipynb
@@ -61,9 +61,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# imports\n",
@@ -71,12 +69,37 @@
     "import numpy as np"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D5_T1\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "form",
-    "execution": {}
+    "cellView": "form"
    },
    "outputs": [],
    "source": [
@@ -94,7 +117,6 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -152,7 +174,6 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -205,12 +226,21 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_A_Simple_Greenhouse_Model_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "form",
-    "execution": {}
+    "cellView": "form"
    },
    "outputs": [],
    "source": [
@@ -220,14 +250,18 @@
     "\n",
     "link_id = \"3c8nq\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_A_Simple_Greenhouse_Model_Slides\")"
    ]
   },
   {
@@ -287,8 +321,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "form",
-    "execution": {}
+    "cellView": "form"
    },
    "outputs": [],
    "source": [
@@ -382,16 +415,24 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# to_remove explanation\n",
     "\n",
     "\"\"\"\n",
     "1. Infrared.\n",
-    "\"\"\";"
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_1_1\")"
    ]
   },
   {
@@ -430,7 +471,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 33,
      "status": "ok",
@@ -480,9 +520,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# to_remove explanation\n",
@@ -491,7 +529,17 @@
     "1. The calculated emission temperature of approximately 255 K or -18.2 C is significantly lower than the actual global mean surface temperature of approximately 288 K or 15 C.\n",
     "2. We would expect the corresponding outgoing longwave radiation to be higher than the observed 239 W/m², according to the Stefan-Boltzmann law.\n",
     "3. As the video explains, this simple model doesn't account for the atmospheric greenhouse effect due to greenhouse gases that absorb radiation at these wavelengths.\n",
-    "\"\"\";"
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_1_2\")"
    ]
   },
   {
@@ -516,7 +564,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 31,
      "status": "ok",
@@ -547,7 +594,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 27,
      "status": "ok",
@@ -576,6 +622,16 @@
     "print(\"OLR: \", OLR, \"W m^2\")"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Coding_Exercises_1_2\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -650,7 +706,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 22,
      "status": "ok",
@@ -703,9 +758,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# to_remove explanation\n",
@@ -716,7 +769,17 @@
     "2. It implies that Earth's atmosphere is transparent to the sun's radiation. This is not exactly true, for example ozone interacts with ultraviolet light from the sun.\n",
     "   However, Earth's atmosphere does absorb largely in the infrared.\n",
     "3. Clouds, aerosols, and scattering just to name a few.\n",
-    "\"\"\";"
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_2_2\")"
    ]
   },
   {
@@ -741,7 +804,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 401,
      "status": "ok",
@@ -780,7 +842,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 5,
      "status": "ok",
@@ -817,6 +878,16 @@
     "ax.set_ylabel(\"Outgoing Longwave Radiation (W m$^{-2}$)\")"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Coding_Exercises_2_2\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -834,7 +905,9 @@
     "execution": {}
    },
    "source": [
-    "### Instructions\n",
+    "### Coding Exercises 3\n",
+    "\n",
+    "**Instructions**\n",
     "\n",
     "By defining a function for Planck's Law, plot the blackbody radiation curve for the sun, assuming an emission temperature of $5800 \\text{ K}$. Underlay an approximation of the visible range from the electromagnetic spectrum. This exercise should help you understand why we see in color as well as why the sun's radiation headed towards Earth is called incoming shortwave radiation."
    ]
@@ -842,9 +915,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# define the emission temperature of the sun\n",
@@ -911,9 +982,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# to_remove solution\n",
@@ -986,6 +1055,16 @@
     "ax.legend(bbox_to_anchor=(0.5, 0.5))"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Coding_Exercises_3\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -1047,7 +1126,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.19"
+   "version": "3.9.18"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/W1D5_ClimateModeling/W1D5_Tutorial2.ipynb b/tutorials/W1D5_ClimateModeling/W1D5_Tutorial2.ipynb
index 9ace83b92..5df999086 100644
--- a/tutorials/W1D5_ClimateModeling/W1D5_Tutorial2.ipynb
+++ b/tutorials/W1D5_ClimateModeling/W1D5_Tutorial2.ipynb
@@ -65,7 +65,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "tags": [
      "colab"
     ]
@@ -77,12 +76,37 @@
     "import matplotlib.pyplot as plt  # used for plotting"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D5_T2\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "form",
-    "execution": {}
+    "cellView": "form"
    },
    "outputs": [],
    "source": [
@@ -100,7 +124,6 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -153,12 +176,21 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Energy_Balance_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
     "cellView": "form",
-    "execution": {},
     "pycharm": {
      "name": "#%%\n"
     },
@@ -174,14 +206,18 @@
     "\n",
     "link_id = \"ce6mx\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Energy_Balance_Slides\")"
    ]
   },
   {
@@ -248,7 +284,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 17,
      "status": "ok",
@@ -297,9 +332,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# to_remove explanation\n",
@@ -307,7 +340,17 @@
     "\"\"\"\n",
     "1. If the insolation does not vary, a low albedo implies that Earth is less reflective (e.g less cloud, snow or ice cover) and vice versa for high albedo.\n",
     "2. Both. The reflected radiation is a function of land surface changes (e.g. glaciations and vegetation changes) and clouds (water vapor changes).  The radiation from the sun has also varied over time, which you will go into more detail in tutorial 4.\n",
-    "\"\"\";"
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_1_1\")"
    ]
   },
   {
@@ -337,9 +380,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# plug into equation\n",
@@ -364,9 +405,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# to_remove explanation\n",
@@ -374,7 +413,17 @@
     "\"\"\"\n",
     "1. It is slightly more. This means that Earth is absorbing more energy than it is losing. This is just to get you thinking about energy balance that will be discussed in the remainder of the tutorial.\n",
     "2. It does not take these into account. For example, ozone is a notable greenhouse gas that absorbs in the UV range.\n",
-    "\"\"\";"
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_1_2\")"
    ]
   },
   {
@@ -428,7 +477,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 236,
      "status": "ok",
@@ -488,7 +536,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 4,
      "status": "ok",
@@ -534,9 +581,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# to_remove explanation\n",
@@ -544,7 +589,17 @@
     "\"\"\"\n",
     "1. A decrease. A lower transmissivity means the atmosphere is less transparent, and therefore less radiation escapes to space.\n",
     "2. It is much higher because the greenhouse effect is stronger and trapping more heat.\n",
-    "\"\"\";"
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_3_1\")"
    ]
   },
   {
@@ -568,9 +623,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# define the observed insolation based on observations from the IPCC AR6 Figure 7.2\n",
@@ -608,7 +661,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 5,
      "status": "ok",
@@ -655,6 +707,16 @@
     "ax.set_ylabel(\"Equilibrium Temperature\")"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Coding_Exercises_3_1\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -717,7 +779,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.19"
+   "version": "3.9.18"
   }
  },
  "nbformat": 4,

From 17a680ebd6a2fadb74ac00842cb38bccbe3d2ccd Mon Sep 17 00:00:00 2001
From: Paul Heubel <paul_heubel@web.de>
Date: Tue, 9 Jul 2024 00:47:52 +0200
Subject: [PATCH 17/34]  Added feedback widget, simplified slides cell,
 deletion of ;s to improve processing. Header fixed.

---
 .../W1D5_ClimateModeling/W1D5_Tutorial3.ipynb | 248 +++++++++++++-----
 1 file changed, 177 insertions(+), 71 deletions(-)

diff --git a/tutorials/W1D5_ClimateModeling/W1D5_Tutorial3.ipynb b/tutorials/W1D5_ClimateModeling/W1D5_Tutorial3.ipynb
index c138d48ba..3cc348d09 100644
--- a/tutorials/W1D5_ClimateModeling/W1D5_Tutorial3.ipynb
+++ b/tutorials/W1D5_ClimateModeling/W1D5_Tutorial3.ipynb
@@ -65,7 +65,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "tags": [
      "colab"
     ]
@@ -77,12 +76,37 @@
     "import matplotlib.pyplot as plt  # used for plotting"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D5_T3\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "form",
-    "execution": {}
+    "cellView": "form"
    },
    "outputs": [],
    "source": [
@@ -100,7 +124,6 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -162,12 +185,21 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_A_Zero_Dimensional_Energy_Balance_Model_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
     "cellView": "form",
-    "execution": {},
     "pycharm": {
      "name": "#%%\n"
     },
@@ -183,14 +215,18 @@
     "\n",
     "link_id = \"5mgns\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_A_Zero_Dimensional_Energy_Balance_Model_Slides\")"
    ]
   },
   {
@@ -267,9 +303,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# heat capacity of the ocean\n",
@@ -315,7 +349,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 308,
      "status": "ok",
@@ -347,7 +380,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 310,
      "status": "ok",
@@ -377,6 +409,16 @@
     "d_oc"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Coding_Exercises_1_1\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -398,9 +440,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# to_remove explanation\n",
@@ -411,6 +451,16 @@
     "\"\"\""
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_1_1\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -448,9 +498,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# define the time interval, currently one year expressed in seconds\n",
@@ -500,7 +548,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 6,
      "status": "ok",
@@ -542,7 +589,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 177,
      "status": "ok",
@@ -564,7 +610,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 921,
      "status": "ok",
@@ -606,9 +651,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# to_remove explanation\n",
@@ -618,6 +661,16 @@
     "\"\"\""
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_1_2\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -640,7 +693,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 165,
      "status": "error",
@@ -664,7 +716,7 @@
     "numtsteps = np.array([10, 5, 1]) * 3\n",
     "\n",
     "# for converting the number of seconds in a year\n",
-    "sec_2_yr = ...\n",
+    "sec_2_yr = 3.154e7\n",
     "\n",
     "fig, ax = plt.subplots()\n",
     "# loop through each choice of time step\n",
@@ -694,7 +746,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 1096,
      "status": "ok",
@@ -746,6 +797,16 @@
     "ax.legend()"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Coding_Exercises_1_2\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -777,7 +838,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 942,
      "status": "ok",
@@ -839,9 +899,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# to_remove explanation\n",
@@ -851,6 +909,16 @@
     "\"\"\""
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_2_1\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -876,9 +944,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# define your functions and constants\n",
@@ -945,9 +1011,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# to_remove solution\n",
@@ -1010,6 +1074,16 @@
     "    return T_new, Ftoa"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Bonus_Coding_Exercises_3_1\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -1022,9 +1096,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# run the model to equilibrium without forcing and begining with T(0) = 288K\n",
@@ -1053,9 +1125,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# to_remove solution\n",
@@ -1083,6 +1153,16 @@
     "print(Ftoa)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Bonus_Coding_Exercises_3_2\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -1095,9 +1175,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# define the number of timesteps (years) to run the model\n",
@@ -1124,9 +1202,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# to_remove solution\n",
@@ -1156,6 +1232,16 @@
     "print(Ftoa_forced)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Bonus_Coding_Exercises_3_3\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -1168,9 +1254,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# plot the time series\n",
@@ -1184,9 +1268,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# to_remove solution\n",
@@ -1199,6 +1281,16 @@
     "ax.set_ylabel(\"Global mean temperature (K)\")"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Bonus_Coding_Exercises_3_4\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -1211,9 +1303,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# calculate equilibrium climate sensitivity\n",
@@ -1224,9 +1314,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# to_remove solution\n",
@@ -1236,6 +1324,16 @@
     "print(\"Equilibrium Climate Sensitivity: \", ecs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Bonus_Coding_Exercises_3_5\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -1259,9 +1357,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# to_remove explanation\n",
@@ -1273,6 +1369,16 @@
     "\"\"\""
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Bonus_Questions_3\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -1336,7 +1442,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.19"
+   "version": "3.9.18"
   }
  },
  "nbformat": 4,

From a83237600c6e295c860d2a5c352ef9894b19870a Mon Sep 17 00:00:00 2001
From: Paul Heubel <paul_heubel@web.de>
Date: Tue, 9 Jul 2024 00:51:38 +0200
Subject: [PATCH 18/34]  Added feedback widget, simplified slides cell,
 deletion of ;s to improve processing. Header and Exercise titles fixed.

---
 .../W1D5_ClimateModeling/W1D5_Tutorial4.ipynb | 118 +++++++++++--
 .../W1D5_ClimateModeling/W1D5_Tutorial5.ipynb | 158 +++++++++++-------
 .../W1D5_ClimateModeling/W1D5_Tutorial6.ipynb |  82 +++++++--
 .../W1D5_ClimateModeling/W1D5_Tutorial7.ipynb | 141 +++++++++++-----
 .../W1D5_ClimateModeling/W1D5_Tutorial8.ipynb |  90 ++++++++--
 5 files changed, 451 insertions(+), 138 deletions(-)

diff --git a/tutorials/W1D5_ClimateModeling/W1D5_Tutorial4.ipynb b/tutorials/W1D5_ClimateModeling/W1D5_Tutorial4.ipynb
index 5e93d2b0b..c51490787 100644
--- a/tutorials/W1D5_ClimateModeling/W1D5_Tutorial4.ipynb
+++ b/tutorials/W1D5_ClimateModeling/W1D5_Tutorial4.ipynb
@@ -88,6 +88,32 @@
     "from scipy.optimize import brentq  # used for numerical root-finding to get the equilibria"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D5_T4\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -174,6 +200,16 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Climate_Feedbacks_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -195,14 +231,18 @@
     "\n",
     "link_id = \"btpwx\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Climate_Feedbacks_Slides\")"
    ]
   },
   {
@@ -351,7 +391,17 @@
     "\"\"\"\n",
     "1. Three times.\n",
     "2. When the graphs intersect, it means that ASR = OLR, and thus ASR-OLR = 0. These three intersections are the three temperatures for which energy balance is satisfied in our model.\n",
-    "\"\"\";"
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_1_1\")"
    ]
   },
   {
@@ -493,7 +543,17 @@
     "1. Two. Near 235K and 305K.\n",
     "2. They are the  first and third temperatures at which the ASR and OLR curves intersect, or energy balance is achieved.\n",
     "3. Near 245K.\n",
-    "\"\"\";"
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_1_2\")"
    ]
   },
   {
@@ -711,7 +771,17 @@
     "\n",
     "\"\"\"\n",
     "1. Two stable equilibria (near 235 K and 305K) and one unstable equilibrium (near 245 K). Yes, they do.\n",
-    "\"\"\";"
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_1_3\")"
    ]
   },
   {
@@ -814,7 +884,17 @@
     "\"\"\"\n",
     "1. One, cold.\n",
     "2. One, warm.\n",
-    "\"\"\";"
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_2_1\")"
    ]
   },
   {
@@ -930,7 +1010,17 @@
     "1. The transition occurs around 240K. This is the lower temperature limit at which the ice-albedo feedback would kick in if the Earth was warmed from below 240K.\n",
     "2. Initially, we have a cold equilibrium solution like the blue and orange lines of the figure in Section 2.1, so the model converges to the cold equilibrium temperature. However, as the insolation increases we reach a point where only a warm equilibrium state exists, like the green line. When this happens, the Earth cannot equilibrate in a cold state anymore so Earth's temperature continues rising until it reaches the warm equilibrium state.\n",
     "3. All the systems on this plot start at 220K, where Earth is in a completely frozen state with an albedo of 0.7. Initially, as the planet warms, the albedo stays at 0.7, however, when the insolation becomes high enough that the planet warms to 240K (i.e. there is no cold equilibrium state) the ice-albedo feedback causes the albedo to begin decreasing, representing the effect of ice & snow melt. This drop in albedo accelerates the warming of the planet over time, as seen in the plot, until Earth reaches its warm equilibrium temperature.\n",
-    "\"\"\";"
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_2_2\")"
    ]
   },
   {
@@ -994,7 +1084,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.19"
+   "version": "3.9.18"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/W1D5_ClimateModeling/W1D5_Tutorial5.ipynb b/tutorials/W1D5_ClimateModeling/W1D5_Tutorial5.ipynb
index 1a02672dd..27fbe6865 100644
--- a/tutorials/W1D5_ClimateModeling/W1D5_Tutorial5.ipynb
+++ b/tutorials/W1D5_ClimateModeling/W1D5_Tutorial5.ipynb
@@ -63,7 +63,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 161558,
      "status": "ok",
@@ -97,7 +96,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 10496,
      "status": "ok",
@@ -126,12 +124,37 @@
     "import tempfile"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D5_T5\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
     "cellView": "form",
-    "execution": {},
     "executionInfo": {
      "elapsed": 418,
      "status": "ok",
@@ -158,8 +181,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "form",
-    "execution": {}
+    "cellView": "form"
    },
    "outputs": [],
    "source": [
@@ -189,7 +211,6 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -252,12 +273,21 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Vertical_Structure_of_the_Atmosphere_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
     "cellView": "form",
-    "execution": {},
     "pycharm": {
      "name": "#%%\n"
     },
@@ -273,14 +303,18 @@
     "\n",
     "link_id = \"dxthu\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Vertical_Structure_of_the_Atmosphere_Slides\")"
    ]
   },
   {
@@ -311,7 +345,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 121302,
      "status": "ok",
@@ -337,9 +370,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# the specific humidity is stored in a variable called Q\n",
@@ -349,9 +380,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "ds.time"
@@ -370,7 +399,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 5500,
      "status": "ok",
@@ -405,7 +433,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 148,
      "status": "ok",
@@ -437,7 +464,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 3619,
      "status": "ok",
@@ -475,7 +501,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 115,
      "status": "ok",
@@ -507,7 +532,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 158,
      "status": "ok",
@@ -537,7 +561,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 125,
      "status": "ok",
@@ -567,7 +590,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 287,
      "status": "ok",
@@ -598,7 +620,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 158,
      "status": "ok",
@@ -645,9 +666,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# to_remove explanation\n",
@@ -657,6 +676,16 @@
     "\"\"\""
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_1\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -678,9 +707,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "fig, ax = plt.subplots()\n",
@@ -709,7 +736,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 2400,
      "status": "ok",
@@ -746,6 +772,16 @@
     "_ = ax.legend()"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Coding_Exercises_1\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -768,7 +804,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 979,
      "status": "ok",
@@ -796,7 +831,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 7,
      "status": "ok",
@@ -831,9 +865,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# to setup the skewT and plot observations\n",
@@ -869,9 +901,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# to add a model derived profile to the skewT figure\n",
@@ -896,7 +926,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 2544,
      "status": "ok",
@@ -945,9 +974,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# take a single step forward to the diagnostics are updated and there is some energy imbalance\n",
@@ -962,7 +989,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 7,
      "status": "ok",
@@ -993,7 +1019,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 2330,
      "status": "ok",
@@ -1034,9 +1059,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# to_remove explanation\n",
@@ -1047,6 +1070,16 @@
     "\"\"\""
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_3\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -1068,9 +1101,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# make an exact clone of our existing model\n",
@@ -1098,7 +1129,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 5291,
      "status": "ok",
@@ -1135,6 +1165,16 @@
     "    add_profile(skew, model)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Coding_Exercises_3\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -1192,7 +1232,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.19"
+   "version": "3.9.18"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/W1D5_ClimateModeling/W1D5_Tutorial6.ipynb b/tutorials/W1D5_ClimateModeling/W1D5_Tutorial6.ipynb
index af1a32f4a..76057793c 100644
--- a/tutorials/W1D5_ClimateModeling/W1D5_Tutorial6.ipynb
+++ b/tutorials/W1D5_ClimateModeling/W1D5_Tutorial6.ipynb
@@ -128,6 +128,32 @@
     "from matplotlib import animation"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D5_T6\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -382,6 +408,16 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Radiative_Convective_Equilibrium_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -403,14 +439,18 @@
     "\n",
     "link_id = \"msarf\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Radiative_Convective_Equilibrium_Slides\")"
    ]
   },
   {
@@ -657,7 +697,17 @@
     "\"\"\"\n",
     "1. In nature, convection changes the temperature of the atmospheric column faster than radiative processes because convection involves the quick movement of air (and heat) from one place to another. Our model takes this into account by having convective processes act instantaneously on instabilities due to unstable temperature profiles.\n",
     "2. Next steps could include expanding in space (x,y,z) and including other processes (such as dynamics) and additional components of the climate system (ocean, etc.). We'll talk about this more in Tutorial 7 where you will work with the Taiwan Earth System Model (TaiESM1).\n",
-    "\"\"\";"
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_2\")"
    ]
   },
   {
@@ -666,7 +716,7 @@
     "execution": {}
    },
    "source": [
-    "## Coding Exercises "
+    "## Coding Exercises 2"
    ]
   },
   {
@@ -742,6 +792,16 @@
     "animation.FuncAnimation(fig, animate, 50, fargs=(rcm, lines))"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Coding_Exercises_2\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -797,7 +857,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.19"
+   "version": "3.9.18"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/W1D5_ClimateModeling/W1D5_Tutorial7.ipynb b/tutorials/W1D5_ClimateModeling/W1D5_Tutorial7.ipynb
index 2db845e43..183f8b2a6 100644
--- a/tutorials/W1D5_ClimateModeling/W1D5_Tutorial7.ipynb
+++ b/tutorials/W1D5_ClimateModeling/W1D5_Tutorial7.ipynb
@@ -60,7 +60,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "tags": [
      "colab"
     ]
@@ -82,7 +81,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 2,
      "status": "ok",
@@ -112,12 +110,37 @@
     "import cartopy.crs as ccrs"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D5_T7\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
     "cellView": "form",
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -137,7 +160,6 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -190,12 +212,21 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Recap_Earth_System_Models_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
     "cellView": "form",
-    "execution": {},
     "pycharm": {
      "name": "#%%\n"
     },
@@ -211,14 +242,18 @@
     "\n",
     "link_id = \"x3kwy\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Recap_Earth_System_Models_Slides\")"
    ]
   },
   {
@@ -283,9 +318,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "col = intake.open_esm_datastore(\n",
@@ -357,7 +390,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 6561,
      "status": "ok",
@@ -407,9 +439,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "cat.keys()"
@@ -434,7 +464,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 1011,
      "status": "ok",
@@ -479,9 +508,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "ssp585 = dt[\"TaiESM1\"][\"ssp585\"].ds\n",
@@ -500,9 +527,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "ssp585.tos"
@@ -532,7 +557,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 11488,
      "status": "ok",
@@ -576,7 +600,7 @@
     "execution": {}
    },
    "source": [
-    "## Coding Exercise 2\n",
+    "## Coding Exercises 2\n",
     "\n",
     "Now that we can plot maps of CMIP6 data, let's look at some projected future changes using this data!\n",
     "\n",
@@ -594,7 +618,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 163,
      "status": "error",
@@ -656,7 +679,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 36973,
      "status": "ok",
@@ -743,6 +765,16 @@
     "ax_diff_jan.set_title(\"2100 vs. 2024 Difference (January)\")"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Coding_Exercises_2\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -763,7 +795,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -774,7 +805,17 @@
     "1. Based on the top maps, it looks like the Equator and low latitudes warm significantly, and the higher latitudes also warm. The northern hemisphere warms more than the southern hemisphere. These changes agree qualitatively with the \"change map\" (bottom left), although the change map makes it clear that the Arctic surface waters are warming faster than the rest of the planet and that the warming is not spatially uniform anywhere (in fact parts of the North Atlantic cool slightly!). The warming in the low latitudes and Southern hemisphere is still significant, and shows interesting spatial patterns.\n",
     "2. There are various things you might notice. For example, the January maps show more warming in the Southern hemisphere than the July maps, consistent with the Southern hemisphere summer creating a warmer baseline and more potential for extreme heat. We also see warming in the Equatorial Pacific region for January, which was not present for July, which could be due to different ENSO phases across the two months and the two years. A final example is that the North Atlantic shows even stronger cooling in January than in July, this is a common signal in many climate models. This cooling can result from melting ice sheets and glaciers creating colder, fresher surface water, which increases stratification. This can reduce the amount of deep convection in the North Atlantic region (by trapping fresh cold water at the surface), weakening the thermohaline circulation.\n",
     "3. The metadata of the CMIP6 dataset we are using in the first two plots contains a long-name for the variable and its units, which are automatically used for the axis labels. When we perform a mathematical operation (subtraction) on the dataset to create a new DataArray, the long-name metadata is not transferred to the new array to avoid confusion in case the operation creates a new variable (that could also have different units). This leads to the plot using the variable name (tos) for the x-axis instead of the long name.\n",
-    "\"\"\";"
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_2\")"
    ]
   },
   {
@@ -807,7 +848,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 1822,
      "status": "ok",
@@ -848,7 +888,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -858,7 +897,17 @@
     "\"\"\"\n",
     "1. For a regular latitude-longitude grid the plot should consist of straight lines from top to bottom, and straight lines from left to right, that are evenly spaced in each of those directions. The grid of TaiESM1 looks like a regular latitude-longitude grid in the Southern Hemisphere, but is quite different in the Northern Hemisphere, with the grid cells getting small (converging) at a \"grid North pole\" which is actually placed at ~75 degrees North and 40 degrees West. a large part of this \"grid North pole\" doesn't contain any grid points (the white hole).\n",
     "2. On a regular latitude-longitude grid, the grid cells rapidly get very small as you approach the pole which causes numerical issues for the ocean model. For example, the time step has to be reduced to physically capture the movement between the smallest cells, leading to many more computations required to evolve the model. This is not a problem for ocean models at the South Pole because the pole is on land! In the Northern hemisphere, it is common to move the \"grid North pole\" of ocean models to occur in a land region (e.g., Asian and/or North American continents), and sometimes there are poles in both these land masses!\n",
-    "\"\"\";"
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_3_1\")"
    ]
   },
   {
@@ -878,7 +927,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 190,
      "status": "ok",
@@ -907,7 +955,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 9588,
      "status": "ok",
@@ -933,7 +980,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 3184,
      "status": "ok",
@@ -960,7 +1006,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 191,
      "status": "ok",
@@ -994,7 +1039,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 21337,
      "status": "ok",
@@ -1059,7 +1103,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -1068,7 +1111,17 @@
     "\n",
     "\"\"\"\n",
     "1. They look similar, which is what we expect from the regridding operation. It should not significantly change the underlying spatial information (i.e., the data), it should just adjust the locations at which that information is provided.\n",
-    "\"\"\";"
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_3_3\")"
    ]
   },
   {
@@ -1137,7 +1190,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.19"
+   "version": "3.9.18"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/W1D5_ClimateModeling/W1D5_Tutorial8.ipynb b/tutorials/W1D5_ClimateModeling/W1D5_Tutorial8.ipynb
index 15f87dc85..b572f03b5 100644
--- a/tutorials/W1D5_ClimateModeling/W1D5_Tutorial8.ipynb
+++ b/tutorials/W1D5_ClimateModeling/W1D5_Tutorial8.ipynb
@@ -114,6 +114,32 @@
     "from xmip.postprocessing import _parse_metric"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D5_T8\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -192,6 +218,16 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Future_Climate_Scenarios_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -213,14 +249,18 @@
     "\n",
     "link_id = \"yg9du\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Future_Climate_Scenarios_Slides\")"
    ]
   },
   {
@@ -409,6 +449,16 @@
     "    dt_with_area[model] = subtree.map_over_subtree(_parse_metric, metric)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Coding_Exercises_1_1\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -533,6 +583,16 @@
     "ax.legend()"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Coding_Exercises_2_1\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -564,7 +624,17 @@
     "\n",
     "\"\"\"\n",
     "1. The plots show warming of the ocean surface under SSP1-2.6, and the even greater warming seen under SSP5-8.5. This is expected from the forcing, the emissions under both scenarios lead to an increase in radiative forcing later in the century (which warms the planet), with the highest radiative forcing and warming under the SSP5-8.5 scenario.\n",
-    "\"\"\";"
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_2_1\")"
    ]
   },
   {
@@ -631,7 +701,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.19"
+   "version": "3.9.18"
   }
  },
  "nbformat": 4,

From 1fa137197c9a73184c102d5492e0c90182b65fa2 Mon Sep 17 00:00:00 2001
From: Paul Heubel <paul_heubel@web.de>
Date: Tue, 9 Jul 2024 00:55:07 +0200
Subject: [PATCH 19/34] Fixed typos.

---
 tutorials/W1D5_ClimateModeling/further_reading.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/tutorials/W1D5_ClimateModeling/further_reading.md b/tutorials/W1D5_ClimateModeling/further_reading.md
index 5da41aeac..3f97f411b 100644
--- a/tutorials/W1D5_ClimateModeling/further_reading.md
+++ b/tutorials/W1D5_ClimateModeling/further_reading.md
@@ -1,3 +1,3 @@
 # Suggested Further Reading
 
-Today’s lectures and tutorials were inspired by The Climate Laboratory, Brian Rose, 2022. If you want further information or context on any of today’s topics, this The Climate Laboratory likely contains that information or links to other appropriate readings.
+Today’s lectures and tutorials were inspired by The Climate Laboratory, Brian Rose, 2022. If you want further information or context on any of today’s topics, The Climate Laboratory likely contains that information or links to other appropriate readings.

From 9f867ccb5a9034175d097cbddc3e8f793956abe4 Mon Sep 17 00:00:00 2001
From: Paul Heubel <paul_heubel@web.de>
Date: Tue, 9 Jul 2024 01:04:10 +0200
Subject: [PATCH 20/34] Sponsor logo update 2024.

---
 tutorials/static/CMA_Logo_Block_2024.png | Bin 0 -> 191640 bytes
 1 file changed, 0 insertions(+), 0 deletions(-)
 create mode 100644 tutorials/static/CMA_Logo_Block_2024.png

diff --git a/tutorials/static/CMA_Logo_Block_2024.png b/tutorials/static/CMA_Logo_Block_2024.png
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HcmV?d00001


From 219368adfb762acce594280d4f344eced0e7d496 Mon Sep 17 00:00:00 2001
From: Paul Heubel <paul_heubel@web.de>
Date: Tue, 9 Jul 2024 01:13:06 +0200
Subject: [PATCH 21/34] new sponsors image link

---
 tutorials/intro.ipynb | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/tutorials/intro.ipynb b/tutorials/intro.ipynb
index 3574d8ead..107e8695a 100644
--- a/tutorials/intro.ipynb
+++ b/tutorials/intro.ipynb
@@ -31,7 +31,7 @@
     "execution": {}
    },
    "source": [
-    "![Sponsors](./static/cma_sponsors_intro_2.png)\n"
+    "![Sponsors](./static/CMA_Logo_Block_2024.png)\n"
    ]
   },
   {
@@ -106,9 +106,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.12"
+   "version": "3.9.18"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 1
+ "nbformat_minor": 4
 }

From e30f8ddea23669a8063da01d2c53b12d471d454f Mon Sep 17 00:00:00 2001
From: Paul Heubel <paul_heubel@web.de>
Date: Tue, 9 Jul 2024 01:29:21 +0200
Subject: [PATCH 22/34] removed dates and added orientation video.

---
 tutorials/intro.ipynb | 81 ++++++++++++++++++++++++++++++++++++++++---
 1 file changed, 76 insertions(+), 5 deletions(-)

diff --git a/tutorials/intro.ipynb b/tutorials/intro.ipynb
index 107e8695a..082249131 100644
--- a/tutorials/intro.ipynb
+++ b/tutorials/intro.ipynb
@@ -56,26 +56,97 @@
     "execution": {}
    },
    "source": [
-    "We have curated an integrated program of tutorials, research projects and professional development activities. The curriculum spans most areas of climate science and will cover cutting-edge methods to analyse climate data and models. This section will overview the curriculum.\n",
+    "We have curated an integrated program of tutorials, research projects, and professional development activities. The curriculum spans most areas of climate science and will cover cutting-edge methods to analyze climate data and models. This section will overview the curriculum.\n",
     "\n",
     "## Prerequisite refreshers\n",
     "\n",
-    "We curated a number of [refresher resources](https://github.com/NeuromatchAcademy/precourse/blob/main/prereqs/ClimateScience.md) for you that will help you prepare for Climatematch Academy. You are not required to study this material before the course. It is rather meant to help you detect and fill any gaps you may have in your knowledge.\n",
-    "The **Introduction to Python** pre-course is an asynchronous course that you can complete on your own time. You will learn how to code in Python from scratch using straightforward examples curated by Project Pythia. If you have questions about the pre-course material, we offer support via Discord chat on July 12-14, 2023\n",
+    "We curated a number of [refresher resources](https://github.com/neuromatch/precourse/blob/main/prereqs/ClimateScience.md) for you that will help you prepare for Climatematch Academy. You are not required to study this material before the course. It is rather meant to help you detect and fill any gaps you may have in your knowledge.\n",
+    "The **Introduction to Python** pre-course is an asynchronous course that you can complete on your own time. You will learn how to code in Python from scratch using straightforward examples curated by Project Pythia. If you have questions about the pre-course material, we offer support via Discord chat.\n",
     "You will also find other open-source resources to catch up on algebra, statistics, calculus, physics, chemistry, and climate science. The topics covered on these days were carefully chosen based on what you need for the course.\n",
     "\n",
     "## The Academy begins!\n",
     "\n",
     "You will start out your two weeks at Climatematch Academy covering the **fundamentals** for understanding climate science data and research. This will include an overview of the climate system and xarray, as well as an introduction to good, equitable research practices.\n",
     "\n",
-    "You will then switch your focus on different types of **climate data**. You will use reanalysis products, remote sensing data, and paleoclimate proxy data to understand multi-scale climate interactions, climate monitoring, and variations in past marine, terrestrial, and atmospheric climates.\n",
+    "You will then switch your focus to different types of **climate data**. You will use reanalysis products, remote sensing data, and paleoclimate proxy data to understand multi-scale climate interactions, climate monitoring, and variations in past marine, terrestrial, and atmospheric climates.\n",
     "\n",
-    "This will be followed by an introduction to the **future of the climate system** as predicted through climate modeling. You will learn about climate models, how to interpret their projections of future climate and the standard framework for assessing socio-economic climate risks. You will also explore pathways to mitigate those risks. During this time, you will also have a full day to work on your research projects, which will give you a chance to incorporate these new insights into your data analyses and interpretation.\n",
+    "This will be followed by an introduction to the **future of the climate system** as predicted through climate modeling. You will learn about climate models, how to interpret their projections of future climate, and the standard framework for assessing socio-economic climate risks. You will also explore pathways to mitigate those risks. During this time, you will also have a full day to work on your research projects, which will give you a chance to incorporate these new insights into your data analyses and interpretation.\n",
     "\n",
     "Finally, the course will cover the **responses to climate change**, including identification of extreme climate events, like heatwaves, droughts, or wildfires, and the use of climate data for tracking the impacts of climate change to inform adaptation measures.\n",
     "\n",
     "You can find more details on the daily schedule and topics taught on different days in the [General Schedule](https://comptools.climatematch.io/tutorials/Schedule/daily_schedules.html).\n"
    ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Video: Student Orientation"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# @markdown\n",
+    "\n",
+    "from ipywidgets import widgets\n",
+    "from IPython.display import YouTubeVideo\n",
+    "from IPython.display import IFrame\n",
+    "from IPython.display import display\n",
+    "\n",
+    "\n",
+    "class PlayVideo(IFrame):\n",
+    "    def __init__(self, id, source, page=1, width=400, height=300, **kwargs):\n",
+    "        self.id = id\n",
+    "        if source == \"Bilibili\":\n",
+    "            src = f\"https://player.bilibili.com/player.html?bvid={id}&page={page}\"\n",
+    "        elif source == \"Osf\":\n",
+    "            src = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/download/{id}/?direct%26mode=render\"\n",
+    "        super(PlayVideo, self).__init__(src, width, height, **kwargs)\n",
+    "\n",
+    "\n",
+    "def display_videos(video_ids, W=400, H=300, fs=1):\n",
+    "    tab_contents = []\n",
+    "    for i, video_id in enumerate(video_ids):\n",
+    "        out = widgets.Output()\n",
+    "        with out:\n",
+    "            if video_ids[i][0] == \"Youtube\":\n",
+    "                video = YouTubeVideo(\n",
+    "                    id=video_ids[i][1], width=W, height=H, fs=fs, rel=0\n",
+    "                )\n",
+    "                print(f\"Video available at https://youtube.com/watch?v={video.id}\")\n",
+    "            else:\n",
+    "                video = PlayVideo(\n",
+    "                    id=video_ids[i][1],\n",
+    "                    source=video_ids[i][0],\n",
+    "                    width=W,\n",
+    "                    height=H,\n",
+    "                    fs=fs,\n",
+    "                    autoplay=False,\n",
+    "                )\n",
+    "                if video_ids[i][0] == \"Bilibili\":\n",
+    "                    print(\n",
+    "                        f\"Video available at https://www.bilibili.com/video/{video.id}\"\n",
+    "                    )\n",
+    "                elif video_ids[i][0] == \"Osf\":\n",
+    "                    print(f\"Video available at https://osf.io/{video.id}\")\n",
+    "            display(video)\n",
+    "        tab_contents.append(out)\n",
+    "    return tab_contents\n",
+    "\n",
+    "\n",
+    "video_ids = [(\"Youtube\", \"FwjyhCLeqx0\"), (\"Bilibili\", \"BV1QE421P7EJ\")\n",
+    "            ]\n",
+    "tab_contents = display_videos(video_ids, W=730, H=410)\n",
+    "tabs = widgets.Tab()\n",
+    "tabs.children = tab_contents\n",
+    "for i in range(len(tab_contents)):\n",
+    "    tabs.set_title(i, video_ids[i][0])\n",
+    "display(tabs)"
+   ]
   }
  ],
  "metadata": {

From 25476e603f9a270c554a980add213fb22b10ca38 Mon Sep 17 00:00:00 2001
From: Paul Heubel <paul_heubel@web.de>
Date: Tue, 9 Jul 2024 01:40:10 +0200
Subject: [PATCH 23/34] Removed ";"s for improved processing performance,
 slides cell simplification.

---
 tutorials/W2D1_AnEnsembleofFutures/W2D1_Intro.ipynb  |  2 +-
 .../W2D1_AnEnsembleofFutures/W2D1_Tutorial1.ipynb    | 12 +++---------
 .../W2D1_AnEnsembleofFutures/W2D1_Tutorial2.ipynb    |  6 +++---
 .../W2D1_AnEnsembleofFutures/W2D1_Tutorial3.ipynb    |  4 ++--
 .../W2D1_AnEnsembleofFutures/W2D1_Tutorial4.ipynb    |  4 ++--
 5 files changed, 11 insertions(+), 17 deletions(-)

diff --git a/tutorials/W2D1_AnEnsembleofFutures/W2D1_Intro.ipynb b/tutorials/W2D1_AnEnsembleofFutures/W2D1_Intro.ipynb
index 9bb811e7c..2825625e5 100644
--- a/tutorials/W2D1_AnEnsembleofFutures/W2D1_Intro.ipynb
+++ b/tutorials/W2D1_AnEnsembleofFutures/W2D1_Intro.ipynb
@@ -240,7 +240,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.19"
+   "version": "3.9.18"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/W2D1_AnEnsembleofFutures/W2D1_Tutorial1.ipynb b/tutorials/W2D1_AnEnsembleofFutures/W2D1_Tutorial1.ipynb
index af170f9f9..f470377ba 100644
--- a/tutorials/W2D1_AnEnsembleofFutures/W2D1_Tutorial1.ipynb
+++ b/tutorials/W2D1_AnEnsembleofFutures/W2D1_Tutorial1.ipynb
@@ -409,14 +409,8 @@
     "\n",
     "link_id = \"dsm6a\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
    ]
   },
   {
@@ -782,7 +776,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.19"
+   "version": "3.9.18"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/W2D1_AnEnsembleofFutures/W2D1_Tutorial2.ipynb b/tutorials/W2D1_AnEnsembleofFutures/W2D1_Tutorial2.ipynb
index eb7b92b26..1198a6653 100644
--- a/tutorials/W2D1_AnEnsembleofFutures/W2D1_Tutorial2.ipynb
+++ b/tutorials/W2D1_AnEnsembleofFutures/W2D1_Tutorial2.ipynb
@@ -578,7 +578,7 @@
     "\n",
     "\"\"\"\n",
     "1. Each of these models has slightly different physics, numerics, and discretization. During the Introduction to Climate Modeling day you showed that Earth's theoretical equilibrium temperature under fixed insolation changes as more details/complexity of the real Earth system are included. Similarly, the small differences between models result in each model having a slightly different equilibrium temperature for a given insolation, which also manifests in these long-term simulations.\n",
-    "\"\"\";"
+    "\"\"\""
    ]
   },
   {
@@ -749,7 +749,7 @@
     "\"\"\"\n",
     "1. The models agree much better across this time period, particularly in the reference period and during the rapid warming phase projected in the near future.\n",
     "2. There is variability at both ends of the scale, but the future (2080) period has more inter-model variability than the past (1850) period. This is likely because each of these models has to simulate a unique climate system, as we found in the last question, which leads to different responses to the rapid changes in effective radiative forcing that are projected in the near future.\n",
-    "\"\"\";"
+    "\"\"\""
    ]
   },
   {
@@ -827,7 +827,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.19"
+   "version": "3.9.18"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/W2D1_AnEnsembleofFutures/W2D1_Tutorial3.ipynb b/tutorials/W2D1_AnEnsembleofFutures/W2D1_Tutorial3.ipynb
index b2655ffba..f8b1e0947 100644
--- a/tutorials/W2D1_AnEnsembleofFutures/W2D1_Tutorial3.ipynb
+++ b/tutorials/W2D1_AnEnsembleofFutures/W2D1_Tutorial3.ipynb
@@ -597,7 +597,7 @@
     "1. Under both of these scenarios (SSP1-2.6 and SSP5-8.5), the projected warming of the climate is greater than the multi-model uncertainty.\n",
     "2. The warming is greater for SSP5-8.5, but so is the multi-model uncertainty, so the relative size of physical changes and multi-model uncertainty is comparable across both scenarios.\n",
     "3. The likely range includes the middle 66% of model results at a given time. For 5 models this means the ranges encompass the middle 3 models (i.e., they exclude the highest and lowest valued model at each time).\n",
-    "\"\"\";"
+    "\"\"\""
    ]
   },
   {
@@ -676,7 +676,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.19"
+   "version": "3.9.18"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/W2D1_AnEnsembleofFutures/W2D1_Tutorial4.ipynb b/tutorials/W2D1_AnEnsembleofFutures/W2D1_Tutorial4.ipynb
index 598574622..8099d3dba 100644
--- a/tutorials/W2D1_AnEnsembleofFutures/W2D1_Tutorial4.ipynb
+++ b/tutorials/W2D1_AnEnsembleofFutures/W2D1_Tutorial4.ipynb
@@ -627,7 +627,7 @@
     "\n",
     "\"\"\"\n",
     "1. I will let you decide what you take away from synthesizing these figures and data!\n",
-    "\"\"\";"
+    "\"\"\""
    ]
   },
   {
@@ -709,7 +709,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.19"
+   "version": "3.9.18"
   }
  },
  "nbformat": 4,

From f171f9a87ed8312859ab16751a5acef3c6baf97f Mon Sep 17 00:00:00 2001
From: Paul Heubel <paul_heubel@web.de>
Date: Tue, 9 Jul 2024 01:46:31 +0200
Subject: [PATCH 24/34] Removed ";"s to improve processing.

---
 tutorials/W2D3_ExtremesandVariability/W2D3_Tutorial1.ipynb | 4 ++--
 tutorials/W2D3_ExtremesandVariability/W2D3_Tutorial2.ipynb | 4 ++--
 tutorials/W2D3_ExtremesandVariability/W2D3_Tutorial3.ipynb | 4 ++--
 tutorials/W2D3_ExtremesandVariability/W2D3_Tutorial4.ipynb | 4 ++--
 tutorials/W2D3_ExtremesandVariability/W2D3_Tutorial8.ipynb | 6 +++---
 5 files changed, 11 insertions(+), 11 deletions(-)

diff --git a/tutorials/W2D3_ExtremesandVariability/W2D3_Tutorial1.ipynb b/tutorials/W2D3_ExtremesandVariability/W2D3_Tutorial1.ipynb
index 09108c692..928d228fa 100644
--- a/tutorials/W2D3_ExtremesandVariability/W2D3_Tutorial1.ipynb
+++ b/tutorials/W2D3_ExtremesandVariability/W2D3_Tutorial1.ipynb
@@ -784,7 +784,7 @@
     "# to_remove explanation\n",
     "\"\"\"\n",
     "1. As presented in the figure above, the data falls largely outside of the percentiles you calculated. That, paired with the skewness calculated earlier suggests a different distribution may fit the data better. For example, log-normal distributions tend to be better suited for describing skewed datasets such as this.\n",
-    "\"\"\";"
+    "\"\"\""
    ]
   },
   {
@@ -852,7 +852,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.19"
+   "version": "3.9.18"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/W2D3_ExtremesandVariability/W2D3_Tutorial2.ipynb b/tutorials/W2D3_ExtremesandVariability/W2D3_Tutorial2.ipynb
index 25f147a07..ac3760adc 100644
--- a/tutorials/W2D3_ExtremesandVariability/W2D3_Tutorial2.ipynb
+++ b/tutorials/W2D3_ExtremesandVariability/W2D3_Tutorial2.ipynb
@@ -712,7 +712,7 @@
     "\"\"\"\n",
     "1. 10, 40 and 70 mm/day.\n",
     "2. Our data only spans from 1920 to 2022. If we are truly interested in 100-year events we need to work with a longer dataset perhaps using paleo proxies or other instrumentation. The longer the dataset, the more frequently we would expect to observe the long return period events and increase our confidence in them. Other ideas would be estimating probability/cumulative density functions (next few tutorials) or to use resampling methods (coding exercise below).\n",
-    "\"\"\";"
+    "\"\"\""
    ]
   },
   {
@@ -908,7 +908,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.19"
+   "version": "3.9.18"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/W2D3_ExtremesandVariability/W2D3_Tutorial3.ipynb b/tutorials/W2D3_ExtremesandVariability/W2D3_Tutorial3.ipynb
index b82a5eed7..685817496 100644
--- a/tutorials/W2D3_ExtremesandVariability/W2D3_Tutorial3.ipynb
+++ b/tutorials/W2D3_ExtremesandVariability/W2D3_Tutorial3.ipynb
@@ -962,7 +962,7 @@
     "Scale parameter: The scale parameter influences the spread or width of the distribution. A higher scale parameter will widen the distribution, implying greater variability in the data and thicker tails, while a lower scale parameter will narrow the distribution, implying less probability of extreme events.\n",
     "\n",
     "Shape parameter: This parameter is unique to the GEV distribution and impacts the tails of the distribution. It can make the tails of the distribution thinner or thicker, which in turn affects the skewness and kurtosis of the distribution. In the context of extreme events, a positive shape parameter results in a heavy-tailed distribution, implying a higher probability of very extreme events (far from the median), while a negative shape parameter results in a light-tailed distribution, implying a lower probability of such events.\n",
-    "\"\"\";"
+    "\"\"\""
    ]
   },
   {
@@ -1030,7 +1030,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.19"
+   "version": "3.9.18"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/W2D3_ExtremesandVariability/W2D3_Tutorial4.ipynb b/tutorials/W2D3_ExtremesandVariability/W2D3_Tutorial4.ipynb
index 5f28a4b69..32fb5c738 100644
--- a/tutorials/W2D3_ExtremesandVariability/W2D3_Tutorial4.ipynb
+++ b/tutorials/W2D3_ExtremesandVariability/W2D3_Tutorial4.ipynb
@@ -715,7 +715,7 @@
     "# to_remove explanation\n",
     "\"\"\"\n",
     "Put your observations here. GEV distribution describes the data better than the normal distribution. However, they are similar for shorter return periods. This suggests that for common, less extreme events (short return periods), both the Normal and GEV distributions provide a similar representation of the data. This similarity is likely due to the fact that for less extreme events, the tail of the distribution (which captures extreme events) is less relevant. When we move toards longer return periods (which correspond to more extreme events), the two curves start to diverge.\n",
-    "\"\"\";"
+    "\"\"\""
    ]
   },
   {
@@ -931,7 +931,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.19"
+   "version": "3.9.18"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/W2D3_ExtremesandVariability/W2D3_Tutorial8.ipynb b/tutorials/W2D3_ExtremesandVariability/W2D3_Tutorial8.ipynb
index 1ac12d656..e0b622caa 100644
--- a/tutorials/W2D3_ExtremesandVariability/W2D3_Tutorial8.ipynb
+++ b/tutorials/W2D3_ExtremesandVariability/W2D3_Tutorial8.ipynb
@@ -1036,7 +1036,7 @@
     "1. Return level for a 3-year event under SSP5-8.5 is 34.5 degrees C (SSP2-4.5: 32.5, SSP1-2.6: 32). This is more than a very rare event (return period >> 100 years) in all other scenarios\n",
     "2. Return level for a 100-year event during the historical period: 32 degrees (SSP1-2.6: 32.5, SSP2-4.5: 33, SSP5-8.5:35.5). In the other scenarios this is the new 'normal', or more specific common events in all scenarios. Under SSP1-2.6 it is a 4-year event, and an annual event in all other scenarios.\n",
     "\n",
-    "\"\"\";"
+    "\"\"\""
    ]
   },
   {
@@ -1821,7 +1821,7 @@
     "1. There is a larger fraction of land area exposed to extreme temperature conditions the higher the emission scenario.\n",
     "\n",
     "2. The choice of threshold here could certainly impact the results! The best way to know for sure is to try it out! While the threshold used here is physically grounded in studies, it is important to understand the sensitivity of this choice, especially when using models which are imperfect. One possible route to understanding the uncertainty more would be to use an ensemble of climate models, similar to those from the IPCC Physical Basis day.\n",
-    "\"\"\";"
+    "\"\"\""
    ]
   },
   {
@@ -1895,7 +1895,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.19"
+   "version": "3.9.18"
   }
  },
  "nbformat": 4,

From c5cc6e6e68da10ca59c07bd296037248ef2d960b Mon Sep 17 00:00:00 2001
From: Paul Heubel <paul_heubel@web.de>
Date: Tue, 9 Jul 2024 01:59:22 +0200
Subject: [PATCH 25/34] FIX path to main instead of a certain release.

---
 tutorials/W2D3_ExtremesandVariability/W2D3_Tutorial6.ipynb | 2 +-
 tutorials/W2D3_ExtremesandVariability/W2D3_Tutorial7.ipynb | 2 +-
 tutorials/W2D3_ExtremesandVariability/W2D3_Tutorial8.ipynb | 6 +++---
 3 files changed, 5 insertions(+), 5 deletions(-)

diff --git a/tutorials/W2D3_ExtremesandVariability/W2D3_Tutorial6.ipynb b/tutorials/W2D3_ExtremesandVariability/W2D3_Tutorial6.ipynb
index cdfac4926..99e698758 100644
--- a/tutorials/W2D3_ExtremesandVariability/W2D3_Tutorial6.ipynb
+++ b/tutorials/W2D3_ExtremesandVariability/W2D3_Tutorial6.ipynb
@@ -1507,7 +1507,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.19"
+   "version": "3.9.18"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/W2D3_ExtremesandVariability/W2D3_Tutorial7.ipynb b/tutorials/W2D3_ExtremesandVariability/W2D3_Tutorial7.ipynb
index fc62a7ebb..8f76dfccd 100644
--- a/tutorials/W2D3_ExtremesandVariability/W2D3_Tutorial7.ipynb
+++ b/tutorials/W2D3_ExtremesandVariability/W2D3_Tutorial7.ipynb
@@ -1117,7 +1117,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.19"
+   "version": "3.9.18"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/W2D3_ExtremesandVariability/W2D3_Tutorial8.ipynb b/tutorials/W2D3_ExtremesandVariability/W2D3_Tutorial8.ipynb
index e0b622caa..693253913 100644
--- a/tutorials/W2D3_ExtremesandVariability/W2D3_Tutorial8.ipynb
+++ b/tutorials/W2D3_ExtremesandVariability/W2D3_Tutorial8.ipynb
@@ -83,9 +83,9 @@
     "# condacolab.install()\n",
     "# !mamba install numpy matplotlib seaborn pandas cartopy scipy texttable xarrayutils cf_xarray cmocean\n",
     "\n",
-    "!wget https://raw.githubusercontent.com/neuromatch/climate-course-content/release-v0.2.1/tutorials/W2D3_ExtremesandVariability/extremes_functions.py\n",
-    "!wget https://raw.githubusercontent.com/neuromatch/climate-course-content/release-v0.2.1/tutorials/W2D3_ExtremesandVariability/gev_functions.py\n",
-    "!wget https://raw.githubusercontent.com/neuromatch/climate-course-content/release-v0.2.1/tutorials/W2D3_ExtremesandVariability/sdfc_classes.py"
+    "!wget https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W2D3_ExtremesandVariability/extremes_functions.py\n",
+    "!wget https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W2D3_ExtremesandVariability/gev_functions.py\n",
+    "!wget https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W2D3_ExtremesandVariability/sdfc_classes.py"
    ]
   },
   {

From 4af173c8d5e84b221a846fa7aeaa5bf3893c03dd Mon Sep 17 00:00:00 2001
From: Zoltan <kosta.tsaf@gmail.com>
Date: Tue, 9 Jul 2024 13:24:58 -0400
Subject: [PATCH 26/34] process changed notebooks for release v1.0.0

---
 .github/workflows/notebook-pr.yaml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/workflows/notebook-pr.yaml b/.github/workflows/notebook-pr.yaml
index 0cc88dff2..a01a1adec 100644
--- a/.github/workflows/notebook-pr.yaml
+++ b/.github/workflows/notebook-pr.yaml
@@ -55,7 +55,7 @@ jobs:
       - name: Run Notebooks
         uses: ./.github/actions/check-notebooks
         with:
-          run_all: 'true'
+          run_all: 'false'
           # exec_flag: '--check-only'
           exec_flag: '--execute'
           # exercise-continue-on-error: true

From 01f4a6baee7a2607ad7a171d56643b111016c81b Mon Sep 17 00:00:00 2001
From: Paul Heubel <paul_heubel@web.de>
Date: Wed, 10 Jul 2024 10:40:35 +0200
Subject: [PATCH 27/34] Renamed directory according to day title.

---
 .../README.md                                       |   0
 .../W1D5_DaySummary.ipynb                           |   0
 .../W1D5_Intro.ipynb                                |   0
 .../W1D5_Outro.ipynb                                |   0
 .../W1D5_Tutorial1.ipynb                            |   0
 .../W1D5_Tutorial2.ipynb                            |   0
 .../W1D5_Tutorial3.ipynb                            |   0
 .../W1D5_Tutorial4.ipynb                            |   0
 .../W1D5_Tutorial5.ipynb                            |   0
 .../W1D5_Tutorial6.ipynb                            |   0
 .../W1D5_Tutorial7.ipynb                            |   0
 .../W1D5_Tutorial8.ipynb                            |   0
 .../chapter_title.md                                |   0
 .../further_reading.md                              |   0
 .../instructor/W1D5_DaySummary.ipynb                |   0
 .../instructor/W1D5_Intro.ipynb                     |   0
 .../instructor/W1D5_Outro.ipynb                     |   0
 .../instructor/W1D5_Tutorial1.ipynb                 |   0
 .../instructor/W1D5_Tutorial2.ipynb                 |   0
 .../instructor/W1D5_Tutorial3.ipynb                 |   0
 .../instructor/W1D5_Tutorial4.ipynb                 |   0
 .../instructor/W1D5_Tutorial5.ipynb                 |   0
 .../instructor/W1D5_Tutorial6.ipynb                 |   0
 .../instructor/W1D5_Tutorial7.ipynb                 |   0
 .../instructor/W1D5_Tutorial8.ipynb                 |   0
 .../solutions/W1D5_Tutorial1_Solution_3a0c44b9.py   |   0
 .../solutions/W1D5_Tutorial1_Solution_46434603.py   |   0
 .../solutions/W1D5_Tutorial1_Solution_83fdc728.py   |   0
 .../solutions/W1D5_Tutorial1_Solution_a2d0f592.py   |   0
 .../solutions/W1D5_Tutorial1_Solution_a6ad63d3.py   |   0
 .../solutions/W1D5_Tutorial1_Solution_bd931bda.py   |   0
 .../solutions/W1D5_Tutorial2_Solution_3fa7479c.py   |   0
 .../solutions/W1D5_Tutorial2_Solution_94090198.py   |   0
 .../solutions/W1D5_Tutorial2_Solution_d879cd19.py   |   0
 .../solutions/W1D5_Tutorial2_Solution_f766d310.py   |   0
 .../solutions/W1D5_Tutorial3_Solution_35a3c870.py   |   0
 .../solutions/W1D5_Tutorial3_Solution_422bae10.py   |   0
 .../solutions/W1D5_Tutorial3_Solution_4ae01b99.py   |   0
 .../solutions/W1D5_Tutorial3_Solution_5e19a97e.py   |   0
 .../solutions/W1D5_Tutorial3_Solution_71e39306.py   |   0
 .../solutions/W1D5_Tutorial3_Solution_7d35dd95.py   |   0
 .../solutions/W1D5_Tutorial3_Solution_a1d313aa.py   |   0
 .../solutions/W1D5_Tutorial3_Solution_a860c046.py   |   0
 .../solutions/W1D5_Tutorial3_Solution_b87ad7af.py   |   0
 .../solutions/W1D5_Tutorial3_Solution_caa2deb1.py   |   0
 .../solutions/W1D5_Tutorial3_Solution_d7862a90.py   |   0
 .../solutions/W1D5_Tutorial4_Solution_449c4dae.py   |   0
 .../solutions/W1D5_Tutorial4_Solution_66fe91b4.py   |   0
 .../solutions/W1D5_Tutorial4_Solution_81a4e015.py   |   0
 .../solutions/W1D5_Tutorial4_Solution_b91846bf.py   |   0
 .../solutions/W1D5_Tutorial4_Solution_b9dadf47.py   |   0
 .../solutions/W1D5_Tutorial5_Solution_012273c4.py   |   0
 .../solutions/W1D5_Tutorial5_Solution_0fd7e870.py   |   0
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From fd52e2f37d1d8b02c5201f0893a351e019e30e9f Mon Sep 17 00:00:00 2001
From: Paul Heubel <paul_heubel@web.de>
Date: Wed, 10 Jul 2024 10:47:46 +0200
Subject: [PATCH 28/34] Renamed according to day title.

---
 .../README.md                                       |   0
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From 0ede212b9befbfb161be57cfd536368b6b3468f7 Mon Sep 17 00:00:00 2001
From: Paul Heubel <paul_heubel@web.de>
Date: Wed, 10 Jul 2024 10:48:41 +0200
Subject: [PATCH 29/34] Renamed dir according to day title.

---
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diff --git a/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/README.md b/tutorials/W1D2_Ocean-AtmosphereReanalysis/README.md
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From 788d973247ad6627947ec497bf3d61d1485cf40c Mon Sep 17 00:00:00 2001
From: Paul Heubel <paul_heubel@web.de>
Date: Wed, 10 Jul 2024 10:49:27 +0200
Subject: [PATCH 30/34] FIX update day titles of W1 and section titles.

---
 tutorials/materials.yml | 12 ++++++------
 1 file changed, 6 insertions(+), 6 deletions(-)

diff --git a/tutorials/materials.yml b/tutorials/materials.yml
index 771c019db..521d0e309 100644
--- a/tutorials/materials.yml
+++ b/tutorials/materials.yml
@@ -9,23 +9,23 @@
   playlist: https://youtube.com/playlist?list=PLkBQOLLbi18MoOWPdzGj8t0Yxm-IC1nvN
   tutorials: 8
 - day: W1D2
-  category: Climate Data
-  name: State of the Climate Ocean and Atmosphere Reanalysis
+  category: Past and Present Climate
+  name: Ocean-Atmosphere Reanalysis
   playlist: https://youtube.com/playlist?list=PLkBQOLLbi18MtuSiOkabOmG-KdhOM_Xi_
   tutorials: 6
 - day: W1D3
-  category: Climate Data
-  name: Remote Sensing Land Ocean and Atmosphere
+  category: Past and Present Climate
+  name: Remote Sensing
   playlist: https://youtube.com/playlist?list=PLkBQOLLbi18NwBOdx0d59O34HmG8yrGp7
   tutorials: 8
 - day: W1D4
-  category: Climate Data
+  category: Past and Present Climate
   name: Paleoclimate
   playlist: https://youtube.com/playlist?list=PLkBQOLLbi18M30SfesAh0AHGKIIYbjQhl
   tutorials: 9
 - day: W1D5
   category: Climate Future
-  name: Climate Modeling
+  name: Introduction to Climate Modeling
   playlist: https://youtube.com/playlist?list=PLkBQOLLbi18OQtfBlfe_Py6AubwL8FAs1
   tutorials: 8
 - day: W2D1

From 1693128b8ac42190ce116013b313e790399fbe64 Mon Sep 17 00:00:00 2001
From: Paul Heubel <paul_heubel@web.de>
Date: Wed, 10 Jul 2024 12:46:18 +0200
Subject: [PATCH 31/34] Added pyleoclim to requirements

---
 requirements.txt | 1 +
 1 file changed, 1 insertion(+)

diff --git a/requirements.txt b/requirements.txt
index b342921d8..6b3e15482 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -47,4 +47,5 @@ dicelib @ https://github.com/mptouzel/PyDICE/archive/master.zip
 cdsapi
 texttable
 lipd
+pyleoclim
 # cfgrib

From 6734ae87772a49572a31599989bf3233f8d17093 Mon Sep 17 00:00:00 2001
From: Paul Heubel <paul_heubel@web.de>
Date: Wed, 10 Jul 2024 12:47:49 +0200
Subject: [PATCH 32/34] FIX looping over the correct items of the entire
 datatree dt now.

---
 .../W1D5_Tutorial8.ipynb                      | 27 +++++++++----------
 1 file changed, 12 insertions(+), 15 deletions(-)

diff --git a/tutorials/W1D5_IntroductiontoClimateModeling/W1D5_Tutorial8.ipynb b/tutorials/W1D5_IntroductiontoClimateModeling/W1D5_Tutorial8.ipynb
index b572f03b5..4b7421720 100644
--- a/tutorials/W1D5_IntroductiontoClimateModeling/W1D5_Tutorial8.ipynb
+++ b/tutorials/W1D5_IntroductiontoClimateModeling/W1D5_Tutorial8.ipynb
@@ -66,7 +66,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 90386,
      "status": "ok",
@@ -97,7 +96,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -145,7 +143,6 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -165,7 +162,6 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -233,7 +229,6 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
-    "execution": {},
     "pycharm": {
      "name": "#%%\n"
     },
@@ -288,7 +283,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 12915,
      "status": "ok",
@@ -339,6 +333,15 @@
     "dt = cat.to_datatree(**kwargs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "dt"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -359,7 +362,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 313,
      "status": "error",
@@ -399,7 +401,7 @@
     "dt_with_area = DataTree()\n",
     "\n",
     "# add the sub-catalog to the DataTree object via map_over_subtree()\n",
-    "for model, subtree in dt_area.items():\n",
+    "for model, subtree in dt.items():\n",
     "    metric = dt_area[model][\"historical\"].ds[\"areacello\"]\n",
     "    dt_with_area[model] = subtree.map_over_subtree(_parse_metric, metric)"
    ]
@@ -408,7 +410,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 4330,
      "status": "ok",
@@ -444,7 +445,7 @@
     "dt_with_area = DataTree()\n",
     "\n",
     "# add the sub-catalog to the DataTree object via map_over_subtree()\n",
-    "for model, subtree in dt_area.items():\n",
+    "for model, subtree in dt.items():\n",
     "    metric = dt_area[model][\"historical\"].ds[\"areacello\"]\n",
     "    dt_with_area[model] = subtree.map_over_subtree(_parse_metric, metric)"
    ]
@@ -508,7 +509,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 296,
      "status": "error",
@@ -546,7 +546,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "executionInfo": {
      "elapsed": 31727,
      "status": "ok",
@@ -615,9 +614,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# to_remove explanation\n",

From 73c90666f74a1559c9db30dfd4efd305c77a76dd Mon Sep 17 00:00:00 2001
From: Zoltan <kosta.tsaf@gmail.com>
Date: Wed, 10 Jul 2024 12:55:06 -0400
Subject: [PATCH 33/34] retry process

---
 .github/actions/setup/action.yaml | 2 +-
 requirements.txt                  | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/.github/actions/setup/action.yaml b/.github/actions/setup/action.yaml
index 8da5b3919..208602a63 100644
--- a/.github/actions/setup/action.yaml
+++ b/.github/actions/setup/action.yaml
@@ -142,7 +142,7 @@ runs:
         pip install cfgrib
         python -m cfgrib selfcheck
         pip install requests aiohttp
-        pip install jupyter-book==0.14.0 ghp-import cftime pyleoclim importlib-metadata==4.13.0
+        pip install jupyter-book==0.14.0 ghp-import cftime importlib-metadata==4.13.0
       shell: bash -l {0}
 
     - name: Build climlab from source
diff --git a/requirements.txt b/requirements.txt
index 6b3e15482..5795b4fb4 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -47,5 +47,5 @@ dicelib @ https://github.com/mptouzel/PyDICE/archive/master.zip
 cdsapi
 texttable
 lipd
-pyleoclim
+pyleoclim==0.14.0
 # cfgrib

From c04c435f8b468fe875739a83155bea1238978d00 Mon Sep 17 00:00:00 2001
From: GitHub Action <action@github.com>
Date: Wed, 10 Jul 2024 21:55:12 +0000
Subject: [PATCH 34/34] Process tutorial notebooks

---
 .../Projects_Tutorial8.ipynb                  |   8 +-
 .../instructor/Projects_Tutorial8.ipynb       |   6 +-
 .../student/Projects_Tutorial8.ipynb          |   6 +-
 tutorials/README.md                           |  88 +++---
 .../W1D1_Intro.ipynb                          |  23 +-
 .../W1D1_Tutorial1.ipynb                      |   2 +-
 .../W1D1_Tutorial2.ipynb                      |  22 +-
 .../W1D1_Tutorial3.ipynb                      |  32 ++-
 .../W1D1_Tutorial4.ipynb                      |  43 ++-
 .../W1D1_Tutorial5.ipynb                      |  45 +++-
 .../W1D1_Tutorial6.ipynb                      |  38 ++-
 .../W1D1_Tutorial7.ipynb                      |  40 ++-
 .../W1D1_Tutorial8.ipynb                      |  36 ++-
 .../W1D1_Tutorial9.ipynb                      |  40 ++-
 .../instructor/W1D1_Intro.ipynb               |  68 ++++-
 .../instructor/W1D1_Tutorial1.ipynb           |  10 +-
 .../instructor/W1D1_Tutorial2.ipynb           |  78 +++++-
 .../instructor/W1D1_Tutorial3.ipynb           | 104 ++++++-
 .../instructor/W1D1_Tutorial4.ipynb           |  84 +++++-
 .../instructor/W1D1_Tutorial5.ipynb           | 102 ++++++-
 .../instructor/W1D1_Tutorial6.ipynb           |  84 +++++-
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 .../instructor/W1D1_Tutorial8.ipynb           |  84 +++++-
 .../instructor/W1D1_Tutorial9.ipynb           |  84 +++++-
 ...py => W1D1_Tutorial4_Solution_c61cf4b9.py} |   2 +-
 ...py => W1D1_Tutorial5_Solution_11d6af2a.py} |   2 +-
 ...py => W1D1_Tutorial5_Solution_79c64ee7.py} |   2 +-
 ...py => W1D1_Tutorial6_Solution_2f2d35e9.py} |   2 +-
 ...py => W1D1_Tutorial7_Solution_9e05e276.py} |   2 +-
 ...py => W1D1_Tutorial8_Solution_0bc6741a.py} |   2 +-
 ...py => W1D1_Tutorial9_Solution_ffe2e77d.py} |   2 +-
 .../student/W1D1_Intro.ipynb                  |  68 ++++-
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 .../student/W1D1_Tutorial9.ipynb              |  84 +++++-
 .../W1D2_Ocean-AtmosphereReanalysis/README.md |  34 +--
 .../W1D2_Intro.ipynb                          |  17 +-
 .../W1D2_Tutorial1.ipynb                      |  64 ++++-
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 .../instructor/get_ERA5_reanalysis_data.ipynb | 216 +++++++++++++++
 ...py => W1D2_Tutorial2_Solution_04b4bc1e.py} |   2 +-
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 .../W1D2_Tutorial3_Solution_a061ee5b.py       |  23 --
 .../W1D2_Tutorial3_Solution_f288b0e0.py       |  29 ++
 ...py => W1D2_Tutorial4_Solution_3561fefc.py} |   2 +-
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 .../student/get_ERA5_reanalysis_data.ipynb    | 216 +++++++++++++++
 tutorials/W1D3_RemoteSensing/README.md        |  42 +--
 tutorials/W1D3_RemoteSensing/W1D3_Intro.ipynb |  23 +-
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 ...py => W2D3_Tutorial1_Solution_be51f3cc.py} |   2 +-
 ...py => W2D3_Tutorial2_Solution_99c3b035.py} |   2 +-
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 .../student/W2D3_Tutorial1.ipynb              |   4 +-
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 tutorials/instructor/intro.ipynb              | 190 +++++++++++++
 tutorials/intro.ipynb                         |  11 +-
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 rename tutorials/W2D3_ExtremesandVariability/solutions/{W2D3_Tutorial8_Solution_43e64815.py => W2D3_Tutorial8_Solution_51796267.py} (99%)
 delete mode 100644 tutorials/W2D3_ExtremesandVariability/static/W2D3_Tutorial1_Solution_e35d1bc8_1.png
 create mode 100644 tutorials/W2D3_ExtremesandVariability/static/W2D3_Tutorial1_Solution_e35d1bc8_2.png
 rename tutorials/W2D3_ExtremesandVariability/static/{W2D3_Tutorial6_Solution_f0cfaef4_1.png => W2D3_Tutorial6_Solution_f0cfaef4_2.png} (100%)
 create mode 100644 tutorials/instructor/intro.ipynb
 create mode 100644 tutorials/student/intro.ipynb

diff --git a/tutorials/Projects_GoodResearchPractices/Projects_Tutorial8.ipynb b/tutorials/Projects_GoodResearchPractices/Projects_Tutorial8.ipynb
index d96775bbe..d7e974053 100644
--- a/tutorials/Projects_GoodResearchPractices/Projects_Tutorial8.ipynb
+++ b/tutorials/Projects_GoodResearchPractices/Projects_Tutorial8.ipynb
@@ -55,7 +55,8 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "form"
+    "cellView": "form",
+    "execution": {}
    },
    "outputs": [],
    "source": [
@@ -111,7 +112,8 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "form"
+    "cellView": "form",
+    "execution": {}
    },
    "outputs": [],
    "source": [
@@ -225,7 +227,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.18"
+   "version": "3.9.19"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/Projects_GoodResearchPractices/instructor/Projects_Tutorial8.ipynb b/tutorials/Projects_GoodResearchPractices/instructor/Projects_Tutorial8.ipynb
index a7f4f83d2..d7e974053 100644
--- a/tutorials/Projects_GoodResearchPractices/instructor/Projects_Tutorial8.ipynb
+++ b/tutorials/Projects_GoodResearchPractices/instructor/Projects_Tutorial8.ipynb
@@ -19,7 +19,7 @@
     "\n",
     "**Good Research Practices**\n",
     "\n",
-    "**Content creators:** Marguerite Brown, Zane Mitrevica, Natalie Steinemann, Yuxin Zhou\n",
+    "**Content creators:** Marguerite Brown, Zane Mitrevica, Aakash Sane, Natalie Steinemann, Yuxin Zhou\n",
     "\n",
     "**Content reviewers:** Katrina Dobson, Sloane Garelick, Maria Gonzalez, Nahid Hasan, Paul Heubel, Sherry Mi, Beatriz Cosenza Muralles, Cheng Zhang\n",
     "\n",
@@ -99,7 +99,7 @@
     "  return tab_contents\n",
     "\n",
     "\n",
-    "video_ids = [('Youtube', 'XZfqyancNpk'), ('Bilibili', 'BV1494y1B7qs')]\n",
+    "video_ids = [('Youtube', 'HEsrjlyza5o'), ('Bilibili', 'BV1494y1B7qs')]\n",
     "tab_contents = display_videos(video_ids, W=730, H=410)\n",
     "tabs = widgets.Tab()\n",
     "tabs.children = tab_contents\n",
@@ -120,7 +120,7 @@
     "# @title Tutorial slides\n",
     "# @markdown These are the slides for the videos in all tutorials today\n",
     "from IPython.display import IFrame\n",
-    "link_id = \"9s6ub\"\n",
+    "link_id = \"648nt\"\n",
     "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
     "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
    ]
diff --git a/tutorials/Projects_GoodResearchPractices/student/Projects_Tutorial8.ipynb b/tutorials/Projects_GoodResearchPractices/student/Projects_Tutorial8.ipynb
index a7f4f83d2..d7e974053 100644
--- a/tutorials/Projects_GoodResearchPractices/student/Projects_Tutorial8.ipynb
+++ b/tutorials/Projects_GoodResearchPractices/student/Projects_Tutorial8.ipynb
@@ -19,7 +19,7 @@
     "\n",
     "**Good Research Practices**\n",
     "\n",
-    "**Content creators:** Marguerite Brown, Zane Mitrevica, Natalie Steinemann, Yuxin Zhou\n",
+    "**Content creators:** Marguerite Brown, Zane Mitrevica, Aakash Sane, Natalie Steinemann, Yuxin Zhou\n",
     "\n",
     "**Content reviewers:** Katrina Dobson, Sloane Garelick, Maria Gonzalez, Nahid Hasan, Paul Heubel, Sherry Mi, Beatriz Cosenza Muralles, Cheng Zhang\n",
     "\n",
@@ -99,7 +99,7 @@
     "  return tab_contents\n",
     "\n",
     "\n",
-    "video_ids = [('Youtube', 'XZfqyancNpk'), ('Bilibili', 'BV1494y1B7qs')]\n",
+    "video_ids = [('Youtube', 'HEsrjlyza5o'), ('Bilibili', 'BV1494y1B7qs')]\n",
     "tab_contents = display_videos(video_ids, W=730, H=410)\n",
     "tabs = widgets.Tab()\n",
     "tabs.children = tab_contents\n",
@@ -120,7 +120,7 @@
     "# @title Tutorial slides\n",
     "# @markdown These are the slides for the videos in all tutorials today\n",
     "from IPython.display import IFrame\n",
-    "link_id = \"9s6ub\"\n",
+    "link_id = \"648nt\"\n",
     "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
     "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
    ]
diff --git a/tutorials/README.md b/tutorials/README.md
index 9cc515ad1..d965bee31 100644
--- a/tutorials/README.md
+++ b/tutorials/README.md
@@ -2,7 +2,7 @@
 
 <!-- DO NOT EDIT THIS FILE. IT IS AUTO-GENERATED BY A FRIENDLY ROBOT -->
 
-[W1D1](#w1d1---climate-system-overview) | [W1D2](#w1d2---stateofthe-climate-oceanand-atmosphere-reanalysis) | [W1D3](#w1d3---remote-sensing-land-oceanand-atmosphere) | [W1D4](#w1d4---paleoclimate) | [W1D5](#w1d5---climate-modeling) | [W2D1](#w2d1---an-ensembleof-futures) | [W2D2](#w2d2---the-socioeconomicsof-climate-change) | [W2D3](#w2d3---extremesand-variability) | [W2D4](#w2d4---a-iand-climate-change) | [W2D5](#w2d5---projects-day)
+[W1D1](#w1d1---climate-system-overview) | [W1D2](#w1d2---ocean--atmosphere-reanalysis) | [W1D3](#w1d3---remote-sensing) | [W1D4](#w1d4---paleoclimate) | [W1D5](#w1d5---introductionto-climate-modeling) | [W2D1](#w2d1---an-ensembleof-futures) | [W2D2](#w2d2---the-socioeconomicsof-climate-change) | [W2D3](#w2d3---extremesand-variability) | [W2D4](#w2d4---a-iand-climate-change) | [W2D5](#w2d5---projects-day)
 
 *Warning:* The 'render with NBViewer' buttons may show outdated content.
 
@@ -29,46 +29,46 @@
 [Further Reading](https://github.com/neuromatch/climate-course-content/blob/main/tutorials/W1D1_ClimateSystemOverview/further_reading.md)
 
 
-## W1D2 - Stateofthe Climate Oceanand Atmosphere Reanalysis
+## W1D2 - Ocean- Atmosphere Reanalysis
 
 [YouTube Playlist](https://youtube.com/playlist?list=PLkBQOLLbi18MtuSiOkabOmG-KdhOM_Xi_)
 |   | Run | Run | View |
 | - | --- | --- | ---- |
-| Intro | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/W1D2_Intro.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/W1D2_Intro.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/W1D2_Intro.ipynb?flush_cache=true) |
-| Tutorial 1 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/student/W1D2_Tutorial1.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/student/W1D2_Tutorial1.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/student/W1D2_Tutorial1.ipynb?flush_cache=true) |
-| Tutorial 2 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/student/W1D2_Tutorial2.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/student/W1D2_Tutorial2.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/student/W1D2_Tutorial2.ipynb?flush_cache=true) |
-| Tutorial 3 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/student/W1D2_Tutorial3.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/student/W1D2_Tutorial3.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/student/W1D2_Tutorial3.ipynb?flush_cache=true) |
-| Tutorial 4 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/student/W1D2_Tutorial4.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/student/W1D2_Tutorial4.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/student/W1D2_Tutorial4.ipynb?flush_cache=true) |
-| Tutorial 5 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/student/W1D2_Tutorial5.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/student/W1D2_Tutorial5.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/student/W1D2_Tutorial5.ipynb?flush_cache=true) |
-| Tutorial 6 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/student/W1D2_Tutorial6.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/student/W1D2_Tutorial6.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/student/W1D2_Tutorial6.ipynb?flush_cache=true) |
-| Outro | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/W1D2_Outro.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/W1D2_Outro.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/W1D2_Outro.ipynb?flush_cache=true) |
+| Intro | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_Ocean-AtmosphereReanalysis/W1D2_Intro.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D2_Ocean-AtmosphereReanalysis/W1D2_Intro.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_Ocean-AtmosphereReanalysis/W1D2_Intro.ipynb?flush_cache=true) |
+| Tutorial 1 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_Ocean-AtmosphereReanalysis/student/W1D2_Tutorial1.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D2_Ocean-AtmosphereReanalysis/student/W1D2_Tutorial1.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_Ocean-AtmosphereReanalysis/student/W1D2_Tutorial1.ipynb?flush_cache=true) |
+| Tutorial 2 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_Ocean-AtmosphereReanalysis/student/W1D2_Tutorial2.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D2_Ocean-AtmosphereReanalysis/student/W1D2_Tutorial2.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_Ocean-AtmosphereReanalysis/student/W1D2_Tutorial2.ipynb?flush_cache=true) |
+| Tutorial 3 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_Ocean-AtmosphereReanalysis/student/W1D2_Tutorial3.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D2_Ocean-AtmosphereReanalysis/student/W1D2_Tutorial3.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_Ocean-AtmosphereReanalysis/student/W1D2_Tutorial3.ipynb?flush_cache=true) |
+| Tutorial 4 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_Ocean-AtmosphereReanalysis/student/W1D2_Tutorial4.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D2_Ocean-AtmosphereReanalysis/student/W1D2_Tutorial4.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_Ocean-AtmosphereReanalysis/student/W1D2_Tutorial4.ipynb?flush_cache=true) |
+| Tutorial 5 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_Ocean-AtmosphereReanalysis/student/W1D2_Tutorial5.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D2_Ocean-AtmosphereReanalysis/student/W1D2_Tutorial5.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_Ocean-AtmosphereReanalysis/student/W1D2_Tutorial5.ipynb?flush_cache=true) |
+| Tutorial 6 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_Ocean-AtmosphereReanalysis/student/W1D2_Tutorial6.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D2_Ocean-AtmosphereReanalysis/student/W1D2_Tutorial6.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_Ocean-AtmosphereReanalysis/student/W1D2_Tutorial6.ipynb?flush_cache=true) |
+| Outro | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_Ocean-AtmosphereReanalysis/W1D2_Outro.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D2_Ocean-AtmosphereReanalysis/W1D2_Outro.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_Ocean-AtmosphereReanalysis/W1D2_Outro.ipynb?flush_cache=true) |
 
 
 
 
-[Further Reading](https://github.com/neuromatch/climate-course-content/blob/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/further_reading.md)
+[Further Reading](https://github.com/neuromatch/climate-course-content/blob/main/tutorials/W1D2_Ocean-AtmosphereReanalysis/further_reading.md)
 
 
-## W1D3 - Remote Sensing Land Oceanand Atmosphere
+## W1D3 - Remote Sensing
 
 [YouTube Playlist](https://youtube.com/playlist?list=PLkBQOLLbi18NwBOdx0d59O34HmG8yrGp7)
 |   | Run | Run | View |
 | - | --- | --- | ---- |
-| Intro | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/W1D3_Intro.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/W1D3_Intro.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/W1D3_Intro.ipynb?flush_cache=true) |
-| Tutorial 1 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/student/W1D3_Tutorial1.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/student/W1D3_Tutorial1.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/student/W1D3_Tutorial1.ipynb?flush_cache=true) |
-| Tutorial 2 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/student/W1D3_Tutorial2.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/student/W1D3_Tutorial2.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/student/W1D3_Tutorial2.ipynb?flush_cache=true) |
-| Tutorial 3 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/student/W1D3_Tutorial3.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/student/W1D3_Tutorial3.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/student/W1D3_Tutorial3.ipynb?flush_cache=true) |
-| Tutorial 4 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/student/W1D3_Tutorial4.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/student/W1D3_Tutorial4.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/student/W1D3_Tutorial4.ipynb?flush_cache=true) |
-| Tutorial 5 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/student/W1D3_Tutorial5.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/student/W1D3_Tutorial5.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/student/W1D3_Tutorial5.ipynb?flush_cache=true) |
-| Tutorial 6 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/student/W1D3_Tutorial6.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/student/W1D3_Tutorial6.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/student/W1D3_Tutorial6.ipynb?flush_cache=true) |
-| Tutorial 7 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/student/W1D3_Tutorial7.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/student/W1D3_Tutorial7.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/student/W1D3_Tutorial7.ipynb?flush_cache=true) |
-| Tutorial 8 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/student/W1D3_Tutorial8.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/student/W1D3_Tutorial8.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/student/W1D3_Tutorial8.ipynb?flush_cache=true) |
-| Outro | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/W1D3_Outro.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/W1D3_Outro.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/W1D3_Outro.ipynb?flush_cache=true) |
+| Intro | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensing/W1D3_Intro.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D3_RemoteSensing/W1D3_Intro.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensing/W1D3_Intro.ipynb?flush_cache=true) |
+| Tutorial 1 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensing/student/W1D3_Tutorial1.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D3_RemoteSensing/student/W1D3_Tutorial1.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensing/student/W1D3_Tutorial1.ipynb?flush_cache=true) |
+| Tutorial 2 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensing/student/W1D3_Tutorial2.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D3_RemoteSensing/student/W1D3_Tutorial2.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensing/student/W1D3_Tutorial2.ipynb?flush_cache=true) |
+| Tutorial 3 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensing/student/W1D3_Tutorial3.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D3_RemoteSensing/student/W1D3_Tutorial3.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensing/student/W1D3_Tutorial3.ipynb?flush_cache=true) |
+| Tutorial 4 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensing/student/W1D3_Tutorial4.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D3_RemoteSensing/student/W1D3_Tutorial4.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensing/student/W1D3_Tutorial4.ipynb?flush_cache=true) |
+| Tutorial 5 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensing/student/W1D3_Tutorial5.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D3_RemoteSensing/student/W1D3_Tutorial5.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensing/student/W1D3_Tutorial5.ipynb?flush_cache=true) |
+| Tutorial 6 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensing/student/W1D3_Tutorial6.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D3_RemoteSensing/student/W1D3_Tutorial6.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensing/student/W1D3_Tutorial6.ipynb?flush_cache=true) |
+| Tutorial 7 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensing/student/W1D3_Tutorial7.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D3_RemoteSensing/student/W1D3_Tutorial7.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensing/student/W1D3_Tutorial7.ipynb?flush_cache=true) |
+| Tutorial 8 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensing/student/W1D3_Tutorial8.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D3_RemoteSensing/student/W1D3_Tutorial8.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensing/student/W1D3_Tutorial8.ipynb?flush_cache=true) |
+| Outro | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensing/W1D3_Outro.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D3_RemoteSensing/W1D3_Outro.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensing/W1D3_Outro.ipynb?flush_cache=true) |
 
 
 
 
-[Further Reading](https://github.com/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/further_reading.md)
+[Further Reading](https://github.com/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensing/further_reading.md)
 
 
 ## W1D4 - Paleoclimate
@@ -94,26 +94,36 @@
 [Further Reading](https://github.com/neuromatch/climate-course-content/blob/main/tutorials/W1D4_Paleoclimate/further_reading.md)
 
 
-## W1D5 - Climate Modeling
+## W1D5 - Introductionto Climate Modeling
 
 [YouTube Playlist](https://youtube.com/playlist?list=PLkBQOLLbi18OQtfBlfe_Py6AubwL8FAs1)
 |   | Run | Run | View |
 | - | --- | --- | ---- |
-| Intro | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_ClimateModeling/W1D5_Intro.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_ClimateModeling/W1D5_Intro.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_ClimateModeling/W1D5_Intro.ipynb?flush_cache=true) |
-| Tutorial 1 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_ClimateModeling/student/W1D5_Tutorial1.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_ClimateModeling/student/W1D5_Tutorial1.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_ClimateModeling/student/W1D5_Tutorial1.ipynb?flush_cache=true) |
-| Tutorial 2 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_ClimateModeling/student/W1D5_Tutorial2.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_ClimateModeling/student/W1D5_Tutorial2.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_ClimateModeling/student/W1D5_Tutorial2.ipynb?flush_cache=true) |
-| Tutorial 3 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_ClimateModeling/student/W1D5_Tutorial3.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_ClimateModeling/student/W1D5_Tutorial3.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_ClimateModeling/student/W1D5_Tutorial3.ipynb?flush_cache=true) |
-| Tutorial 4 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_ClimateModeling/student/W1D5_Tutorial4.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_ClimateModeling/student/W1D5_Tutorial4.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_ClimateModeling/student/W1D5_Tutorial4.ipynb?flush_cache=true) |
-| Tutorial 5 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_ClimateModeling/student/W1D5_Tutorial5.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_ClimateModeling/student/W1D5_Tutorial5.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_ClimateModeling/student/W1D5_Tutorial5.ipynb?flush_cache=true) |
-| Tutorial 6 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_ClimateModeling/student/W1D5_Tutorial6.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_ClimateModeling/student/W1D5_Tutorial6.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_ClimateModeling/student/W1D5_Tutorial6.ipynb?flush_cache=true) |
-| Tutorial 7 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_ClimateModeling/student/W1D5_Tutorial7.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_ClimateModeling/student/W1D5_Tutorial7.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_ClimateModeling/student/W1D5_Tutorial7.ipynb?flush_cache=true) |
-| Tutorial 8 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_ClimateModeling/student/W1D5_Tutorial8.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_ClimateModeling/student/W1D5_Tutorial8.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_ClimateModeling/student/W1D5_Tutorial8.ipynb?flush_cache=true) |
-| Outro | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_ClimateModeling/W1D5_Outro.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_ClimateModeling/W1D5_Outro.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_ClimateModeling/W1D5_Outro.ipynb?flush_cache=true) |
-
-
-
-
-[Further Reading](https://github.com/neuromatch/climate-course-content/blob/main/tutorials/W1D5_ClimateModeling/further_reading.md)
+| DaySummary | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/W1D5_DaySummary.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_IntroductiontoClimateModeling/W1D5_DaySummary.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/W1D5_DaySummary.ipynb?flush_cache=true) |
+| Intro | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/W1D5_Intro.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_IntroductiontoClimateModeling/W1D5_Intro.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/W1D5_Intro.ipynb?flush_cache=true) |
+| Outro | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/W1D5_Outro.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_IntroductiontoClimateModeling/W1D5_Outro.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/W1D5_Outro.ipynb?flush_cache=true) |
+| Tutorial 1 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial1.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial1.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial1.ipynb?flush_cache=true) |
+| Tutorial 2 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial2.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial2.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial2.ipynb?flush_cache=true) |
+| Tutorial 3 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial3.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial3.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial3.ipynb?flush_cache=true) |
+| Tutorial 4 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial4.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial4.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial4.ipynb?flush_cache=true) |
+| Tutorial 5 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial5.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial5.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial5.ipynb?flush_cache=true) |
+| Tutorial 6 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial6.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial6.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial6.ipynb?flush_cache=true) |
+| Tutorial 7 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial7.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial7.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial7.ipynb?flush_cache=true) |
+| Tutorial 8 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial8.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial8.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial8.ipynb?flush_cache=true) |
+| Tutorial 1 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial1.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial1.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial1.ipynb?flush_cache=true) |
+| Tutorial 2 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial2.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial2.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial2.ipynb?flush_cache=true) |
+| Tutorial 3 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial3.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial3.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial3.ipynb?flush_cache=true) |
+| Tutorial 4 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial4.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial4.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial4.ipynb?flush_cache=true) |
+| Tutorial 5 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial5.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial5.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial5.ipynb?flush_cache=true) |
+| Tutorial 6 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial6.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial6.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial6.ipynb?flush_cache=true) |
+| Tutorial 7 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial7.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial7.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial7.ipynb?flush_cache=true) |
+| Tutorial 8 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial8.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial8.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial8.ipynb?flush_cache=true) |
+| Outro | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/W1D5_Outro.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_IntroductiontoClimateModeling/W1D5_Outro.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/W1D5_Outro.ipynb?flush_cache=true) |
+
+
+
+
+[Further Reading](https://github.com/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/further_reading.md)
 
 
 ## W2D1 - An Ensembleof Futures
diff --git a/tutorials/W1D1_ClimateSystemOverview/W1D1_Intro.ipynb b/tutorials/W1D1_ClimateSystemOverview/W1D1_Intro.ipynb
index 18f7f3d73..1c9aea835 100644
--- a/tutorials/W1D1_ClimateSystemOverview/W1D1_Intro.ipynb
+++ b/tutorials/W1D1_ClimateSystemOverview/W1D1_Intro.ipynb
@@ -50,7 +50,10 @@
    "cell_type": "code",
    "execution_count": null,
    "id": "d8266b33-da1b-43a9-927f-ab629de4a10b",
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Install and import feedback gadget\n",
@@ -88,7 +91,8 @@
    "execution_count": null,
    "id": "afe1b307",
    "metadata": {
-    "cellView": "form"
+    "cellView": "form",
+    "execution": {}
    },
    "outputs": [],
    "source": [
@@ -153,7 +157,10 @@
    "cell_type": "code",
    "execution_count": null,
    "id": "48f83cbb-fe30-4ed9-bfe2-c13792e81502",
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -175,7 +182,8 @@
    "execution_count": null,
    "id": "c044d10e",
    "metadata": {
-    "cellView": "form"
+    "cellView": "form",
+    "execution": {}
    },
    "outputs": [],
    "source": [
@@ -192,7 +200,10 @@
    "cell_type": "code",
    "execution_count": null,
    "id": "f22cd6b1-37ca-4da3-9ea8-d2a4d65d3c1f",
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -227,7 +238,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.18"
+   "version": "3.9.19"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial1.ipynb b/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial1.ipynb
index 0f4f69be0..06d916d75 100644
--- a/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial1.ipynb
+++ b/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial1.ipynb
@@ -824,7 +824,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.18"
+   "version": "3.9.19"
   },
   "toc-autonumbering": false
  },
diff --git a/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial2.ipynb b/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial2.ipynb
index b404efa12..08bfc710a 100644
--- a/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial2.ipynb
+++ b/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial2.ipynb
@@ -91,7 +91,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Install and import feedback gadget\n",
@@ -190,7 +193,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -225,7 +231,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -426,7 +435,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -741,7 +753,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.18"
+   "version": "3.9.19"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial3.ipynb b/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial3.ipynb
index d86d59b46..28295900f 100644
--- a/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial3.ipynb
+++ b/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial3.ipynb
@@ -108,7 +108,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Install and import feedback gadget\n",
@@ -220,7 +223,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -255,7 +261,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -368,7 +377,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -713,7 +725,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -795,7 +810,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -865,7 +883,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.18"
+   "version": "3.9.19"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial4.ipynb b/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial4.ipynb
index cd416ccc4..74fb296b4 100644
--- a/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial4.ipynb
+++ b/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial4.ipynb
@@ -86,7 +86,9 @@
    "cell_type": "code",
    "execution_count": null,
    "id": "5e22563d-1148-4079-9f92-5f2e780b9119",
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# installations ( uncomment and run this cell ONLY when using google colab or kaggle )\n",
@@ -98,6 +100,7 @@
    "execution_count": null,
    "id": "06073287-7bdb-45b5-9cec-8cdf123adb49",
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -112,7 +115,10 @@
    "cell_type": "code",
    "execution_count": null,
    "id": "754caab0-66fc-4e23-bd60-6de2ff7d3b0a",
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Install and import feedback gadget\n",
@@ -141,6 +147,7 @@
    "id": "ed6bcdfe-d18b-42a4-96d6-2f921d9ce3fd",
    "metadata": {
     "cellView": "form",
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -160,6 +167,7 @@
    "id": "1712a218-1c6b-4ae9-9b89-5843bdde1d96",
    "metadata": {
     "cellView": "form",
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -216,7 +224,10 @@
    "cell_type": "code",
    "execution_count": null,
    "id": "65eb3752-2e77-4024-9f6e-6cdbd66337a5",
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -229,6 +240,7 @@
    "id": "682c6f71-edc2-4088-bd74-fb526e667ba7",
    "metadata": {
     "cellView": "form",
+    "execution": {},
     "pycharm": {
      "name": "#%%\n"
     },
@@ -252,7 +264,10 @@
    "cell_type": "code",
    "execution_count": null,
    "id": "bb3c61b6-544e-422a-be4c-ee7c6a2e2164",
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -277,6 +292,7 @@
    "execution_count": null,
    "id": "7837f8bd-da89-4718-ab02-d5107576d2d6",
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 303,
      "status": "ok",
@@ -310,7 +326,9 @@
    "cell_type": "code",
    "execution_count": null,
    "id": "cbe80157",
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "ds.tos"
@@ -331,6 +349,7 @@
    "execution_count": null,
    "id": "09542eab-998d-4b2d-807c-dccd5bd4329e",
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 14,
      "status": "ok",
@@ -367,6 +386,7 @@
    "execution_count": null,
    "id": "78c1ffc2-45cb-40cc-962e-c76021d9ab1c",
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 12,
      "status": "ok",
@@ -428,6 +448,7 @@
    "execution_count": null,
    "id": "06e3bfff",
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -450,6 +471,7 @@
    "execution_count": null,
    "id": "400c3dab",
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -472,6 +494,7 @@
    "execution_count": null,
    "id": "5d397f30",
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -494,6 +517,7 @@
    "execution_count": null,
    "id": "59b84034-7d42-4080-932f-0eefd165953d",
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 297,
      "status": "ok",
@@ -526,6 +550,7 @@
    "execution_count": null,
    "id": "a49b957e-ea24-414e-a422-c40a3723fbae",
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 815,
      "status": "ok",
@@ -563,6 +588,7 @@
    "execution_count": null,
    "id": "589b4cf2-9431-43e9-ad76-9acbc7bde892",
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -578,7 +604,10 @@
    "cell_type": "code",
    "execution_count": null,
    "id": "1115cecf-9d73-4ac1-a6d3-9425342dc642",
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -646,7 +675,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.18"
+   "version": "3.9.19"
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  "nbformat": 4,
diff --git a/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial5.ipynb b/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial5.ipynb
index b2a891eef..500f42b8d 100644
--- a/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial5.ipynb
+++ b/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial5.ipynb
@@ -79,7 +79,9 @@
    "cell_type": "code",
    "execution_count": null,
    "id": "9226796c-2eca-44c2-9dc7-5cf2ba93836d",
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# installations ( uncomment and run this cell ONLY when using google colab or kaggle )\n",
@@ -91,6 +93,7 @@
    "execution_count": null,
    "id": "06073287-7bdb-45b5-9cec-8cdf123adb49",
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 2358,
      "status": "ok",
@@ -117,7 +120,10 @@
    "cell_type": "code",
    "execution_count": null,
    "id": "2ad30cf1-5467-4010-ac68-5046fb316018",
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Install and import feedback gadget\n",
@@ -146,6 +152,7 @@
    "id": "72e04965-e982-444d-b3da-4e1e639c6899",
    "metadata": {
     "cellView": "form",
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -165,6 +172,7 @@
    "id": "21725d4b-ee68-42aa-af76-70392b4ab6ac",
    "metadata": {
     "cellView": "form",
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -221,7 +229,10 @@
    "cell_type": "code",
    "execution_count": null,
    "id": "a2371121-637e-4517-9db2-1c5faab01348",
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -234,6 +245,7 @@
    "id": "1bfcf3bd-6805-4cfb-90c4-a9067f6ce91c",
    "metadata": {
     "cellView": "form",
+    "execution": {},
     "pycharm": {
      "name": "#%%\n"
     },
@@ -257,7 +269,10 @@
    "cell_type": "code",
    "execution_count": null,
    "id": "c28bb25a-1852-4477-b932-41fdecbe42ef",
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -300,6 +315,7 @@
    "execution_count": null,
    "id": "7837f8bd-da89-4718-ab02-d5107576d2d6",
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 388,
      "status": "ok",
@@ -334,6 +350,7 @@
    "execution_count": null,
    "id": "c0348ee8-6e9b-4f50-a844-375ae00d2771",
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 959,
      "status": "ok",
@@ -380,6 +397,7 @@
    "execution_count": null,
    "id": "6e4fb25e-165f-4350-a93d-46a344f2d175",
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 160,
      "status": "ok",
@@ -426,6 +444,7 @@
    "execution_count": null,
    "id": "c6990393-fb5f-4a10-b8e2-fd9c6917d9d2",
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 215,
      "status": "ok",
@@ -472,6 +491,7 @@
    "execution_count": null,
    "id": "7e568c2f-7143-4346-85ce-a430db03316e",
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 2695,
      "status": "ok",
@@ -507,6 +527,7 @@
    "execution_count": null,
    "id": "f908c377-67fa-449c-b8d1-82ba6a14baff",
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 363,
      "status": "ok",
@@ -551,6 +572,7 @@
    "execution_count": null,
    "id": "fb839b81-6bc3-4cf8-8d06-748a3770cd22",
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -567,7 +589,10 @@
    "cell_type": "code",
    "execution_count": null,
    "id": "68b7485b-5ca4-47fd-8009-32376b4b5049",
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -599,6 +624,7 @@
    "execution_count": null,
    "id": "22c61c11-2a48-4c6c-8009-6f20e0101237",
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 584,
      "status": "ok",
@@ -632,6 +658,7 @@
    "execution_count": null,
    "id": "19a2808b-81f9-40e5-ab31-d63bfce85eae",
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 1075,
      "status": "ok",
@@ -667,6 +694,7 @@
    "execution_count": null,
    "id": "1ce210a0-f392-448d-a2bf-cd27ad370d99",
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -684,7 +712,10 @@
    "cell_type": "code",
    "execution_count": null,
    "id": "78e2905e-cb34-4ca0-b17a-2defe5ec0630",
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -754,7 +785,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.18"
+   "version": "3.9.19"
   }
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diff --git a/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial6.ipynb b/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial6.ipynb
index 8e9d619d6..4d86167e7 100644
--- a/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial6.ipynb
+++ b/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial6.ipynb
@@ -79,7 +79,9 @@
    "cell_type": "code",
    "execution_count": null,
    "id": "b3ea206d-56dd-43fe-a1e3-01b2235c9f51",
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# installations ( uncomment and run this cell ONLY when using google colab or kaggle )\n",
@@ -91,6 +93,7 @@
    "execution_count": null,
    "id": "06073287-7bdb-45b5-9cec-8cdf123adb49",
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -105,7 +108,10 @@
    "cell_type": "code",
    "execution_count": null,
    "id": "e05b62d2-e46f-4d85-af57-72213527248a",
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Install and import feedback gadget\n",
@@ -134,6 +140,7 @@
    "id": "b4cabcfc-2cc0-450a-8e94-4f8e635213c5",
    "metadata": {
     "cellView": "form",
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -153,6 +160,7 @@
    "id": "e941ab00-bac3-4fbb-a582-9a73da96b617",
    "metadata": {
     "cellView": "form",
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -209,7 +217,10 @@
    "cell_type": "code",
    "execution_count": null,
    "id": "93161e14-e3a3-4bf2-8448-ecd35e1ee7c8",
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -222,6 +233,7 @@
    "id": "a1ac91c8-11f3-4bb0-86ee-8eff1e61187c",
    "metadata": {
     "cellView": "form",
+    "execution": {},
     "pycharm": {
      "name": "#%%\n"
     },
@@ -245,7 +257,10 @@
    "cell_type": "code",
    "execution_count": null,
    "id": "ba94f7c9-1871-449d-ad5c-6a13612e7748",
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -269,6 +284,7 @@
    "execution_count": null,
    "id": "7837f8bd-da89-4718-ab02-d5107576d2d6",
    "metadata": {
+    "execution": {},
     "executionInfo": {
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      "status": "ok",
@@ -303,6 +319,7 @@
    "execution_count": null,
    "id": "4c9940df-5174-49bf-9117-eef1e14abec0",
    "metadata": {
+    "execution": {},
     "executionInfo": {
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      "status": "ok",
@@ -343,6 +360,7 @@
    "execution_count": null,
    "id": "35fc2054-df48-4ea2-8433-632ba8755c61",
    "metadata": {
+    "execution": {},
     "executionInfo": {
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      "status": "ok",
@@ -376,6 +394,7 @@
    "execution_count": null,
    "id": "5d3abf06-a341-45ac-a3f2-76131016c0b3",
    "metadata": {
+    "execution": {},
     "executionInfo": {
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      "status": "ok",
@@ -427,6 +446,7 @@
    "execution_count": null,
    "id": "a5878de6-f3ab-43e0-8f0d-12ab51631450",
    "metadata": {
+    "execution": {},
     "executionInfo": {
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      "status": "ok",
@@ -461,6 +481,7 @@
    "execution_count": null,
    "id": "b8f7e3a5-0748-4395-95b0-0e31d0a5d4d1",
    "metadata": {
+    "execution": {},
     "tags": []
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    "outputs": [],
@@ -484,6 +505,7 @@
    "execution_count": null,
    "id": "802c5e99-7223-49b5-a867-91d943075d52",
    "metadata": {
+    "execution": {},
     "executionInfo": {
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      "status": "ok",
@@ -523,6 +545,7 @@
    "execution_count": null,
    "id": "5b3181b8-e3a2-4740-aac7-8ba205e12e52",
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -539,7 +562,10 @@
    "cell_type": "code",
    "execution_count": null,
    "id": "96461dcd-f5b7-409a-bb95-da0c2600938e",
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -609,7 +635,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.18"
+   "version": "3.9.19"
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diff --git a/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial7.ipynb b/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial7.ipynb
index fb9ae6086..afb3a614a 100644
--- a/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial7.ipynb
+++ b/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial7.ipynb
@@ -81,7 +81,9 @@
    "cell_type": "code",
    "execution_count": null,
    "id": "9fa2315d-13a8-4499-b962-4434934b39ed",
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# installations ( uncomment and run this cell ONLY when using google colab or kaggle )\n",
@@ -93,6 +95,7 @@
    "execution_count": null,
    "id": "06073287-7bdb-45b5-9cec-8cdf123adb49",
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -107,7 +110,10 @@
    "cell_type": "code",
    "execution_count": null,
    "id": "21b5614e-3a3f-46d1-a926-283e9458da74",
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Install and import feedback gadget\n",
@@ -136,6 +142,7 @@
    "id": "5c385e97-285f-45d4-88e2-26ee76b8d039",
    "metadata": {
     "cellView": "form",
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -155,6 +162,7 @@
    "id": "2fd1ee75-9e23-4204-a896-9a08da3e794f",
    "metadata": {
     "cellView": "form",
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -211,7 +219,10 @@
    "cell_type": "code",
    "execution_count": null,
    "id": "43bfb42a-8ce6-44b6-9a88-6bca2000bd7e",
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -224,6 +235,7 @@
    "id": "c9027490-8086-41a3-9489-0f164b6375a2",
    "metadata": {
     "cellView": "form",
+    "execution": {},
     "pycharm": {
      "name": "#%%\n"
     },
@@ -247,7 +259,10 @@
    "cell_type": "code",
    "execution_count": null,
    "id": "3918492b-f1c5-4b8e-8479-748a1652f724",
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -278,6 +293,7 @@
    "execution_count": null,
    "id": "7837f8bd-da89-4718-ab02-d5107576d2d6",
    "metadata": {
+    "execution": {},
     "tags": []
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    "outputs": [],
@@ -306,6 +322,7 @@
    "execution_count": null,
    "id": "a9cfb76b-c4ab-441e-a474-c66b7af944ad",
    "metadata": {
+    "execution": {},
     "executionInfo": {
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      "status": "ok",
@@ -330,6 +347,7 @@
    "execution_count": null,
    "id": "6927f5be-d313-4d03-bab8-d22b3cb13899",
    "metadata": {
+    "execution": {},
     "executionInfo": {
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      "status": "ok",
@@ -370,6 +388,7 @@
    "execution_count": null,
    "id": "342acbf1-4eee-4d0d-bb52-b394ffcd556d",
    "metadata": {
+    "execution": {},
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@@ -394,6 +413,7 @@
    "execution_count": null,
    "id": "0eb0cc4e-661a-4ab1-96ad-e096917ef104",
    "metadata": {
+    "execution": {},
     "executionInfo": {
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      "status": "ok",
@@ -433,6 +453,7 @@
    "execution_count": null,
    "id": "118df2c7",
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -447,6 +468,7 @@
    "execution_count": null,
    "id": "f0b9ef33",
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -471,6 +493,7 @@
    "execution_count": null,
    "id": "1517017a",
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -483,6 +506,7 @@
    "execution_count": null,
    "id": "daf709a8",
    "metadata": {
+    "execution": {},
     "tags": []
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    "outputs": [],
@@ -521,6 +545,7 @@
    "execution_count": null,
    "id": "34f4c5ba-8a12-4472-b482-4ca4f2948a2c",
    "metadata": {
+    "execution": {},
     "tags": []
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    "outputs": [],
@@ -537,7 +562,10 @@
    "cell_type": "code",
    "execution_count": null,
    "id": "b026c173-582c-48e1-8504-ef1c13acee9e",
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -604,7 +632,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.18"
+   "version": "3.9.19"
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diff --git a/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial8.ipynb b/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial8.ipynb
index 1c842d76f..30518e204 100644
--- a/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial8.ipynb
+++ b/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial8.ipynb
@@ -77,7 +77,9 @@
    "cell_type": "code",
    "execution_count": null,
    "id": "5d7768f4-c27d-4502-a975-934632c1d9b3",
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# installations ( uncomment and run this cell ONLY when using google colab or kaggle )\n",
@@ -89,6 +91,7 @@
    "execution_count": null,
    "id": "06073287-7bdb-45b5-9cec-8cdf123adb49",
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 1691,
      "status": "ok",
@@ -113,7 +116,10 @@
    "cell_type": "code",
    "execution_count": null,
    "id": "d041a3d6-01af-42cc-bdc0-7e62eb272bc9",
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Install and import feedback gadget\n",
@@ -142,6 +148,7 @@
    "id": "994efaf1-a38b-42f4-ac31-40b747e6b806",
    "metadata": {
     "cellView": "form",
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -161,6 +168,7 @@
    "id": "7bc232cf-a917-49e3-93b9-77afb5fb3f20",
    "metadata": {
     "cellView": "form",
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -217,7 +225,10 @@
    "cell_type": "code",
    "execution_count": null,
    "id": "6647e202-05cd-490c-b694-8ca6bad2ccdd",
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -230,6 +241,7 @@
    "id": "bc214dbf-b28f-44c4-bb53-8d8e852610e6",
    "metadata": {
     "cellView": "form",
+    "execution": {},
     "pycharm": {
      "name": "#%%\n"
     },
@@ -253,7 +265,10 @@
    "cell_type": "code",
    "execution_count": null,
    "id": "09bb8a72-a965-4598-9b34-8341b293776f",
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -297,6 +312,7 @@
    "execution_count": null,
    "id": "7837f8bd-da89-4718-ab02-d5107576d2d6",
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 4386,
      "status": "ok",
@@ -341,6 +357,7 @@
    "execution_count": null,
    "id": "ac3e42eb-1852-4580-9c52-e7237135ed01",
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 166,
      "status": "ok",
@@ -376,6 +393,7 @@
    "execution_count": null,
    "id": "61abc5b3-aadf-4a96-98a2-c9c36094a863",
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 159,
      "status": "ok",
@@ -410,6 +428,7 @@
    "execution_count": null,
    "id": "eced16af",
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -434,6 +453,7 @@
    "execution_count": null,
    "id": "ca1e150f-c422-4f0c-8f64-9c734bcbdee3",
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -467,6 +487,7 @@
    "execution_count": null,
    "id": "e6518686-8d6b-41be-adbb-b8b121894fd7",
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -485,7 +506,10 @@
    "cell_type": "code",
    "execution_count": null,
    "id": "a7722baa-1de1-4bc3-937c-398c43ecf953",
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -556,7 +580,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.18"
+   "version": "3.9.19"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial9.ipynb b/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial9.ipynb
index 0ab92bcb7..1e6558a91 100644
--- a/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial9.ipynb
+++ b/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial9.ipynb
@@ -77,7 +77,9 @@
    "cell_type": "code",
    "execution_count": null,
    "id": "a3d3f235-a5bf-4445-be5b-0aba0c3c1f7e",
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# installations ( uncomment and run this cell ONLY when using google colab or kaggle )\n",
@@ -89,6 +91,7 @@
    "execution_count": null,
    "id": "06073287-7bdb-45b5-9cec-8cdf123adb49",
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 521,
      "status": "ok",
@@ -113,7 +116,10 @@
    "cell_type": "code",
    "execution_count": null,
    "id": "07974de6-0957-45b3-9e77-895af3c459c8",
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Install and import feedback gadget\n",
@@ -142,6 +148,7 @@
    "id": "b389f92a-2998-494d-a58c-f582a91c6b95",
    "metadata": {
     "cellView": "form",
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -161,6 +168,7 @@
    "id": "51f0a30a-35f7-4b29-a1d6-5d242f6aefa7",
    "metadata": {
     "cellView": "form",
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -217,7 +225,10 @@
    "cell_type": "code",
    "execution_count": null,
    "id": "bf18fa96-f99f-420c-95aa-5b18704fac8a",
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -230,6 +241,7 @@
    "id": "af18aad1-ddc6-404c-bf27-978471fe2b70",
    "metadata": {
     "cellView": "form",
+    "execution": {},
     "pycharm": {
      "name": "#%%\n"
     },
@@ -253,7 +265,10 @@
    "cell_type": "code",
    "execution_count": null,
    "id": "6a5f6a63-2185-448e-9a94-104977794bb0",
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -286,6 +301,7 @@
    "execution_count": null,
    "id": "7837f8bd-da89-4718-ab02-d5107576d2d6",
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 4331,
      "status": "ok",
@@ -320,6 +336,7 @@
    "execution_count": null,
    "id": "c9bf1c46-e7ed-43c1-8a45-e03d22295da1",
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 624,
      "status": "ok",
@@ -366,6 +383,7 @@
    "execution_count": null,
    "id": "505bbd2d",
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -400,6 +418,7 @@
    "execution_count": null,
    "id": "090f1997-8dea-4eed-aa55-ab3a180ecdd5",
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 728,
      "status": "ok",
@@ -435,6 +454,7 @@
    "execution_count": null,
    "id": "aae12476-4802-42a2-993b-29da6c383535",
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 567,
      "status": "ok",
@@ -460,7 +480,9 @@
    "cell_type": "code",
    "execution_count": null,
    "id": "c12ef69c-b730-486c-9300-286cc2e338ae",
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "nino_mean.plot()"
@@ -493,6 +515,7 @@
    "execution_count": null,
    "id": "c8986c67",
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -512,7 +535,10 @@
    "cell_type": "code",
    "execution_count": null,
    "id": "601b5358-8df2-4b1e-9576-bb5323d6b9ce",
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -583,7 +609,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.18"
+   "version": "3.9.19"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/W1D1_ClimateSystemOverview/instructor/W1D1_Intro.ipynb b/tutorials/W1D1_ClimateSystemOverview/instructor/W1D1_Intro.ipynb
index 66fad600e..1c9aea835 100644
--- a/tutorials/W1D1_ClimateSystemOverview/instructor/W1D1_Intro.ipynb
+++ b/tutorials/W1D1_ClimateSystemOverview/instructor/W1D1_Intro.ipynb
@@ -46,6 +46,36 @@
     "3. Identify the main concepts covered in the course."
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "d8266b33-da1b-43a9-927f-ab629de4a10b",
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D1_Intro\""
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "452816ee",
@@ -123,6 +153,20 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "48f83cbb-fe30-4ed9-bfe2-c13792e81502",
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Climate_Solutions_Video\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "168f8f55",
@@ -148,14 +192,22 @@
     "\n",
     "link_id = \"ghmn5\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "f22cd6b1-37ca-4da3-9ea8-d2a4d65d3c1f",
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Climate_Solutions_Slides\")"
    ]
   }
  ],
diff --git a/tutorials/W1D1_ClimateSystemOverview/instructor/W1D1_Tutorial1.ipynb b/tutorials/W1D1_ClimateSystemOverview/instructor/W1D1_Tutorial1.ipynb
index 9900b2e00..06d916d75 100644
--- a/tutorials/W1D1_ClimateSystemOverview/instructor/W1D1_Tutorial1.ipynb
+++ b/tutorials/W1D1_ClimateSystemOverview/instructor/W1D1_Tutorial1.ipynb
@@ -243,14 +243,8 @@
     "\n",
     "link_id = \"4suf5\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
    ]
   },
   {
diff --git a/tutorials/W1D1_ClimateSystemOverview/instructor/W1D1_Tutorial2.ipynb b/tutorials/W1D1_ClimateSystemOverview/instructor/W1D1_Tutorial2.ipynb
index 3af66f36e..2c761bcca 100644
--- a/tutorials/W1D1_ClimateSystemOverview/instructor/W1D1_Tutorial2.ipynb
+++ b/tutorials/W1D1_ClimateSystemOverview/instructor/W1D1_Tutorial2.ipynb
@@ -88,6 +88,35 @@
     "import matplotlib.pyplot as plt"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D1_T2\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -161,6 +190,19 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Solar_Radiation_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -182,14 +224,21 @@
     "\n",
     "link_id = \"gh5us\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Solar_Radiation_Slides\")"
    ]
   },
   {
@@ -385,6 +434,19 @@
     "coordinate_selection"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Coding_Exercise_1_2\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
diff --git a/tutorials/W1D1_ClimateSystemOverview/instructor/W1D1_Tutorial3.ipynb b/tutorials/W1D1_ClimateSystemOverview/instructor/W1D1_Tutorial3.ipynb
index 3f0bd4614..28295900f 100644
--- a/tutorials/W1D1_ClimateSystemOverview/instructor/W1D1_Tutorial3.ipynb
+++ b/tutorials/W1D1_ClimateSystemOverview/instructor/W1D1_Tutorial3.ipynb
@@ -105,6 +105,35 @@
     "import matplotlib.pyplot as plt"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D1_T3\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -191,6 +220,19 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Atmospheric_Climate_Systems_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -212,14 +254,21 @@
     "\n",
     "link_id = \"cnfwz\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Atmospheric_Climate_Systems_Slides\")"
    ]
   },
   {
@@ -325,6 +374,19 @@
     "\"\"\""
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_1\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -660,6 +722,19 @@
     "\"\"\""
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_2_2\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -732,6 +807,19 @@
     "\"\"\""
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_2_3\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
diff --git a/tutorials/W1D1_ClimateSystemOverview/instructor/W1D1_Tutorial4.ipynb b/tutorials/W1D1_ClimateSystemOverview/instructor/W1D1_Tutorial4.ipynb
index 8282fb0be..74fb296b4 100644
--- a/tutorials/W1D1_ClimateSystemOverview/instructor/W1D1_Tutorial4.ipynb
+++ b/tutorials/W1D1_ClimateSystemOverview/instructor/W1D1_Tutorial4.ipynb
@@ -111,6 +111,36 @@
     "import matplotlib.pyplot as plt"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "754caab0-66fc-4e23-bd60-6de2ff7d3b0a",
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D1_T4\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -190,6 +220,20 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "65eb3752-2e77-4024-9f6e-6cdbd66337a5",
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Oceanic_Climate_Systems_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -212,14 +256,22 @@
     "\n",
     "link_id = \"hmqfr\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "bb3c61b6-544e-422a-be4c-ee7c6a2e2164",
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Oceanic_Climate_Systems_Slides\")"
    ]
   },
   {
@@ -545,7 +597,21 @@
     "\n",
     "\"\"\"\n",
     "1.  Upwelling is a process in which deep, cold water rises toward the surface. This can be identified in a sea surface temperature (SST) map as areas where the SST is colder than the surrounding waters. We note off the west coast of South America there is a 'tongue' of colder water from about -40 S northward. The strength of upwelling can often vary seasonally, and thus in our annual mean SST map above, the effects of this are likely more subtle.\n",
-    "\"\"\";"
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "1115cecf-9d73-4ac1-a6d3-9425342dc642",
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_2\")"
    ]
   },
   {
diff --git a/tutorials/W1D1_ClimateSystemOverview/instructor/W1D1_Tutorial5.ipynb b/tutorials/W1D1_ClimateSystemOverview/instructor/W1D1_Tutorial5.ipynb
index 6c918bf93..500f42b8d 100644
--- a/tutorials/W1D1_ClimateSystemOverview/instructor/W1D1_Tutorial5.ipynb
+++ b/tutorials/W1D1_ClimateSystemOverview/instructor/W1D1_Tutorial5.ipynb
@@ -116,6 +116,36 @@
     "import matplotlib.pyplot as plt"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "2ad30cf1-5467-4010-ac68-5046fb316018",
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D1_T5\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -195,6 +225,20 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "a2371121-637e-4517-9db2-1c5faab01348",
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Terrestrial_Temperature_Rainfall_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -217,14 +261,22 @@
     "\n",
     "link_id = \"9z6km\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "c28bb25a-1852-4477-b932-41fdecbe42ef",
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Terrestrial_Temperature_Rainfall_Slides\")"
    ]
   },
   {
@@ -530,7 +582,21 @@
     "\"\"\"\n",
     "1. This location's strong seasonality suggests that it experiences significant seasonal changes in incoming solar radiation received at the surface over the course of a year.\n",
     "2. Seasonal variations in sea surface temperature (SST) would differ at different latitudes. At the equator, the seasonal variations in SST tend to be relatively small. This is because the equatorial region experiences a relatively constant amount of solar radiation throughout the year, resulting in a relatively stable SST. At the poles, however, the seasonal variations in SST are more pronounced. At 50ºS, the seasonal cycle would be opposite that shown here because the northern and southern hemispheres experience their seasons at different times of year (that is northern hemisphere summer is southern hemisphere winter).\n",
-    "\"\"\";"
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "68b7485b-5ca4-47fd-8009-32376b4b5049",
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_1_2_1\")"
    ]
   },
   {
@@ -616,7 +682,7 @@
     "execution": {}
    },
    "source": [
-    "#### Questions 1.2.1: Climate Connection\n",
+    "#### Questions 1.2.2: Climate Connection\n",
     "\n",
     "1. What patterns do you observe in this map?\n",
     "2. Why is there such an apparent difference between the Northern and Southern Hemisphere SST changes?\n",
@@ -639,7 +705,21 @@
     "1. Generally the difference is negative in the Northern Hemisphere and positive in the Southern Hemisphere.\n",
     "2. The hemispheres have opposing signs, which is because of Earth's tilt and how it affects the timing of the seasons in each hemisphere (i.e. Northern Hemisphere summer is Southern Hemisphere winter). In the Northern Hemisphere, the difference is negative because the Northern Hemisphere July is warmer than the Northern Hemisphere January. In the Southern Hemisphere, the opposite is true.\n",
     "3. The ITCZ shifts with the seasons. When the Sun is directly overhead at the Northern Tropics (June), the ITCZ moves northwards, and when the Sun is directly overhead at the Southern Tropics (December), the ITCZ shifts southwards. This migration can affect the distribution of rain, leading to wet and dry seasons in many tropical regions.\n",
-    "\"\"\";"
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "78e2905e-cb34-4ca0-b17a-2defe5ec0630",
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_1_2_2\")"
    ]
   },
   {
diff --git a/tutorials/W1D1_ClimateSystemOverview/instructor/W1D1_Tutorial6.ipynb b/tutorials/W1D1_ClimateSystemOverview/instructor/W1D1_Tutorial6.ipynb
index 98bf0df64..4d86167e7 100644
--- a/tutorials/W1D1_ClimateSystemOverview/instructor/W1D1_Tutorial6.ipynb
+++ b/tutorials/W1D1_ClimateSystemOverview/instructor/W1D1_Tutorial6.ipynb
@@ -104,6 +104,36 @@
     "import matplotlib.pyplot as plt"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "e05b62d2-e46f-4d85-af57-72213527248a",
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D1_T6\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -183,6 +213,20 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "93161e14-e3a3-4bf2-8448-ecd35e1ee7c8",
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Orbital_Cycles_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -205,14 +249,22 @@
     "\n",
     "link_id = \"tcb2q\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "ba94f7c9-1871-449d-ad5c-6a13612e7748",
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Orbital_Cycles_Slides\")"
    ]
   },
   {
@@ -503,7 +555,21 @@
     "\"\"\"\n",
     "1. An area-weighted mean global temperature anomaly provides a more accurate representation of global temperature changes by accounting for the uneven distribution of grid cell sizes across latitudes. It ensures each region's contribution to the global mean is proportional to its surface area, avoiding any disproportionate influence from smaller areas at higher latitudes. Both weighted and unweighted SST means show the similar increasing trend in temperature from 2000 to 2014, although by eye, it appears that the trend would be slightly lower for the unweighted mean.\n",
     "2. The observed SST warming trend from 2000 to 2014 is similar to the rate of change observed from 1980 to 2000, which fits into the larger context of the substantial warming trend observed over the past century. Over this period, global average temperatures have risen rapidly, at a rate that is not typical in the context of most longer-term naturally driven temperature variations.\n",
-    "\"\"\";"
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "96461dcd-f5b7-409a-bb95-da0c2600938e",
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_1\")"
    ]
   },
   {
diff --git a/tutorials/W1D1_ClimateSystemOverview/instructor/W1D1_Tutorial7.ipynb b/tutorials/W1D1_ClimateSystemOverview/instructor/W1D1_Tutorial7.ipynb
index 35371d2d2..afb3a614a 100644
--- a/tutorials/W1D1_ClimateSystemOverview/instructor/W1D1_Tutorial7.ipynb
+++ b/tutorials/W1D1_ClimateSystemOverview/instructor/W1D1_Tutorial7.ipynb
@@ -106,6 +106,36 @@
     "from pythia_datasets import DATASETS"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "21b5614e-3a3f-46d1-a926-283e9458da74",
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D1_T7\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -185,6 +215,20 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "43bfb42a-8ce6-44b6-9a88-6bca2000bd7e",
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Carbon_Cycle_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -207,14 +251,22 @@
     "\n",
     "link_id = \"sb3n5\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "3918492b-f1c5-4b8e-8479-748a1652f724",
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Carbon_Cycle_Slides\")"
    ]
   },
   {
@@ -503,7 +555,21 @@
     "\"\"\"\n",
     "1. In general, by examining the data at these different time scales, you can get a more comprehensive understanding of the SST variations and their potential causes.\n",
     "2. The original monthly data gives you the most granular view of the data, allowing you to see monthly variations in SST. Coarsening the data over 4-month periods reduces the temporal resolution but provides a slightly smoothed series that could help identify patterns or trends over this larger time period. A 6-month moving average could be useful for identifying semi-annual trends and reducing the impact of short-term noise in the data. The annually resampled (12 months) data provides a high-level view of the SST data, emphasizing the annual pattern. This can be useful for identifying long-term trends or changes in the data over the span of years.\n",
-    "\"\"\";"
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "b026c173-582c-48e1-8504-ef1c13acee9e",
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_1_4\")"
    ]
   },
   {
diff --git a/tutorials/W1D1_ClimateSystemOverview/instructor/W1D1_Tutorial8.ipynb b/tutorials/W1D1_ClimateSystemOverview/instructor/W1D1_Tutorial8.ipynb
index 7acd6e530..30518e204 100644
--- a/tutorials/W1D1_ClimateSystemOverview/instructor/W1D1_Tutorial8.ipynb
+++ b/tutorials/W1D1_ClimateSystemOverview/instructor/W1D1_Tutorial8.ipynb
@@ -112,6 +112,36 @@
     "from pythia_datasets import DATASETS"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "d041a3d6-01af-42cc-bdc0-7e62eb272bc9",
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D1_T8\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -191,6 +221,20 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "6647e202-05cd-490c-b694-8ca6bad2ccdd",
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Climate_Feedbacks_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -213,14 +257,22 @@
     "\n",
     "link_id = \"zhb3c\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "09bb8a72-a965-4598-9b34-8341b293776f",
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Climate_Feedbacks_Slides\")"
    ]
   },
   {
@@ -447,7 +499,21 @@
     "2. In the Antarctic, they are roughly the same. In the Artic, there is more area with warmer SST in 2014.\n",
     "3. The ice-albedo feedback could be amplifying the ocean warming noted in Question 2. The polar regions examined here are the only places where waters can be cold enough to sustain sea ice. In a warming world where sea ice is melting, areas of the ocean that were once covered by reflective ice are replaced by darker water, which absorbs more sunlight, warms and hinders sea-ice growth.\n",
     "\n",
-    "\"\"\";"
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "a7722baa-1de1-4bc3-937c-398c43ecf953",
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_1_1\")"
    ]
   },
   {
diff --git a/tutorials/W1D1_ClimateSystemOverview/instructor/W1D1_Tutorial9.ipynb b/tutorials/W1D1_ClimateSystemOverview/instructor/W1D1_Tutorial9.ipynb
index 950d05ad2..1e6558a91 100644
--- a/tutorials/W1D1_ClimateSystemOverview/instructor/W1D1_Tutorial9.ipynb
+++ b/tutorials/W1D1_ClimateSystemOverview/instructor/W1D1_Tutorial9.ipynb
@@ -112,6 +112,36 @@
     "import matplotlib.pyplot as plt"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "07974de6-0957-45b3-9e77-895af3c459c8",
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D1_T9\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -191,6 +221,20 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "bf18fa96-f99f-420c-95aa-5b18704fac8a",
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Past_Present_Future_Climate_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -213,14 +257,22 @@
     "\n",
     "link_id = \"dtgax\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "6a5f6a63-2185-448e-9a94-104977794bb0",
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Past_Present_Future_Climate_Slides\")"
    ]
   },
   {
@@ -476,7 +528,21 @@
     "3. In the equatorial region, the grid cells are usually very similar in size. You could compute the weighted average and compare to be sure this is the case with our reanalysis product.\n",
     "\n",
     "These questions are just to get you thinking....note from this time series alone we can not attribute processes to the observed SST.\n",
-    "\"\"\";"
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "601b5358-8df2-4b1e-9576-bb5323d6b9ce",
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_3\")"
    ]
   },
   {
diff --git a/tutorials/W1D1_ClimateSystemOverview/solutions/W1D1_Tutorial4_Solution_6ce26e59.py b/tutorials/W1D1_ClimateSystemOverview/solutions/W1D1_Tutorial4_Solution_c61cf4b9.py
similarity index 99%
rename from tutorials/W1D1_ClimateSystemOverview/solutions/W1D1_Tutorial4_Solution_6ce26e59.py
rename to tutorials/W1D1_ClimateSystemOverview/solutions/W1D1_Tutorial4_Solution_c61cf4b9.py
index f5410960f..0d4b38acf 100644
--- a/tutorials/W1D1_ClimateSystemOverview/solutions/W1D1_Tutorial4_Solution_6ce26e59.py
+++ b/tutorials/W1D1_ClimateSystemOverview/solutions/W1D1_Tutorial4_Solution_c61cf4b9.py
@@ -1,4 +1,4 @@
 
 """
 1.  Upwelling is a process in which deep, cold water rises toward the surface. This can be identified in a sea surface temperature (SST) map as areas where the SST is colder than the surrounding waters. We note off the west coast of South America there is a 'tongue' of colder water from about -40 S northward. The strength of upwelling can often vary seasonally, and thus in our annual mean SST map above, the effects of this are likely more subtle.
-""";
\ No newline at end of file
+"""
\ No newline at end of file
diff --git a/tutorials/W1D1_ClimateSystemOverview/solutions/W1D1_Tutorial5_Solution_9cc68676.py b/tutorials/W1D1_ClimateSystemOverview/solutions/W1D1_Tutorial5_Solution_11d6af2a.py
similarity index 99%
rename from tutorials/W1D1_ClimateSystemOverview/solutions/W1D1_Tutorial5_Solution_9cc68676.py
rename to tutorials/W1D1_ClimateSystemOverview/solutions/W1D1_Tutorial5_Solution_11d6af2a.py
index 06a597c9a..c9548fffa 100644
--- a/tutorials/W1D1_ClimateSystemOverview/solutions/W1D1_Tutorial5_Solution_9cc68676.py
+++ b/tutorials/W1D1_ClimateSystemOverview/solutions/W1D1_Tutorial5_Solution_11d6af2a.py
@@ -3,4 +3,4 @@
 1. Generally the difference is negative in the Northern Hemisphere and positive in the Southern Hemisphere.
 2. The hemispheres have opposing signs, which is because of Earth's tilt and how it affects the timing of the seasons in each hemisphere (i.e. Northern Hemisphere summer is Southern Hemisphere winter). In the Northern Hemisphere, the difference is negative because the Northern Hemisphere July is warmer than the Northern Hemisphere January. In the Southern Hemisphere, the opposite is true.
 3. The ITCZ shifts with the seasons. When the Sun is directly overhead at the Northern Tropics (June), the ITCZ moves northwards, and when the Sun is directly overhead at the Southern Tropics (December), the ITCZ shifts southwards. This migration can affect the distribution of rain, leading to wet and dry seasons in many tropical regions.
-""";
\ No newline at end of file
+"""
\ No newline at end of file
diff --git a/tutorials/W1D1_ClimateSystemOverview/solutions/W1D1_Tutorial5_Solution_c7a854ea.py b/tutorials/W1D1_ClimateSystemOverview/solutions/W1D1_Tutorial5_Solution_79c64ee7.py
similarity index 99%
rename from tutorials/W1D1_ClimateSystemOverview/solutions/W1D1_Tutorial5_Solution_c7a854ea.py
rename to tutorials/W1D1_ClimateSystemOverview/solutions/W1D1_Tutorial5_Solution_79c64ee7.py
index b0d7cca95..05857ebeb 100644
--- a/tutorials/W1D1_ClimateSystemOverview/solutions/W1D1_Tutorial5_Solution_c7a854ea.py
+++ b/tutorials/W1D1_ClimateSystemOverview/solutions/W1D1_Tutorial5_Solution_79c64ee7.py
@@ -2,4 +2,4 @@
 """
 1. This location's strong seasonality suggests that it experiences significant seasonal changes in incoming solar radiation received at the surface over the course of a year.
 2. Seasonal variations in sea surface temperature (SST) would differ at different latitudes. At the equator, the seasonal variations in SST tend to be relatively small. This is because the equatorial region experiences a relatively constant amount of solar radiation throughout the year, resulting in a relatively stable SST. At the poles, however, the seasonal variations in SST are more pronounced. At 50ºS, the seasonal cycle would be opposite that shown here because the northern and southern hemispheres experience their seasons at different times of year (that is northern hemisphere summer is southern hemisphere winter).
-""";
\ No newline at end of file
+"""
\ No newline at end of file
diff --git a/tutorials/W1D1_ClimateSystemOverview/solutions/W1D1_Tutorial6_Solution_d05ad784.py b/tutorials/W1D1_ClimateSystemOverview/solutions/W1D1_Tutorial6_Solution_2f2d35e9.py
similarity index 99%
rename from tutorials/W1D1_ClimateSystemOverview/solutions/W1D1_Tutorial6_Solution_d05ad784.py
rename to tutorials/W1D1_ClimateSystemOverview/solutions/W1D1_Tutorial6_Solution_2f2d35e9.py
index 7ff90882b..0411190b8 100644
--- a/tutorials/W1D1_ClimateSystemOverview/solutions/W1D1_Tutorial6_Solution_d05ad784.py
+++ b/tutorials/W1D1_ClimateSystemOverview/solutions/W1D1_Tutorial6_Solution_2f2d35e9.py
@@ -2,4 +2,4 @@
 """
 1. An area-weighted mean global temperature anomaly provides a more accurate representation of global temperature changes by accounting for the uneven distribution of grid cell sizes across latitudes. It ensures each region's contribution to the global mean is proportional to its surface area, avoiding any disproportionate influence from smaller areas at higher latitudes. Both weighted and unweighted SST means show the similar increasing trend in temperature from 2000 to 2014, although by eye, it appears that the trend would be slightly lower for the unweighted mean.
 2. The observed SST warming trend from 2000 to 2014 is similar to the rate of change observed from 1980 to 2000, which fits into the larger context of the substantial warming trend observed over the past century. Over this period, global average temperatures have risen rapidly, at a rate that is not typical in the context of most longer-term naturally driven temperature variations.
-""";
\ No newline at end of file
+"""
\ No newline at end of file
diff --git a/tutorials/W1D1_ClimateSystemOverview/solutions/W1D1_Tutorial7_Solution_61f41a03.py b/tutorials/W1D1_ClimateSystemOverview/solutions/W1D1_Tutorial7_Solution_9e05e276.py
similarity index 99%
rename from tutorials/W1D1_ClimateSystemOverview/solutions/W1D1_Tutorial7_Solution_61f41a03.py
rename to tutorials/W1D1_ClimateSystemOverview/solutions/W1D1_Tutorial7_Solution_9e05e276.py
index 0d04814b9..4a0a3459b 100644
--- a/tutorials/W1D1_ClimateSystemOverview/solutions/W1D1_Tutorial7_Solution_61f41a03.py
+++ b/tutorials/W1D1_ClimateSystemOverview/solutions/W1D1_Tutorial7_Solution_9e05e276.py
@@ -2,4 +2,4 @@
 """
 1. In general, by examining the data at these different time scales, you can get a more comprehensive understanding of the SST variations and their potential causes.
 2. The original monthly data gives you the most granular view of the data, allowing you to see monthly variations in SST. Coarsening the data over 4-month periods reduces the temporal resolution but provides a slightly smoothed series that could help identify patterns or trends over this larger time period. A 6-month moving average could be useful for identifying semi-annual trends and reducing the impact of short-term noise in the data. The annually resampled (12 months) data provides a high-level view of the SST data, emphasizing the annual pattern. This can be useful for identifying long-term trends or changes in the data over the span of years.
-""";
\ No newline at end of file
+"""
\ No newline at end of file
diff --git a/tutorials/W1D1_ClimateSystemOverview/solutions/W1D1_Tutorial8_Solution_041d7c6d.py b/tutorials/W1D1_ClimateSystemOverview/solutions/W1D1_Tutorial8_Solution_0bc6741a.py
similarity index 99%
rename from tutorials/W1D1_ClimateSystemOverview/solutions/W1D1_Tutorial8_Solution_041d7c6d.py
rename to tutorials/W1D1_ClimateSystemOverview/solutions/W1D1_Tutorial8_Solution_0bc6741a.py
index 15e5a6ffe..20cebaa0c 100644
--- a/tutorials/W1D1_ClimateSystemOverview/solutions/W1D1_Tutorial8_Solution_041d7c6d.py
+++ b/tutorials/W1D1_ClimateSystemOverview/solutions/W1D1_Tutorial8_Solution_0bc6741a.py
@@ -4,4 +4,4 @@
 2. In the Antarctic, they are roughly the same. In the Artic, there is more area with warmer SST in 2014.
 3. The ice-albedo feedback could be amplifying the ocean warming noted in Question 2. The polar regions examined here are the only places where waters can be cold enough to sustain sea ice. In a warming world where sea ice is melting, areas of the ocean that were once covered by reflective ice are replaced by darker water, which absorbs more sunlight, warms and hinders sea-ice growth.
 
-""";
\ No newline at end of file
+"""
\ No newline at end of file
diff --git a/tutorials/W1D1_ClimateSystemOverview/solutions/W1D1_Tutorial9_Solution_bce23fae.py b/tutorials/W1D1_ClimateSystemOverview/solutions/W1D1_Tutorial9_Solution_ffe2e77d.py
similarity index 99%
rename from tutorials/W1D1_ClimateSystemOverview/solutions/W1D1_Tutorial9_Solution_bce23fae.py
rename to tutorials/W1D1_ClimateSystemOverview/solutions/W1D1_Tutorial9_Solution_ffe2e77d.py
index a66da5f2a..3ec9e9a2a 100644
--- a/tutorials/W1D1_ClimateSystemOverview/solutions/W1D1_Tutorial9_Solution_bce23fae.py
+++ b/tutorials/W1D1_ClimateSystemOverview/solutions/W1D1_Tutorial9_Solution_ffe2e77d.py
@@ -5,4 +5,4 @@
 3. In the equatorial region, the grid cells are usually very similar in size. You could compute the weighted average and compare to be sure this is the case with our reanalysis product.
 
 These questions are just to get you thinking....note from this time series alone we can not attribute processes to the observed SST.
-""";
\ No newline at end of file
+"""
\ No newline at end of file
diff --git a/tutorials/W1D1_ClimateSystemOverview/student/W1D1_Intro.ipynb b/tutorials/W1D1_ClimateSystemOverview/student/W1D1_Intro.ipynb
index 66fad600e..1c9aea835 100644
--- a/tutorials/W1D1_ClimateSystemOverview/student/W1D1_Intro.ipynb
+++ b/tutorials/W1D1_ClimateSystemOverview/student/W1D1_Intro.ipynb
@@ -46,6 +46,36 @@
     "3. Identify the main concepts covered in the course."
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "d8266b33-da1b-43a9-927f-ab629de4a10b",
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D1_Intro\""
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "452816ee",
@@ -123,6 +153,20 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "48f83cbb-fe30-4ed9-bfe2-c13792e81502",
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Climate_Solutions_Video\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "168f8f55",
@@ -148,14 +192,22 @@
     "\n",
     "link_id = \"ghmn5\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "f22cd6b1-37ca-4da3-9ea8-d2a4d65d3c1f",
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Climate_Solutions_Slides\")"
    ]
   }
  ],
diff --git a/tutorials/W1D1_ClimateSystemOverview/student/W1D1_Tutorial1.ipynb b/tutorials/W1D1_ClimateSystemOverview/student/W1D1_Tutorial1.ipynb
index 9900b2e00..06d916d75 100644
--- a/tutorials/W1D1_ClimateSystemOverview/student/W1D1_Tutorial1.ipynb
+++ b/tutorials/W1D1_ClimateSystemOverview/student/W1D1_Tutorial1.ipynb
@@ -243,14 +243,8 @@
     "\n",
     "link_id = \"4suf5\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
    ]
   },
   {
diff --git a/tutorials/W1D1_ClimateSystemOverview/student/W1D1_Tutorial2.ipynb b/tutorials/W1D1_ClimateSystemOverview/student/W1D1_Tutorial2.ipynb
index 7aa563fe4..13f0fcc7f 100644
--- a/tutorials/W1D1_ClimateSystemOverview/student/W1D1_Tutorial2.ipynb
+++ b/tutorials/W1D1_ClimateSystemOverview/student/W1D1_Tutorial2.ipynb
@@ -88,6 +88,35 @@
     "import matplotlib.pyplot as plt"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D1_T2\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -161,6 +190,19 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Solar_Radiation_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -182,14 +224,21 @@
     "\n",
     "link_id = \"gh5us\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Solar_Radiation_Slides\")"
    ]
   },
   {
@@ -380,6 +429,19 @@
     "\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Coding_Exercise_1_2\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
diff --git a/tutorials/W1D1_ClimateSystemOverview/student/W1D1_Tutorial3.ipynb b/tutorials/W1D1_ClimateSystemOverview/student/W1D1_Tutorial3.ipynb
index 14b137656..776b37426 100644
--- a/tutorials/W1D1_ClimateSystemOverview/student/W1D1_Tutorial3.ipynb
+++ b/tutorials/W1D1_ClimateSystemOverview/student/W1D1_Tutorial3.ipynb
@@ -105,6 +105,35 @@
     "import matplotlib.pyplot as plt"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D1_T3\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -191,6 +220,19 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Atmospheric_Climate_Systems_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -212,14 +254,21 @@
     "\n",
     "link_id = \"cnfwz\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Atmospheric_Climate_Systems_Slides\")"
    ]
   },
   {
@@ -320,6 +369,19 @@
     "\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_1\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -649,6 +711,19 @@
     "\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_2_2\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -717,6 +792,19 @@
     "\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_2_3\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
diff --git a/tutorials/W1D1_ClimateSystemOverview/student/W1D1_Tutorial4.ipynb b/tutorials/W1D1_ClimateSystemOverview/student/W1D1_Tutorial4.ipynb
index 64467a667..bc2912765 100644
--- a/tutorials/W1D1_ClimateSystemOverview/student/W1D1_Tutorial4.ipynb
+++ b/tutorials/W1D1_ClimateSystemOverview/student/W1D1_Tutorial4.ipynb
@@ -111,6 +111,36 @@
     "import matplotlib.pyplot as plt"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "754caab0-66fc-4e23-bd60-6de2ff7d3b0a",
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D1_T4\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -190,6 +220,20 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "65eb3752-2e77-4024-9f6e-6cdbd66337a5",
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Oceanic_Climate_Systems_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -212,14 +256,22 @@
     "\n",
     "link_id = \"hmqfr\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "bb3c61b6-544e-422a-be4c-ee7c6a2e2164",
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Oceanic_Climate_Systems_Slides\")"
    ]
   },
   {
@@ -540,10 +592,24 @@
     "tags": []
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D1_ClimateSystemOverview/solutions/W1D1_Tutorial4_Solution_6ce26e59.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D1_ClimateSystemOverview/solutions/W1D1_Tutorial4_Solution_c61cf4b9.py)\n",
     "\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "1115cecf-9d73-4ac1-a6d3-9425342dc642",
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_2\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "9ac2925a-9b96-4b0a-b2b6-24f6b4151d4c",
diff --git a/tutorials/W1D1_ClimateSystemOverview/student/W1D1_Tutorial5.ipynb b/tutorials/W1D1_ClimateSystemOverview/student/W1D1_Tutorial5.ipynb
index 909646042..c20f35f26 100644
--- a/tutorials/W1D1_ClimateSystemOverview/student/W1D1_Tutorial5.ipynb
+++ b/tutorials/W1D1_ClimateSystemOverview/student/W1D1_Tutorial5.ipynb
@@ -116,6 +116,36 @@
     "import matplotlib.pyplot as plt"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "2ad30cf1-5467-4010-ac68-5046fb316018",
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D1_T5\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -195,6 +225,20 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "a2371121-637e-4517-9db2-1c5faab01348",
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Terrestrial_Temperature_Rainfall_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -217,14 +261,22 @@
     "\n",
     "link_id = \"9z6km\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "c28bb25a-1852-4477-b932-41fdecbe42ef",
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Terrestrial_Temperature_Rainfall_Slides\")"
    ]
   },
   {
@@ -524,10 +576,24 @@
     "tags": []
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D1_ClimateSystemOverview/solutions/W1D1_Tutorial5_Solution_c7a854ea.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D1_ClimateSystemOverview/solutions/W1D1_Tutorial5_Solution_79c64ee7.py)\n",
     "\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "68b7485b-5ca4-47fd-8009-32376b4b5049",
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_1_2_1\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "d7c540b2-c707-4d51-8cc7-3ea51b8a505f",
@@ -611,7 +677,7 @@
     "execution": {}
    },
    "source": [
-    "#### Questions 1.2.1: Climate Connection\n",
+    "#### Questions 1.2.2: Climate Connection\n",
     "\n",
     "1. What patterns do you observe in this map?\n",
     "2. Why is there such an apparent difference between the Northern and Southern Hemisphere SST changes?\n",
@@ -627,10 +693,24 @@
     "tags": []
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D1_ClimateSystemOverview/solutions/W1D1_Tutorial5_Solution_9cc68676.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D1_ClimateSystemOverview/solutions/W1D1_Tutorial5_Solution_11d6af2a.py)\n",
     "\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "78e2905e-cb34-4ca0-b17a-2defe5ec0630",
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_1_2_2\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "ee5f2987-d7e3-4b0d-a5ad-abfae5a98072",
diff --git a/tutorials/W1D1_ClimateSystemOverview/student/W1D1_Tutorial6.ipynb b/tutorials/W1D1_ClimateSystemOverview/student/W1D1_Tutorial6.ipynb
index 1f09a8f34..59feb28de 100644
--- a/tutorials/W1D1_ClimateSystemOverview/student/W1D1_Tutorial6.ipynb
+++ b/tutorials/W1D1_ClimateSystemOverview/student/W1D1_Tutorial6.ipynb
@@ -104,6 +104,36 @@
     "import matplotlib.pyplot as plt"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "e05b62d2-e46f-4d85-af57-72213527248a",
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D1_T6\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -183,6 +213,20 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "93161e14-e3a3-4bf2-8448-ecd35e1ee7c8",
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Orbital_Cycles_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -205,14 +249,22 @@
     "\n",
     "link_id = \"tcb2q\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "ba94f7c9-1871-449d-ad5c-6a13612e7748",
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Orbital_Cycles_Slides\")"
    ]
   },
   {
@@ -497,10 +549,24 @@
     "tags": []
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D1_ClimateSystemOverview/solutions/W1D1_Tutorial6_Solution_d05ad784.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D1_ClimateSystemOverview/solutions/W1D1_Tutorial6_Solution_2f2d35e9.py)\n",
     "\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "96461dcd-f5b7-409a-bb95-da0c2600938e",
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_1\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "bbbe7478-dd54-4bb1-9e82-226a655a26d0",
diff --git a/tutorials/W1D1_ClimateSystemOverview/student/W1D1_Tutorial7.ipynb b/tutorials/W1D1_ClimateSystemOverview/student/W1D1_Tutorial7.ipynb
index 17e33f428..7a7fc198c 100644
--- a/tutorials/W1D1_ClimateSystemOverview/student/W1D1_Tutorial7.ipynb
+++ b/tutorials/W1D1_ClimateSystemOverview/student/W1D1_Tutorial7.ipynb
@@ -106,6 +106,36 @@
     "from pythia_datasets import DATASETS"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "21b5614e-3a3f-46d1-a926-283e9458da74",
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D1_T7\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -185,6 +215,20 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "43bfb42a-8ce6-44b6-9a88-6bca2000bd7e",
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Carbon_Cycle_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -207,14 +251,22 @@
     "\n",
     "link_id = \"sb3n5\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "3918492b-f1c5-4b8e-8479-748a1652f724",
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Carbon_Cycle_Slides\")"
    ]
   },
   {
@@ -497,10 +549,24 @@
     "tags": []
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D1_ClimateSystemOverview/solutions/W1D1_Tutorial7_Solution_61f41a03.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D1_ClimateSystemOverview/solutions/W1D1_Tutorial7_Solution_9e05e276.py)\n",
     "\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "b026c173-582c-48e1-8504-ef1c13acee9e",
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_1_4\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "c18bb57b-63f2-4f9d-ac8d-32d0231d02fa",
diff --git a/tutorials/W1D1_ClimateSystemOverview/student/W1D1_Tutorial8.ipynb b/tutorials/W1D1_ClimateSystemOverview/student/W1D1_Tutorial8.ipynb
index c55f7dc28..80d201ef9 100644
--- a/tutorials/W1D1_ClimateSystemOverview/student/W1D1_Tutorial8.ipynb
+++ b/tutorials/W1D1_ClimateSystemOverview/student/W1D1_Tutorial8.ipynb
@@ -112,6 +112,36 @@
     "from pythia_datasets import DATASETS"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "d041a3d6-01af-42cc-bdc0-7e62eb272bc9",
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D1_T8\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -191,6 +221,20 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "6647e202-05cd-490c-b694-8ca6bad2ccdd",
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Climate_Feedbacks_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -213,14 +257,22 @@
     "\n",
     "link_id = \"zhb3c\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "09bb8a72-a965-4598-9b34-8341b293776f",
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Climate_Feedbacks_Slides\")"
    ]
   },
   {
@@ -439,10 +491,24 @@
     "tags": []
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D1_ClimateSystemOverview/solutions/W1D1_Tutorial8_Solution_041d7c6d.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D1_ClimateSystemOverview/solutions/W1D1_Tutorial8_Solution_0bc6741a.py)\n",
     "\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "a7722baa-1de1-4bc3-937c-398c43ecf953",
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_1_1\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "4ce1373d-e4fc-437e-a445-13dd8fa5f22f",
diff --git a/tutorials/W1D1_ClimateSystemOverview/student/W1D1_Tutorial9.ipynb b/tutorials/W1D1_ClimateSystemOverview/student/W1D1_Tutorial9.ipynb
index 6e8109999..285167d7c 100644
--- a/tutorials/W1D1_ClimateSystemOverview/student/W1D1_Tutorial9.ipynb
+++ b/tutorials/W1D1_ClimateSystemOverview/student/W1D1_Tutorial9.ipynb
@@ -112,6 +112,36 @@
     "import matplotlib.pyplot as plt"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "07974de6-0957-45b3-9e77-895af3c459c8",
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D1_T9\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -191,6 +221,20 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "bf18fa96-f99f-420c-95aa-5b18704fac8a",
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Past_Present_Future_Climate_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -213,14 +257,22 @@
     "\n",
     "link_id = \"dtgax\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "6a5f6a63-2185-448e-9a94-104977794bb0",
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Past_Present_Future_Climate_Slides\")"
    ]
   },
   {
@@ -467,10 +519,24 @@
     "tags": []
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D1_ClimateSystemOverview/solutions/W1D1_Tutorial9_Solution_bce23fae.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D1_ClimateSystemOverview/solutions/W1D1_Tutorial9_Solution_ffe2e77d.py)\n",
     "\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "601b5358-8df2-4b1e-9576-bb5323d6b9ce",
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_3\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "5f6c15ba-b7d3-4ef9-a100-44057a2cefce",
diff --git a/tutorials/W1D2_Ocean-AtmosphereReanalysis/README.md b/tutorials/W1D2_Ocean-AtmosphereReanalysis/README.md
index 11db04e95..6763b1166 100644
--- a/tutorials/W1D2_Ocean-AtmosphereReanalysis/README.md
+++ b/tutorials/W1D2_Ocean-AtmosphereReanalysis/README.md
@@ -1,29 +1,29 @@
-# W1D2 - Stateofthe Climate Oceanand Atmosphere Reanalysis
+# W1D2 - Ocean- Atmosphere Reanalysis
 
 ## Instructor notebooks
 
 |   | Run | Run | View |
 | - | --- | --- | ---- |
-| Intro | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/W1D2_Intro.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/W1D2_Intro.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/W1D2_Intro.ipynb?flush_cache=true) |
-| Tutorial 1 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/instructor/W1D2_Tutorial1.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/instructor/W1D2_Tutorial1.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/instructor/W1D2_Tutorial1.ipynb?flush_cache=true) |
-| Tutorial 2 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/instructor/W1D2_Tutorial2.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/instructor/W1D2_Tutorial2.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/instructor/W1D2_Tutorial2.ipynb?flush_cache=true) |
-| Tutorial 3 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/instructor/W1D2_Tutorial3.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/instructor/W1D2_Tutorial3.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/instructor/W1D2_Tutorial3.ipynb?flush_cache=true) |
-| Tutorial 4 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/instructor/W1D2_Tutorial4.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/instructor/W1D2_Tutorial4.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/instructor/W1D2_Tutorial4.ipynb?flush_cache=true) |
-| Tutorial 5 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/instructor/W1D2_Tutorial5.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/instructor/W1D2_Tutorial5.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/instructor/W1D2_Tutorial5.ipynb?flush_cache=true) |
-| Tutorial 6 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/instructor/W1D2_Tutorial6.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/instructor/W1D2_Tutorial6.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/instructor/W1D2_Tutorial6.ipynb?flush_cache=true) |
-| Outro | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/W1D2_Outro.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/W1D2_Outro.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/W1D2_Outro.ipynb?flush_cache=true) |
+| Intro | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_Ocean-AtmosphereReanalysis/W1D2_Intro.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D2_Ocean-AtmosphereReanalysis/W1D2_Intro.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_Ocean-AtmosphereReanalysis/W1D2_Intro.ipynb?flush_cache=true) |
+| Tutorial 1 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_Ocean-AtmosphereReanalysis/instructor/W1D2_Tutorial1.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D2_Ocean-AtmosphereReanalysis/instructor/W1D2_Tutorial1.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_Ocean-AtmosphereReanalysis/instructor/W1D2_Tutorial1.ipynb?flush_cache=true) |
+| Tutorial 2 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_Ocean-AtmosphereReanalysis/instructor/W1D2_Tutorial2.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D2_Ocean-AtmosphereReanalysis/instructor/W1D2_Tutorial2.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_Ocean-AtmosphereReanalysis/instructor/W1D2_Tutorial2.ipynb?flush_cache=true) |
+| Tutorial 3 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_Ocean-AtmosphereReanalysis/instructor/W1D2_Tutorial3.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D2_Ocean-AtmosphereReanalysis/instructor/W1D2_Tutorial3.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_Ocean-AtmosphereReanalysis/instructor/W1D2_Tutorial3.ipynb?flush_cache=true) |
+| Tutorial 4 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_Ocean-AtmosphereReanalysis/instructor/W1D2_Tutorial4.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D2_Ocean-AtmosphereReanalysis/instructor/W1D2_Tutorial4.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_Ocean-AtmosphereReanalysis/instructor/W1D2_Tutorial4.ipynb?flush_cache=true) |
+| Tutorial 5 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_Ocean-AtmosphereReanalysis/instructor/W1D2_Tutorial5.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D2_Ocean-AtmosphereReanalysis/instructor/W1D2_Tutorial5.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_Ocean-AtmosphereReanalysis/instructor/W1D2_Tutorial5.ipynb?flush_cache=true) |
+| Tutorial 6 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_Ocean-AtmosphereReanalysis/instructor/W1D2_Tutorial6.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D2_Ocean-AtmosphereReanalysis/instructor/W1D2_Tutorial6.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_Ocean-AtmosphereReanalysis/instructor/W1D2_Tutorial6.ipynb?flush_cache=true) |
+| Outro | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_Ocean-AtmosphereReanalysis/W1D2_Outro.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D2_Ocean-AtmosphereReanalysis/W1D2_Outro.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_Ocean-AtmosphereReanalysis/W1D2_Outro.ipynb?flush_cache=true) |
 
 
 ## Student notebooks
 
 |   | Run | Run | View |
 | - | --- | --- | ---- |
-| Intro | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/W1D2_Intro.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/W1D2_Intro.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/W1D2_Intro.ipynb?flush_cache=true) |
-| Tutorial 1 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/student/W1D2_Tutorial1.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/student/W1D2_Tutorial1.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/student/W1D2_Tutorial1.ipynb?flush_cache=true) |
-| Tutorial 2 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/student/W1D2_Tutorial2.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/student/W1D2_Tutorial2.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/student/W1D2_Tutorial2.ipynb?flush_cache=true) |
-| Tutorial 3 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/student/W1D2_Tutorial3.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/student/W1D2_Tutorial3.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/student/W1D2_Tutorial3.ipynb?flush_cache=true) |
-| Tutorial 4 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/student/W1D2_Tutorial4.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/student/W1D2_Tutorial4.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/student/W1D2_Tutorial4.ipynb?flush_cache=true) |
-| Tutorial 5 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/student/W1D2_Tutorial5.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/student/W1D2_Tutorial5.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/student/W1D2_Tutorial5.ipynb?flush_cache=true) |
-| Tutorial 6 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/student/W1D2_Tutorial6.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/student/W1D2_Tutorial6.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/student/W1D2_Tutorial6.ipynb?flush_cache=true) |
-| Outro | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/W1D2_Outro.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/W1D2_Outro.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/W1D2_Outro.ipynb?flush_cache=true) |
+| Intro | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_Ocean-AtmosphereReanalysis/W1D2_Intro.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D2_Ocean-AtmosphereReanalysis/W1D2_Intro.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_Ocean-AtmosphereReanalysis/W1D2_Intro.ipynb?flush_cache=true) |
+| Tutorial 1 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_Ocean-AtmosphereReanalysis/student/W1D2_Tutorial1.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D2_Ocean-AtmosphereReanalysis/student/W1D2_Tutorial1.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_Ocean-AtmosphereReanalysis/student/W1D2_Tutorial1.ipynb?flush_cache=true) |
+| Tutorial 2 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_Ocean-AtmosphereReanalysis/student/W1D2_Tutorial2.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D2_Ocean-AtmosphereReanalysis/student/W1D2_Tutorial2.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_Ocean-AtmosphereReanalysis/student/W1D2_Tutorial2.ipynb?flush_cache=true) |
+| Tutorial 3 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_Ocean-AtmosphereReanalysis/student/W1D2_Tutorial3.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D2_Ocean-AtmosphereReanalysis/student/W1D2_Tutorial3.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_Ocean-AtmosphereReanalysis/student/W1D2_Tutorial3.ipynb?flush_cache=true) |
+| Tutorial 4 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_Ocean-AtmosphereReanalysis/student/W1D2_Tutorial4.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D2_Ocean-AtmosphereReanalysis/student/W1D2_Tutorial4.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_Ocean-AtmosphereReanalysis/student/W1D2_Tutorial4.ipynb?flush_cache=true) |
+| Tutorial 5 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_Ocean-AtmosphereReanalysis/student/W1D2_Tutorial5.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D2_Ocean-AtmosphereReanalysis/student/W1D2_Tutorial5.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_Ocean-AtmosphereReanalysis/student/W1D2_Tutorial5.ipynb?flush_cache=true) |
+| Tutorial 6 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_Ocean-AtmosphereReanalysis/student/W1D2_Tutorial6.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D2_Ocean-AtmosphereReanalysis/student/W1D2_Tutorial6.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_Ocean-AtmosphereReanalysis/student/W1D2_Tutorial6.ipynb?flush_cache=true) |
+| Outro | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_Ocean-AtmosphereReanalysis/W1D2_Outro.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D2_Ocean-AtmosphereReanalysis/W1D2_Outro.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D2_Ocean-AtmosphereReanalysis/W1D2_Outro.ipynb?flush_cache=true) |
 
diff --git a/tutorials/W1D2_Ocean-AtmosphereReanalysis/W1D2_Intro.ipynb b/tutorials/W1D2_Ocean-AtmosphereReanalysis/W1D2_Intro.ipynb
index 834c3610e..cb121725f 100644
--- a/tutorials/W1D2_Ocean-AtmosphereReanalysis/W1D2_Intro.ipynb
+++ b/tutorials/W1D2_Ocean-AtmosphereReanalysis/W1D2_Intro.ipynb
@@ -70,7 +70,10 @@
    "cell_type": "code",
    "execution_count": null,
    "id": "cda25c98-a47f-403b-8aeb-d2d34e3c0f8e",
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Install and import feedback gadget\n",
@@ -175,7 +178,10 @@
    "cell_type": "code",
    "execution_count": null,
    "id": "d1cd2985-22ed-4de3-8f2d-e825f18433e8",
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -215,7 +221,10 @@
    "cell_type": "code",
    "execution_count": null,
    "id": "5492dc34-28d1-47ef-bc82-609b4b208424",
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -250,7 +259,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.18"
+   "version": "3.9.19"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/W1D2_Ocean-AtmosphereReanalysis/W1D2_Tutorial1.ipynb b/tutorials/W1D2_Ocean-AtmosphereReanalysis/W1D2_Tutorial1.ipynb
index 78c58f523..ab0247743 100644
--- a/tutorials/W1D2_Ocean-AtmosphereReanalysis/W1D2_Tutorial1.ipynb
+++ b/tutorials/W1D2_Ocean-AtmosphereReanalysis/W1D2_Tutorial1.ipynb
@@ -85,6 +85,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": [
      "colab"
     ]
@@ -101,7 +102,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# imports\n",
@@ -116,7 +119,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Install and import feedback gadget\n",
@@ -143,7 +149,8 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "form"
+    "cellView": "form",
+    "execution": {}
    },
    "outputs": [],
    "source": [
@@ -161,6 +168,7 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -225,7 +233,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -237,6 +248,7 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
+    "execution": {},
     "pycharm": {
      "name": "#%%\n"
     },
@@ -259,7 +271,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -353,6 +368,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 5921,
      "status": "ok",
@@ -400,6 +416,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 5137,
      "status": "ok",
@@ -471,7 +488,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# a bit more complicated code that allows interactive plots\n",
@@ -520,6 +539,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -551,6 +571,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 842,
      "status": "ok",
@@ -582,6 +603,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 492,
      "status": "ok",
@@ -617,7 +639,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# SST in just the Niño 3.4 region\n",
@@ -637,6 +661,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 797,
      "status": "ok",
@@ -707,7 +732,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# again more complicated code that allows interactive plots\n",
@@ -758,7 +785,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# group the dataset by month\n",
@@ -800,7 +829,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# smooth using a centered 3 month running mean\n",
@@ -811,6 +842,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 975,
      "status": "ok",
@@ -883,6 +915,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 1326,
      "status": "ok",
@@ -964,7 +997,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# to_remove explanation\n",
@@ -979,7 +1014,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -1042,7 +1080,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.18"
+   "version": "3.9.19"
   },
   "toc-autonumbering": false,
   "toc-showcode": false,
diff --git a/tutorials/W1D2_Ocean-AtmosphereReanalysis/W1D2_Tutorial2.ipynb b/tutorials/W1D2_Ocean-AtmosphereReanalysis/W1D2_Tutorial2.ipynb
index 11eaa6e29..1641eb2ef 100644
--- a/tutorials/W1D2_Ocean-AtmosphereReanalysis/W1D2_Tutorial2.ipynb
+++ b/tutorials/W1D2_Ocean-AtmosphereReanalysis/W1D2_Tutorial2.ipynb
@@ -64,6 +64,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": [
      "colab"
     ]
@@ -80,7 +81,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "import cdsapi\n",
@@ -105,7 +108,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Install and import feedback gadget\n",
@@ -132,7 +138,8 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "form"
+    "cellView": "form",
+    "execution": {}
    },
    "outputs": [],
    "source": [
@@ -160,6 +167,7 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -178,6 +186,7 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -233,7 +242,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -269,7 +281,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# load data: 5 variables of ERA5 reanalysis, subregion, hourly, March 2018\n",
@@ -281,7 +295,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "ERA5_allvars"
@@ -324,7 +340,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# compute ten-meter wind speed, the magnitude of the wind vector\n",
@@ -353,7 +371,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "ds_surface_temp_2m = ERA5_allvars.t2m\n",
@@ -372,7 +392,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "holoviews.extension(\"bokeh\")\n",
@@ -415,6 +437,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -427,6 +450,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -452,7 +476,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# average temperatures over the whole day after grouping by the day\n",
@@ -462,7 +488,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# interactive plot of daily frequency of surface temperature\n",
@@ -497,7 +525,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# to_remove explanation\n",
@@ -510,7 +540,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -538,6 +571,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -553,7 +587,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# plot the time series of surface temperature\n",
@@ -583,7 +619,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# to_remove explanation\n",
@@ -597,7 +635,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -618,7 +659,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "ERA5_allvars_ts = ERA5_allvars.weighted(weights).mean([\"longitude\", \"latitude\"])\n",
@@ -628,7 +671,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "plot_vars = [\n",
@@ -669,7 +714,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# to_remove explanation\n",
@@ -684,7 +731,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -744,7 +794,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.18"
+   "version": "3.9.19"
   },
   "toc-autonumbering": true
  },
diff --git a/tutorials/W1D2_Ocean-AtmosphereReanalysis/W1D2_Tutorial3.ipynb b/tutorials/W1D2_Ocean-AtmosphereReanalysis/W1D2_Tutorial3.ipynb
index bb690544a..12568a593 100644
--- a/tutorials/W1D2_Ocean-AtmosphereReanalysis/W1D2_Tutorial3.ipynb
+++ b/tutorials/W1D2_Ocean-AtmosphereReanalysis/W1D2_Tutorial3.ipynb
@@ -65,6 +65,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": [
      "colab"
     ]
@@ -79,7 +80,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "import matplotlib.pyplot as plt\n",
@@ -99,7 +102,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Install and import feedback gadget\n",
@@ -126,7 +132,8 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "form"
+    "cellView": "form",
+    "execution": {}
    },
    "outputs": [],
    "source": [
@@ -178,7 +185,8 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "form"
+    "cellView": "form",
+    "execution": {}
    },
    "outputs": [],
    "source": [
@@ -205,7 +213,8 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "form"
+    "cellView": "form",
+    "execution": {}
    },
    "outputs": [],
    "source": [
@@ -223,6 +232,7 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -278,7 +288,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -290,6 +303,7 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
+    "execution": {},
     "pycharm": {
      "name": "#%%\n"
     },
@@ -312,7 +326,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -374,7 +391,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# note this can take a few minutes to download\n",
@@ -399,7 +418,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# take the temporal mean over 26 years (Jan 1980 - Dec 2005)\n",
@@ -409,7 +430,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "ERA5_mean"
@@ -428,6 +451,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -481,7 +505,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "#################################################\n",
@@ -506,7 +532,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# to_remove solution\n",
@@ -542,7 +570,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -563,7 +594,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# to_remove explanation\n",
@@ -576,7 +609,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -597,7 +633,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "fig, ax = plt.subplots()\n",
@@ -649,7 +687,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# to_remove explanation\n",
@@ -662,7 +702,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -687,7 +730,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# Note how we use several commands in one line.\n",
@@ -700,7 +745,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# Have a look at our new dataset, which incorporates the zonal mean and the temporal mean of every month\n",
@@ -723,7 +770,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# plot the zonal wind component of the wind vector\n",
@@ -759,7 +808,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# select the variable of interest and plot it with xarray's plotting method\n",
@@ -769,7 +820,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# to_remove solution\n",
@@ -796,7 +849,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -836,7 +892,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# select the variable of interest, group the data by season, and average over all seasons.\n",
@@ -848,7 +906,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# to_remove solution\n",
@@ -861,7 +921,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -871,7 +934,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "ERA5_season_u10"
@@ -880,7 +945,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "var='u10'\n",
@@ -911,7 +978,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# to_remove solution\n",
@@ -949,7 +1018,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -1027,7 +1099,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.18"
+   "version": "3.9.19"
   },
   "toc-autonumbering": true
  },
diff --git a/tutorials/W1D2_Ocean-AtmosphereReanalysis/W1D2_Tutorial4.ipynb b/tutorials/W1D2_Ocean-AtmosphereReanalysis/W1D2_Tutorial4.ipynb
index 94649902b..882d3e2df 100644
--- a/tutorials/W1D2_Ocean-AtmosphereReanalysis/W1D2_Tutorial4.ipynb
+++ b/tutorials/W1D2_Ocean-AtmosphereReanalysis/W1D2_Tutorial4.ipynb
@@ -66,6 +66,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": [
      "colab"
     ]
@@ -80,7 +81,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "import matplotlib.pyplot as plt\n",
@@ -98,7 +101,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Install and import feedback gadget\n",
@@ -125,7 +131,8 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "form"
+    "cellView": "form",
+    "execution": {}
    },
    "outputs": [],
    "source": [
@@ -152,7 +159,8 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "form"
+    "cellView": "form",
+    "execution": {}
    },
    "outputs": [],
    "source": [
@@ -170,6 +178,7 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -225,7 +234,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -237,6 +249,7 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
+    "execution": {},
     "pycharm": {
      "name": "#%%\n"
     },
@@ -259,7 +272,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -291,7 +307,8 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "both"
+    "cellView": "both",
+    "execution": {}
    },
    "outputs": [],
    "source": [
@@ -306,7 +323,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# wind in north/south direction labeled here as 'v'\n",
@@ -319,7 +338,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# load data: oceanic surface current from ECCO\n",
@@ -335,7 +356,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# current in east/west direction labeled here as 'v'\n",
@@ -363,7 +386,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "atm_wind_u.time"
@@ -383,7 +408,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# to_remove explanation\n",
@@ -397,7 +424,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -421,7 +451,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# compute the annual mean of atm_wind_u\n",
@@ -432,7 +464,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# take the annual mean of atm_wind_stress_v\n",
@@ -464,7 +498,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "fname_surface_temp = \"surface_theta.nc\"\n",
@@ -478,7 +514,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# longitude ad latitude coordinates for plotting\n",
@@ -537,6 +575,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -549,7 +588,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# take the annual mean of ocn_surface_current_v\n",
@@ -569,7 +610,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# longitude ad latitude coordinates for plotting\n",
@@ -638,7 +681,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# to_remove explanation\n",
@@ -652,7 +697,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -721,7 +769,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.18"
+   "version": "3.9.19"
   },
   "toc-autonumbering": true
  },
diff --git a/tutorials/W1D2_Ocean-AtmosphereReanalysis/W1D2_Tutorial5.ipynb b/tutorials/W1D2_Ocean-AtmosphereReanalysis/W1D2_Tutorial5.ipynb
index aeb789442..497823779 100644
--- a/tutorials/W1D2_Ocean-AtmosphereReanalysis/W1D2_Tutorial5.ipynb
+++ b/tutorials/W1D2_Ocean-AtmosphereReanalysis/W1D2_Tutorial5.ipynb
@@ -61,6 +61,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": [
      "colab"
     ]
@@ -79,6 +80,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 2058,
      "status": "error",
@@ -108,7 +110,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Install and import feedback gadget\n",
@@ -135,7 +140,8 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "form"
+    "cellView": "form",
+    "execution": {}
    },
    "outputs": [],
    "source": [
@@ -162,7 +168,8 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "form"
+    "cellView": "form",
+    "execution": {}
    },
    "outputs": [],
    "source": [
@@ -180,6 +187,7 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -235,7 +243,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -247,6 +258,7 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
+    "execution": {},
     "pycharm": {
      "name": "#%%\n"
     },
@@ -269,7 +281,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -296,7 +311,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# import preprocessed ecco data. This is surface data of monthly resolution over the period 2014 to 2016.\n",
@@ -311,7 +328,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# load salinity\n",
@@ -325,7 +344,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# make land points NaN (not a number)\n",
@@ -340,7 +361,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# plot Sea Surface Temprature - similar to plots we used in tutorials 2+3\n",
@@ -386,7 +409,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# plot Sea Surface Salinity\n",
@@ -463,7 +488,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "rho_linear = 1027 * (\n",
@@ -475,7 +502,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# plot linearized density\n",
@@ -519,7 +548,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "CT = gsw.CT_from_pt(\n",
@@ -531,7 +562,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# plot density from full nonlinear equation\n",
@@ -564,7 +597,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# plot difference between linear and non-linear equations of state\n",
@@ -622,7 +657,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# to_remove explanation\n",
@@ -636,7 +673,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -694,7 +734,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.18"
+   "version": "3.9.19"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/W1D2_Ocean-AtmosphereReanalysis/W1D2_Tutorial6.ipynb b/tutorials/W1D2_Ocean-AtmosphereReanalysis/W1D2_Tutorial6.ipynb
index 705df059d..0497dbaf4 100644
--- a/tutorials/W1D2_Ocean-AtmosphereReanalysis/W1D2_Tutorial6.ipynb
+++ b/tutorials/W1D2_Ocean-AtmosphereReanalysis/W1D2_Tutorial6.ipynb
@@ -66,6 +66,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": [
      "colab"
     ]
@@ -81,7 +82,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "import xarray as xr\n",
@@ -97,7 +100,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Install and import feedback gadget\n",
@@ -124,7 +130,8 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "form"
+    "cellView": "form",
+    "execution": {}
    },
    "outputs": [],
    "source": [
@@ -151,7 +158,8 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "form"
+    "cellView": "form",
+    "execution": {}
    },
    "outputs": [],
    "source": [
@@ -169,6 +177,7 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -226,6 +235,7 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
+    "execution": {},
     "pycharm": {
      "name": "#%%\n"
     },
@@ -261,7 +271,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# import preprocessed ECCO data. This data is full depth temperature data over 1992 to 2016 (annual mean)\n",
@@ -289,7 +301,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# Quick plot of the ocean temperature in Kelvin\n",
@@ -310,7 +324,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# take the temporal mean over the period 1992 to 1994\n",
@@ -332,7 +348,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# plot the zonal mean section of this data\n",
@@ -372,7 +390,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "theta_area_int = (\n",
@@ -383,7 +403,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# define reference density of salt water and the specific heat capacity\n",
@@ -438,7 +460,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "area_of_ocean = (\n",
@@ -468,7 +492,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# to_remove explanation\n",
@@ -481,7 +507,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -511,7 +540,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# this cell may take a while to run!\n",
@@ -593,7 +624,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "fig, ax = plt.subplots()\n",
@@ -634,7 +667,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# to_remove explanation\n",
@@ -647,7 +682,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -675,7 +713,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# first let's plot where heat is stored in the mean\n",
@@ -729,7 +769,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# we already defined an object that's the mean over years 1992 to 1994 (subset_theta)\n",
@@ -757,7 +799,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# plot 2 maps to compare changes in heat content in those two layers\n",
@@ -876,7 +920,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.18"
+   "version": "3.9.19"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/W1D2_Ocean-AtmosphereReanalysis/get_ERA5_reanalysis_data.ipynb b/tutorials/W1D2_Ocean-AtmosphereReanalysis/get_ERA5_reanalysis_data.ipynb
index 863ea5f05..e25f38e1b 100644
--- a/tutorials/W1D2_Ocean-AtmosphereReanalysis/get_ERA5_reanalysis_data.ipynb
+++ b/tutorials/W1D2_Ocean-AtmosphereReanalysis/get_ERA5_reanalysis_data.ipynb
@@ -3,7 +3,9 @@
   {
    "cell_type": "markdown",
    "id": "0ea0e24d-c94e-4564-a259-c397aa887e91",
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "source": [
     "# Load ERA5 Reanalysis Data via the CDS API\n",
     "\n",
@@ -25,7 +27,9 @@
   {
    "cell_type": "markdown",
    "id": "6d2e6e35-1965-439d-97aa-0608dd46a3bc",
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "source": [
     "## Prerequisites\n",
     "\n",
@@ -36,7 +40,9 @@
    "cell_type": "code",
    "execution_count": null,
    "id": "a4cf01ac-f46f-45da-b6fe-0e1701200ff0",
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# Import the Copernicus cdsapi package\n",
@@ -46,7 +52,9 @@
   {
    "cell_type": "markdown",
    "id": "1d1066cf-f252-48c9-bd87-0a54c7e0fbf0",
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "source": [
     " We now retrieve the data by choosing a data set, i.e. ```reanalysis-era5-single-levels```;\n",
     " our variables of interest\n",
@@ -70,7 +78,9 @@
    "cell_type": "code",
    "execution_count": null,
    "id": "45b705ae-9933-4f4c-a3dc-3548f8a41594",
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "c = cdsapi.Client()\n",
@@ -121,7 +131,9 @@
    "cell_type": "code",
    "execution_count": null,
    "id": "301328d1-cf3c-47d4-8191-dbd4bcc498a9",
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# We follow https://confluence.ecmwf.int/display/CKB/How+to+download+ERA5 after Signing up for CDS via"
@@ -130,7 +142,9 @@
   {
    "cell_type": "markdown",
    "id": "a627e3ca-37b4-4a64-a841-b1d0f411856c",
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "source": [
     "## Selecting a Different Spatial Region\n",
     "\n",
@@ -145,7 +159,9 @@
   {
    "cell_type": "markdown",
    "id": "875cfd11-cce0-4e84-9744-192f7a3765f9",
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "source": [
     "## Helpful resources\n",
     "\n",
@@ -166,6 +182,17 @@
   }
  ],
  "metadata": {
+  "colab": {
+   "collapsed_sections": [],
+   "include_colab_link": true,
+   "name": "get_ERA5_reanalysis_data",
+   "toc_visible": true
+  },
+  "kernel": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
   "kernelspec": {
    "display_name": "Python 3 (ipykernel)",
    "language": "python",
@@ -181,7 +208,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.18"
+   "version": "3.9.19"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/W1D2_Ocean-AtmosphereReanalysis/instructor/W1D2_Intro.ipynb b/tutorials/W1D2_Ocean-AtmosphereReanalysis/instructor/W1D2_Intro.ipynb
index d0af197bf..4f0cffb3b 100644
--- a/tutorials/W1D2_Ocean-AtmosphereReanalysis/instructor/W1D2_Intro.ipynb
+++ b/tutorials/W1D2_Ocean-AtmosphereReanalysis/instructor/W1D2_Intro.ipynb
@@ -66,6 +66,36 @@
     "3. Analyze ocean and atmosphere reanalysis products on different spatial and temporal scales."
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "cda25c98-a47f-403b-8aeb-d2d34e3c0f8e",
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D2_Intro\""
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "a79a31b2",
@@ -144,6 +174,20 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "d1cd2985-22ed-4de3-8f2d-e825f18433e8",
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Oceans_in_Climate_Video\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "8249df54",
@@ -169,14 +213,22 @@
     "\n",
     "link_id = \"2pxs6\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "5492dc34-28d1-47ef-bc82-609b4b208424",
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Oceans_in_Climate_Slides\")"
    ]
   }
  ],
diff --git a/tutorials/W1D2_Ocean-AtmosphereReanalysis/instructor/W1D2_Tutorial1.ipynb b/tutorials/W1D2_Ocean-AtmosphereReanalysis/instructor/W1D2_Tutorial1.ipynb
index f1b3ec903..c06d0cb3f 100644
--- a/tutorials/W1D2_Ocean-AtmosphereReanalysis/instructor/W1D2_Tutorial1.ipynb
+++ b/tutorials/W1D2_Ocean-AtmosphereReanalysis/instructor/W1D2_Tutorial1.ipynb
@@ -125,13 +125,24 @@
    },
    "outputs": [],
    "source": [
-    "# @title Figure Settings\n",
-    "import ipywidgets as widgets  # interactive display\n",
+    "# @title Install and import feedback gadget\n",
     "\n",
-    "%config InlineBackend.figure_format = 'retina'\n",
-    "plt.style.use(\n",
-    "    \"https://raw.githubusercontent.com/neuromatch/climate-course-content/main/cma.mplstyle\"\n",
-    ")"
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D2_T1\""
    ]
   },
   {
@@ -219,6 +230,19 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_ENSO_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -240,14 +264,21 @@
     "\n",
     "link_id = \"t65v8\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_ENSO_Slides\")"
    ]
   },
   {
@@ -436,21 +467,6 @@
     "</details>"
    ]
   },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "execution": {}
-   },
-   "source": [
-    "<details>\n",
-    "<summary><font color='orangered'>Click here for a description of the plot  </font></summary>\n",
-    "A map plot showing the sea surface temperature (SST) in January 2000 ranging from -2°C to 30°C from the CESM Earth system model's historical simulation for the Sixth Phase of the Coupled Intercomparison Project (CMIP6). Equatorial regions show the warmest temperatures, and polar regions the lowest. A few larger patterns indicate that more than just the latitude is important to create the spatial SST distribution.\n",
-    "\n",
-    "*** \n",
-    "\n",
-    "</details>"
-   ]
-  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -508,21 +524,6 @@
     "</details>"
    ]
   },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "execution": {}
-   },
-   "source": [
-    "<details>\n",
-    "<summary><font color='orangered'>Click here for a description of the plot  </font></summary>\n",
-    "An interactive map plot showing the sea surface temperature (SST) from January 2000 until October 2000  ranging from -2°C to 30°C from the CESM Earth system model's historical simulation for the Sixth Phase of the Coupled Intercomparison Project (CMIP6). Over the annual cycle, the warm and cold SST regions shift depending on the solar input. A few larger patterns indicate that more than just the latitude is important to create the spatial SST distribution, e.g. the equatorial pacific shows a cooler SST trench over the entire year compared to the surrounding subtropical waters.\n",
-    "\n",
-    "*** \n",
-    "\n",
-    "</details>"
-   ]
-  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -770,81 +771,6 @@
     "</details>"
    ]
   },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "execution": {}
-   },
-   "source": [
-    "<details>\n",
-    "<summary><font color='orangered'>Click here for a description of the plot  </font></summary>\n",
-    "A map plot zoomed into the Pacific Ocean showing the sea surface temperature (SST) in the Niño3.4 region in January 2000 ranging from -2°C to 30°C from the CESM Earth system models historical simulation for the Sixth Phase of the Coupled Intercomparison Project (CMIP6). The closer to the equator, the colder the water masses at the surface caused by upwelling from below induced by easterly winds and consequent Ekman transport.\n",
-    "\n",
-    "*** \n",
-    "\n",
-    "</details>"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "execution": {}
-   },
-   "source": [
-    "### Interactive Demo 2.2"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "execution": {}
-   },
-   "source": [
-    "Below we plot an interactive version of the Niño 3.4 region. You can explore the data by zooming in with the tools from the righthand toolbar and visualize what the next few time steps look like in the model by using the interactive slider bar on the most right. Note that the color bar and the corresponding SST scale have changed to make the changing pattern more visible. \n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
-   "outputs": [],
-   "source": [
-    "# again more complicated code that allows interactive plots\n",
-    "gv.extension(\"bokeh\")  # load Bokeh\n",
-    "dataset_plot = gv.Dataset(\n",
-    "    ds_SST.where(\n",
-    "    (ds_SST.lat > -5) & (ds_SST.lat < 5) & (ds_SST.lon > 190) & (ds_SST.lon < 240)\n",
-    ").isel(time=slice(0, 10))\n",
-    ")  # slice only the first 10 timepoint, as it is a time consuming task\n",
-    "images = dataset_plot.to(gv.Image, [\"longitude\", \"latitude\"], \"tos\", \"time\")\n",
-    "# aesthetics\n",
-    "images.opts(\n",
-    "    cmap=\"coolwarm\",\n",
-    "    colorbar=True,\n",
-    "    width=600,\n",
-    "    height=400,\n",
-    "    projection=ccrs.Robinson(central_longitude=180),\n",
-    "    clabel=\"Sea Surface Temperature [˚C]\",\n",
-    ") * gf.coastline"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "execution": {}
-   },
-   "source": [
-    "<details>\n",
-    "<summary><font color='orangered'>Click here for a description of the plot  </font></summary>\n",
-    "An interactive map plot showing the sea surface temperature (SST) from January 2000 until October 2000  ranging from 23.5°C to 30.5°C from the CESM Earth system model's historical simulation for the Sixth Phase of the Coupled Intercomparison Project (CMIP6). Over the annual cycle, the SST increases in the northern hemispherical summer. The closer to the equator, the colder the water masses at the surface caused by upwelling induced by easterly winds and consequent Ekman transport. The more west in the region the warmer the water masses also caused by this transport.\n",
-    "\n",
-    "*** \n",
-    "\n",
-    "</details>"
-   ]
-  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -1085,6 +1011,19 @@
     "\"\"\""
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_3\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
diff --git a/tutorials/W1D2_Ocean-AtmosphereReanalysis/instructor/W1D2_Tutorial2.ipynb b/tutorials/W1D2_Ocean-AtmosphereReanalysis/instructor/W1D2_Tutorial2.ipynb
index c507e4052..7ec12f1f7 100644
--- a/tutorials/W1D2_Ocean-AtmosphereReanalysis/instructor/W1D2_Tutorial2.ipynb
+++ b/tutorials/W1D2_Ocean-AtmosphereReanalysis/instructor/W1D2_Tutorial2.ipynb
@@ -105,6 +105,35 @@
     "warnings.filterwarnings('ignore')"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D2_T2\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -152,25 +181,6 @@
     ")"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "cellView": "form",
-    "execution": {},
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "# @title Figure Settings\n",
-    "import ipywidgets as widgets  # interactive display\n",
-    "\n",
-    "%config InlineBackend.figure_format = 'retina'\n",
-    "plt.style.use(\n",
-    "    \"https://raw.githubusercontent.com/neuromatch/climate-course-content/main/cma.mplstyle\"\n",
-    ")"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -229,6 +239,19 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_ECMWF_Reanalysis_Video\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -250,7 +273,7 @@
    "source": [
     "## Section 1.1: Accessing ERA5 Data\n",
     "\n",
-    "You will access the data through our OSF cloud storage to simplify the downloading process. If you are keen to download the data yourself or are simply interested in exploring other variables, please have a look into the ```get_ERA5_reanalysis_data.ipynb``` notebook, where we use the Climate Data Store (CDS) API to get a subset of the huge [ECMWF ERA5 Reanalysis](https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-single-levels?tab=overview) data set.\n",
+    "You will access the data through our OSF cloud storage to simplify the downloading process. If you are keen to download the data yourself or are simply interested in exploring other variables, please have a look into the [```get_ERA5_reanalysis_data.ipynb```](https://github.com/neuromatch/climate-course-content/blob/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/get_ERA5_reanalysis_data.ipynb) notebook, where we use the Climate Data Store (CDS) API to get a subset of the huge [ECMWF ERA5 Reanalysis](https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-single-levels?tab=overview) data set.\n",
     "\n",
     "Let's select a specific year and month to work with, March of 2018:"
    ]
@@ -462,45 +485,6 @@
     "ds_surface_temp_2m_day = ds_surface_temp_2m.groupby(\"time.day\").mean()"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "execution": {},
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "# interactive plot of hourly frequency of surface temperature\n",
-    "# this cell may take a little longer as it contains several maps in a single plotting function\n",
-    "dataset_plot = gv.Dataset(\n",
-    "    ds_surface_temp_2m_hour.isel(hour=slice(0, 12))\n",
-    ")  # only the first 12 time steps (midnight to noon), as it is a time-consuming task\n",
-    "images = dataset_plot.to(\n",
-    "    gv.Image, [\"longitude\", \"latitude\"], [\"t2m\"], \"hour\"\n",
-    ")\n",
-    "images.opts(\n",
-    "    cmap=\"coolwarm\",\n",
-    "    colorbar=True,\n",
-    "    width=600,\n",
-    "    height=400,\n",
-    "    projection=ccrs.PlateCarree(),\n",
-    "    clabel=\"2m Air Temperature (K)\",\n",
-    ") * gf.coastline"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
-   "outputs": [],
-   "source": [
-    "# average temperatures over the whole day after grouping by the day\n",
-    "ds_surface_temp_2m_day = ds_surface_temp_2m.groupby(\"time.day\").mean()"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -533,7 +517,8 @@
     "execution": {}
    },
    "source": [
-    "### Question 2\n",
+    "### Questions 2\n",
+    "\n",
     "1. What differences do you notice between the hourly and daily interactive plots, and are there any interesting spatial patterns of these temperature changes?"
    ]
   },
@@ -549,7 +534,20 @@
     "\n",
     "\"\"\"\n",
     "1. On hourly timescales, the largest changes are over land because it responds faster than the ocean to the diurnal cycle of solar radiation. This is because the ocean has a higher heat capacity than the land surface. On daily timescales, the surface atmospheric temperature shows comparable variations across both the ocean and land.\n",
-    "\"\"\";"
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_2\")"
    ]
   },
   {
@@ -631,7 +629,20 @@
     "1. The high-frequency variability can largely be attributed to the diurnal cycle or the differences in solar radiation between night and day. This causes large variations in surface temperature, particularly over land and shallow water.\n",
     "2. The low-frequency variability can be attributed to synoptic patterns (e.g., weather) which can move cold or warm air around on timescales of days to weeks.\n",
     "3. We do not have a long enough time series for ENSO to show up, but ENSO could indirectly affect this time series by changing weather patterns on shorter timescales.\n",
-    "\"\"\";"
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_3_1\")"
    ]
   },
   {
@@ -714,7 +725,20 @@
     "2. The surface pressure, which is usually associated with storms, is dominated by the synoptic scale.\n",
     "3. The 10-meter wind speed shows influences from both the diurnal cycle and the synoptic scale.\n",
     "4. The ocean surface temperature shows some sensitivity to the diurnal cycle but is dominated by longer timescale (>weeks) variations than the atmospheric variables.\n",
-    "\"\"\";"
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_3_2\")"
    ]
   },
   {
@@ -738,7 +762,7 @@
    "source": [
     "# Resources\n",
     "\n",
-    "Data for this tutorial can be accessed [here](https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-single-levels?tab=overview). We summarized the download procedure in a separate notebook named ```get_ERA5_reanalysis_data.ipynb```."
+    "Data for this tutorial can be accessed [here](https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-single-levels?tab=overview). We summarized the download procedure in a separate notebook named [```get_ERA5_reanalysis_data.ipynb```](https://github.com/neuromatch/climate-course-content/blob/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/get_ERA5_reanalysis_data.ipynb)."
    ]
   }
  ],
diff --git a/tutorials/W1D2_Ocean-AtmosphereReanalysis/instructor/W1D2_Tutorial3.ipynb b/tutorials/W1D2_Ocean-AtmosphereReanalysis/instructor/W1D2_Tutorial3.ipynb
index 1b7d51012..bdbb73c8b 100644
--- a/tutorials/W1D2_Ocean-AtmosphereReanalysis/instructor/W1D2_Tutorial3.ipynb
+++ b/tutorials/W1D2_Ocean-AtmosphereReanalysis/instructor/W1D2_Tutorial3.ipynb
@@ -27,7 +27,7 @@
     "\n",
     "**Production editors:** Wesley Banfield, Paul Heubel, Jenna Pearson, Konstantine Tsafatinos, Chi Zhang, Ohad Zivan\n",
     "\n",
-    "**Our 2024 Sponsors:** NFDI4Earth, CMIP\n"
+    "**Our 2024 Sponsors:** CMIP, NFDI4Earth\n"
    ]
   },
   {
@@ -99,6 +99,35 @@
     "warnings.filterwarnings(\"ignore\")"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D2_T3\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -256,6 +285,19 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Wind_Driven_Circulation_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -275,16 +317,23 @@
     "from ipywidgets import widgets\n",
     "from IPython.display import IFrame\n",
     "\n",
-    "link_id = \"ebz7w\"\n",
+    "link_id = \"t6c78\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Wind_Driven_Circulation_Slides\")"
    ]
   },
   {
@@ -378,18 +427,6 @@
     "ERA5_mean = ERA5_mm.mean(\"time\")"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
-   "outputs": [],
-   "source": [
-    "# take the temporal mean over 26 years (Jan 1980 - Dec 2005)\n",
-    "ERA5_mean = ERA5_mm.mean(\"time\")"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -484,7 +521,7 @@
     "dataplot = ax.contourf(\n",
     "    ERA5_mean.longitude,\n",
     "    ERA5_mean.latitude,\n",
-    "    ERA5_ANN[var],\n",
+    "    ERA5_mean[var],\n",
     "    levels=colorlevels_clim,\n",
     "    transform=ccrs.PlateCarree(),\n",
     "    cmap=plt.cm.coolwarm,\n",
@@ -532,6 +569,19 @@
     "</details>"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Coding_Exercise_1_1\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -555,7 +605,20 @@
     "'''\n",
     "1. The Hadley Cell is the tropical region containing the easterlies (a.k.a. trade winds), and the Ferrel Cell is the mid-latitude region containing the westerlies.\n",
     "2. Meridional winds are typically weaker and less variable than zonal winds. This is due to the general circulation of the atmosphere, which primarily moves air in the east-west direction rather than north-south.TODO add smt here regarding longtiude and latitude\n",
-    "''';"
+    "'''"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_1_1\")"
    ]
   },
   {
@@ -635,49 +698,20 @@
     "\n",
     "\"\"\"\n",
     "1. The continents influence the strength of the winds, and since the continents are so unevenly distributed on the planet, the winds are weaker in the North than in the South. The strongest winds occur in the Southern Ocean, where there is little land, and must become very strong to create the same drag as over the large land masses of the Northern Hemisphere.\n",
-    "\"\"\";"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "execution": {}
-   },
-   "source": [
-    "# Section 2: Monthly Climatology\n",
-    "\n",
-    "Now, you should examine how the zonal mean winds vary throughout the seasons. You will focus on the zonal wind component and create a special type of diagram called a Hovmöller diagram. In this diagram, the horizontal axis represents latitude, while the vertical axis represents time.\n",
-    "\n",
-    "By using the [Hovmöller diagram](https://en.wikipedia.org/wiki/Hovm%C3%B6ller_diagram), you can visualize how the average east-west winds change over the annual cycle.\n",
-    "\n",
-    "At first, we average our original dataset over all longitudes to get the zonal mean of all variables. We then temporally average it with respect to all months, resulting in a data set with twelve time steps which represent the mean of every month over the whole period of January 1980 to December 2005 for all three variables (`u10`, `v10` and `si10`)."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
-   "outputs": [],
-   "source": [
-    "# Note how we use several commands in one line.\n",
-    "# Python performs them in order. First, calculate the zonal mean, then group by month, and lastly calculate the mean.\n",
-    "# The groupby method hereby regroups the data by month, such that all Januarys, all Februaries, .. can be averaged.\n",
-    "\n",
-    "ERA5_zmean_mmean = ERA5_mm.mean(\"longitude\").groupby(\"time.month\").mean()"
+    "\"\"\""
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "cellView": "form",
     "execution": {}
    },
    "outputs": [],
    "source": [
-    "# Have a look at our new dataset, which incorporates the zonal mean and the temporal mean of every month\n",
-    "ERA5_zmean_mmean"
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_1_2\")"
    ]
   },
   {
@@ -686,11 +720,13 @@
     "execution": {}
    },
    "source": [
-    "We plot the zonal wind component `u10` of the wind vector versus month and latitude, i.e. the aforementioned Hovmöller diagram, which is a special type of [heatmap](https://en.wikipedia.org/wiki/Heat_map) and might remind you of the [Warming Stripes](https://en.wikipedia.org/wiki/Warming_stripes).\n",
+    "# Section 2: Monthly Climatology\n",
     "\n",
-    "It allows us to recognize both spatial (abscissa/ x-axis) and temporal changes (ordinate/ y-axis) in our variables. \n",
+    "Now, you should examine how the zonal mean winds vary throughout the seasons. You will focus on the zonal wind component and create a special type of diagram called a Hovmöller diagram. In this diagram, the horizontal axis represents latitude, while the vertical axis represents time.\n",
     "\n",
-    "Note that xarray uses the metadata of the dataset to label the axes, hence it does not look as pretty and insightful as our previous plots. If you have difficulties to interpret the output, perhaps it helps to look at the previous blue line plot, to compare the axes and to try to understand how the shown extrema translate into colors of the Hovmöller diagram."
+    "By using the [Hovmöller diagram](https://en.wikipedia.org/wiki/Hovm%C3%B6ller_diagram), you can visualize how the average east-west winds change over the annual cycle.\n",
+    "\n",
+    "At first, we average our original dataset over all longitudes to get the zonal mean of all variables. We then temporally average it with respect to all months, resulting in a data set with twelve time steps which represent the mean of every month over the whole period of January 1980 to December 2005 for all three variables (`u10`, `v10` and `si10`)."
    ]
   },
   {
@@ -814,6 +850,19 @@
     "</details>"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Coding_Exercises_2\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -876,16 +925,16 @@
    ]
   },
   {
-   "cell_type": "markdown",
+   "cell_type": "code",
+   "execution_count": null,
    "metadata": {
-    "colab_type": "text",
+    "cellView": "form",
     "execution": {}
    },
+   "outputs": [],
    "source": [
-    "```python\n",
-    "ERA5_season_u10\n",
-    "\n",
-    "```"
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Bonus_Coding_Exercise_3_1\")"
    ]
   },
   {
@@ -896,7 +945,17 @@
    },
    "outputs": [],
    "source": [
-    "# to_remove solution\n",
+    "ERA5_season_u10"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "colab_type": "text",
+    "execution": {}
+   },
+   "source": [
+    "```python\n",
     "var='u10'\n",
     "season='DJF'\n",
     "F, ax = set_projection_figure(projection = ccrs.PlateCarree())\n",
@@ -919,7 +978,9 @@
     "ax.set_title(... , loc ='left')\n",
     "dataplot = ...\n",
     "_ = ... # colorbar\n",
-    "plt.show()"
+    "plt.show()\n",
+    "\n",
+    "```"
    ]
   },
   {
@@ -930,6 +991,7 @@
    },
    "outputs": [],
    "source": [
+    "# to_remove solution\n",
     "var='u10'\n",
     "season='DJF'\n",
     "F, ax = set_projection_figure(projection = ccrs.PlateCarree())\n",
@@ -961,6 +1023,19 @@
     "plt.show()"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Bonus_Coding_Exercise_3_2\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
diff --git a/tutorials/W1D2_Ocean-AtmosphereReanalysis/instructor/W1D2_Tutorial4.ipynb b/tutorials/W1D2_Ocean-AtmosphereReanalysis/instructor/W1D2_Tutorial4.ipynb
index df27f212e..c138fc58e 100644
--- a/tutorials/W1D2_Ocean-AtmosphereReanalysis/instructor/W1D2_Tutorial4.ipynb
+++ b/tutorials/W1D2_Ocean-AtmosphereReanalysis/instructor/W1D2_Tutorial4.ipynb
@@ -75,8 +75,7 @@
    "source": [
     "# installations ( uncomment and run this cell ONLY when using google colab or kaggle )\n",
     "\n",
-    "# !pip install cartopy\n",
-    "# !pip install geoviews"
+    "# !pip install cartopy"
    ]
   },
   {
@@ -99,6 +98,35 @@
     "warnings.filterwarnings(\"ignore\")"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D2_T4\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -145,24 +173,6 @@
     ")"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "cellView": "form",
-    "execution": {}
-   },
-   "outputs": [],
-   "source": [
-    "# @title Figure Settings\n",
-    "import ipywidgets as widgets  # interactive display\n",
-    "\n",
-    "%config InlineBackend.figure_format = 'retina'\n",
-    "plt.style.use(\n",
-    "    \"https://raw.githubusercontent.com/neuromatch/climate-course-content/main/cma.mplstyle\"\n",
-    ")"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -221,6 +231,19 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Ocean_Wind_Driven_Circulation_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -242,14 +265,21 @@
     "\n",
     "link_id = \"f8c5r\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Ocean_Wind_Driven_Circulation_Slides\")"
    ]
   },
   {
@@ -331,7 +361,6 @@
    },
    "outputs": [],
    "source": [
-    "#TODO file contains wrong variable EVEL instead of nvel CHECK ipynb file from Aurora\n",
     "# current in east/west direction labeled here as 'v'\n",
     "fname_ocn_surface_current_v = \"nvel_monthly_2016.nc\"\n",
     "url_ocn_surface_current_v = \"https://osf.io/vzdn4/download\"\n",
@@ -389,7 +418,20 @@
     "\"\"\"\n",
     "1. The atmospheric dataset has a higher output frequency than the oceanic dataset because of the different timescales on which the atmosphere and the ocean change significantly. The atmosphere has a lower heat capacity (i.e., thermal inertia) and density than the ocean. This means that the temperature and wind speed (which is related to momentum) of the atmosphere can change rapidly (over minutes to hours), while the ocean temperature and currents change more slowly.\n",
     "2. The atmosphere plays a faster, more immediate role in the climate system than the ocean. It reacts quickly to heat and pressure differences, driving weather and synoptic features. The ocean, on the other hand, plays a longer-term role in the climate system and provides a buffering effect against rapid atmospheric changes.\n",
-    "\"\"\";"
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_1_1\")"
    ]
   },
   {
@@ -649,7 +691,20 @@
     "\"\"\"\n",
     "1. Yes, the surface currents are deflected relative to the surface winds, and this seems to happen globally.\n",
     "2. The deflection of the ocean surface current is to the left of the wind in the Southern Hemisphere, and is to the right of the wind in the Northern Hemisphere. This property is predicted by Ekman flow.\n",
-    "\"\"\";"
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_3\")"
    ]
   },
   {
diff --git a/tutorials/W1D2_Ocean-AtmosphereReanalysis/instructor/W1D2_Tutorial5.ipynb b/tutorials/W1D2_Ocean-AtmosphereReanalysis/instructor/W1D2_Tutorial5.ipynb
index db9b984b1..0268bd1b6 100644
--- a/tutorials/W1D2_Ocean-AtmosphereReanalysis/instructor/W1D2_Tutorial5.ipynb
+++ b/tutorials/W1D2_Ocean-AtmosphereReanalysis/instructor/W1D2_Tutorial5.ipynb
@@ -107,6 +107,35 @@
     "import gsw"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D2_T5\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -153,24 +182,6 @@
     ")"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "cellView": "form",
-    "execution": {}
-   },
-   "outputs": [],
-   "source": [
-    "# @title Figure Settings\n",
-    "import ipywidgets as widgets  # interactive display\n",
-    "\n",
-    "%config InlineBackend.figure_format = 'retina'\n",
-    "plt.style.use(\n",
-    "    \"https://raw.githubusercontent.com/neuromatch/climate-course-content/main/cma.mplstyle\"\n",
-    ")"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -229,6 +240,19 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Thermohaline_Circulation_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -250,14 +274,21 @@
     "\n",
     "link_id = \"vdeq6\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Thermohaline_Circulation_Slides\")"
    ]
   },
   {
@@ -445,7 +476,7 @@
    },
    "source": [
     "## Section 2.1: Linearized Equation of State\n",
-    "Here we take the linearized equation of state from equation 1.57 in Vallis' textbook [\"*Atmospheric and Oceanic Fluid Dynamics*\"](https://www.cambridge.org/core/books/atmospheric-and-oceanic-fluid-dynamics/41379BDDC4257CBE11143C466F6428A4)\n",
+    "Here we take the linearized equation of state from equation 1.57 in Vallis' textbook [\"*Atmospheric and Oceanic Fluid Dynamics*\"](https://www.cambridge.org/core/books/atmospheric-and-oceanic-fluid-dynamics/41379BDDC4257CBE11143C466F6428A4) (not Open-access)\n",
     "\n",
     "$$ \\rho=\\rho_0[1-\\beta_T(T-T_0)+\\beta_S(S-S_0)+\\beta_p(p-p_0)] $$\n",
     "\n",
@@ -636,7 +667,20 @@
     "\"\"\"\n",
     "1. When salinity rises, the water's capacity to contract in response to added salt (haline contraction coefficient) generally increases. Similarly, as temperature decreases, water's volume expansion due to heating (thermal expansion coefficient) generally decreases. These variations can significantly affect seawater density, creating pressure gradients that in turn influence the intensity and direction of ocean currents.\n",
     "2. The surface water in this region has a larger density than the surface water surrounding it, making it relatively likely that this surface water will be dense enough to sink and mix with the waters below. Conversely, the same latitude in the Pacific is much less dense (due to fresher water) and there is no deep water formation that takes place here.\n",
-    "\"\"\";"
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_2_2\")"
    ]
   },
   {
diff --git a/tutorials/W1D2_Ocean-AtmosphereReanalysis/instructor/W1D2_Tutorial6.ipynb b/tutorials/W1D2_Ocean-AtmosphereReanalysis/instructor/W1D2_Tutorial6.ipynb
index a94f55c57..d75172954 100644
--- a/tutorials/W1D2_Ocean-AtmosphereReanalysis/instructor/W1D2_Tutorial6.ipynb
+++ b/tutorials/W1D2_Ocean-AtmosphereReanalysis/instructor/W1D2_Tutorial6.ipynb
@@ -97,6 +97,35 @@
     "import tempfile"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D2_T6\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -143,24 +172,6 @@
     ")"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "cellView": "form",
-    "execution": {}
-   },
-   "outputs": [],
-   "source": [
-    "# @title Figure Settings\n",
-    "import ipywidgets as widgets  # interactive display\n",
-    "\n",
-    "%config InlineBackend.figure_format = 'retina'\n",
-    "plt.style.use(\n",
-    "    \"https://raw.githubusercontent.com/neuromatch/climate-course-content/main/cma.mplstyle\"\n",
-    ")"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -240,14 +251,8 @@
     "\n",
     "link_id = \"vyb68\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
    ]
   },
   {
@@ -316,29 +321,6 @@
     "The ECCO ocean temperature (`THETA`) is provided in the [SI unit](https://en.wikipedia.org/wiki/International_System_of_Units) Kelvin (K), which might be less intuitive to us. So let us now slice a few years from the data, average it temporally and convert it to degrees Celsius (°C)."
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
-   "outputs": [],
-   "source": [
-    "# Quick plot of the ocean temperature in Kelvin\n",
-    "theta_annual.sel(year=1992,Z=-5.0).plot(cmap=cmo.cm.thermal,\n",
-    "                                        add_labels=True\n",
-    "                                       )"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "execution": {}
-   },
-   "source": [
-    "The ECCO ocean temperature (`THETA`) is provided in the [SI unit](https://en.wikipedia.org/wiki/International_System_of_Units) Kelvin (K), which might be less intuitive to us. So let us now slice a few years from the data, average it temporally and convert it to degrees Celsius (°C)."
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -462,22 +444,6 @@
     "</details>"
    ]
   },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "execution": {}
-   },
-   "source": [
-    "<details>\n",
-    "<summary><font color='orangered'>Click here for a description of the plot  </font></summary>\n",
-    "Heat content that is contained in the water mass from the surface to the respective depth, for all depths calculated with a cumulative sum. \n",
-    "Hence, the overall global ocean heat, integrated from 6000m to the surface, is approximately 0.02 * 10^6 ZJ.\n",
-    "\n",
-    "***\n",
-    "\n",
-    "</details>"
-   ]
-  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -518,7 +484,7 @@
     "execution": {}
    },
    "source": [
-    "## Question 1\n",
+    "## Questions 1\n",
     "\n",
     "1. Based on the last two plots, are depth-variations in ocean heat content primarily due to vertical changes in the temperature or area of the ocean?\n"
    ]
@@ -535,7 +501,20 @@
     "\n",
     "\"\"\"\n",
     "1. The volume as a function of depth has a shape that is almost identical to the ocean heat content plot, which indicates that the ocean heat content above each depth is primarily shaped by depth-variations in the global ocean's area.\n",
-    "\"\"\";"
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_1\")"
    ]
   },
   {
@@ -697,7 +676,20 @@
     "\n",
     "\"\"\"\n",
     "1. The total heat gain is around 190 ZJ, while the upper layers have gained roughly 130 ZJ (above 700 m) and 35 ZJ (700-2000 m). This means the upper 2000 m contain (130+35)/190 = 87% of the ocean's heat gain, despite containing only ~50% of the ocean's water (see the volume plot you created in Section 1).\n",
-    "\"\"\";"
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_2\")"
    ]
   },
   {
diff --git a/tutorials/W1D2_Ocean-AtmosphereReanalysis/instructor/get_ERA5_reanalysis_data.ipynb b/tutorials/W1D2_Ocean-AtmosphereReanalysis/instructor/get_ERA5_reanalysis_data.ipynb
new file mode 100644
index 000000000..e25f38e1b
--- /dev/null
+++ b/tutorials/W1D2_Ocean-AtmosphereReanalysis/instructor/get_ERA5_reanalysis_data.ipynb
@@ -0,0 +1,216 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "0ea0e24d-c94e-4564-a259-c397aa887e91",
+   "metadata": {
+    "execution": {}
+   },
+   "source": [
+    "# Load ERA5 Reanalysis Data via the CDS API\n",
+    "\n",
+    "The code in this notebook was used to create the input data for Tutorial 2 using the ERA5 Reanalysis dataset computed by the European Copernicus Copernicus Climate Change Service (C3S) [Climate Data Store (CDS)](https://cds.climate.copernicus.eu/#!/home). It is provided here to give a better idea of how climate data can be obtained, in this case through an [API](https://cds.climate.copernicus.eu/api-how-to). CDS's machinery of working with Reanalysis (and other) data is very powerful and immensely useful. It was decided to download the data separately and load it from OSF in Tutorial 2 as it is not necessary (and too time-consuming) for every participant to sign up for an account and run this operation, unnecessarily using computing resources and blocking queues. \n",
+    "\n",
+    "Nevertheless, this is the way you can access large amounts of data assimilation (measurement-model) output that has been stored in the cloud. This is very useful to get easy access to such information. Feel free to modify the code to access different data and address your research questions.\n",
+    "\n",
+    "Before accessing data this way, please familiarize yourself with the CDS API documentation and resources linked within this notebook and listed at the end. \n",
+    "\n",
+    "This code works by setting up a rather large query, resulting in a download that is possible after creating a personal account. The actual computation is triggered by running the last cell of this section.\n",
+    "\n",
+    "Please DO NOT simply run it straightaway after modifications, the code takes quite a long time to run depending on the number of variables as well as temporal and spatial resolution, and thereby uses significant computing resources. Think first about what is it that you need.\n",
+    "\n",
+    "However, our example can give you a good idea of what data can be accessed via the CDS API, and Tutorial 2 of what can be done with it. \n",
+    "\n",
+    "Get excited, go explore, have fun!"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "6d2e6e35-1965-439d-97aa-0608dd46a3bc",
+   "metadata": {
+    "execution": {}
+   },
+   "source": [
+    "## Prerequisites\n",
+    "\n",
+    "We assume that you have installed all Python libraries that are necessary to build this course's book or to execute it via Colab or Kaggle, such that you have ```cdsapi``` installed already. First, you have to sign up for an account at the [Copernicus Climate Data Store](https://cds.climate.copernicus.eu/user/register) and accept the Copernicus license by creating a test download using the CDS Download web form interface. For more details [click here](https://confluence.ecmwf.int/display/CKB/How+to+download+ERA5#heading-3-DownloadingonlineERA5familydatathroughtheCDSwebinterface).\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "a4cf01ac-f46f-45da-b6fe-0e1701200ff0",
+   "metadata": {
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# Import the Copernicus cdsapi package\n",
+    "import cdsapi"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1d1066cf-f252-48c9-bd87-0a54c7e0fbf0",
+   "metadata": {
+    "execution": {}
+   },
+   "source": [
+    " We now retrieve the data by choosing a data set, i.e. ```reanalysis-era5-single-levels```;\n",
+    " our variables of interest\n",
+    "```\n",
+    "'10m_u_component_of_wind',\n",
+    "'10m_v_component_of_wind',\n",
+    "'2m_temperature',\n",
+    "'sea_surface_temperature',\n",
+    "'surface_pressure';\n",
+    "```\n",
+    "a year, i.e. ```2018```;\n",
+    "a month, i.e. March ```03```;\n",
+    "all days of this month ```01-31```; all hours of these days ```00:00-23:00```; the area of interest, i.e. longitude (```-90``` to ```-65```) and latitude (```30.2``` to ```55.2```); and finally the format, i.e. ```netcdf```. In summary, this results in a file of the size of 72 MB, while we only sliced one month of data in a smaller subregion. So be aware of modifying it to larger data sets, as this might crash your computer. \n",
+    "\n",
+    "Note that we did not write this ```retrieve()``` table on our own but copied the script that is shown once you have selected everything in the web [interface of CDS](https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-single-levels?tab=form) in the ***Download data*** tab and clicked on ***Show API Request***.\n",
+    "\n",
+    "Please also note that this data retrieval can sometimes take up to 24 hours, in reality, our experience shows a queue time of about an hour. The file ```download_month.nc``` is saved in your working directory but you can specify the path here if needed."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "45b705ae-9933-4f4c-a3dc-3548f8a41594",
+   "metadata": {
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "c = cdsapi.Client()\n",
+    "\n",
+    "res = c.retrieve(\n",
+    "    'reanalysis-era5-single-levels',\n",
+    "    {\n",
+    "        'product_type': 'reanalysis',\n",
+    "        'variable': [\n",
+    "            '10m_u_component_of_wind', '10m_v_component_of_wind', '2m_temperature',\n",
+    "            'sea_surface_temperature', 'surface_pressure',\n",
+    "        ],\n",
+    "        'year': '2018',\n",
+    "        'month': '03',\n",
+    "        'day': [\n",
+    "            '01', '02', '03',\n",
+    "            '04', '05', '06',\n",
+    "            '07', '08', '09',\n",
+    "            '10', '11', '12',\n",
+    "            '13', '14', '15',\n",
+    "            '16', '17', '18',\n",
+    "            '19', '20', '21',\n",
+    "            '22', '23', '24',\n",
+    "            '25', '26', '27',\n",
+    "            '28', '29', '30',\n",
+    "            '31',\n",
+    "        ],\n",
+    "        'time': [\n",
+    "            '00:00', '01:00', '02:00',\n",
+    "            '03:00', '04:00', '05:00',\n",
+    "            '06:00', '07:00', '08:00',\n",
+    "            '09:00', '10:00', '11:00',\n",
+    "            '12:00', '13:00', '14:00',\n",
+    "            '15:00', '16:00', '17:00',\n",
+    "            '18:00', '19:00', '20:00',\n",
+    "            '21:00', '22:00', '23:00',\n",
+    "        ],\n",
+    "        'area': [\n",
+    "            55.2, -90, 30.2,\n",
+    "            -65,\n",
+    "        ],\n",
+    "        'format': 'netcdf',\n",
+    "    },\n",
+    "    'download_month.nc')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "301328d1-cf3c-47d4-8191-dbd4bcc498a9",
+   "metadata": {
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# We follow https://confluence.ecmwf.int/display/CKB/How+to+download+ERA5 after Signing up for CDS via"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "a627e3ca-37b4-4a64-a841-b1d0f411856c",
+   "metadata": {
+    "execution": {}
+   },
+   "source": [
+    "## Selecting a Different Spatial Region\n",
+    "\n",
+    "Define another spatial region, such as where you live, by selecting a longitude and latitude range of your choice. To find the longitude and latitude coordinates of your region, you can use [Google Earth view](https://earth.google.com/), and read the position of your cursor in the lower right corner.\n",
+    "\n",
+    "### Note About the Geographic Coordinate System and the Coordinates Used in This Dataset\n",
+    "A point on Earth is described by latitude-longitude coordinates relative to the zero-meridian line going through Greenwich in London, UK (longitude = 0 degree) and the xero-latitude line along the equator (latitude = 0 degrees). Points east of Greenwich up to the *dateline* on the opposite side of the globe are referenced as 0 to +180 and points to the west of Greenwich are 0 to -180. -180 and +180 refer to the same longitude, the so-called *dateline* in the central Pacific. \n",
+    "\n",
+    "However, some data is referenced in a slightly different way where longitude runs from 0 to 360 rather than -180 to +180. Longitude increases as you move east of Greenwich, until you reach Greenwich again (0 or 360 degrees), rather than stopping at the *dateline*. "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "875cfd11-cce0-4e84-9744-192f7a3765f9",
+   "metadata": {
+    "execution": {}
+   },
+   "source": [
+    "## Helpful resources\n",
+    "\n",
+    "This bonus script is added for completeness and follows many great tutorials as well as other documentation that already exists out there. Please have a look at the following list that mentions a few:\n",
+    "\n",
+    "How to use the CDS API:\n",
+    "- [https://cds.climate.copernicus.eu/api-how-to](https://cds.climate.copernicus.eu/api-how-to)\n",
+    "- [https://confluence.ecmwf.int/display/CKB/How+to+download+ERA5](https://confluence.ecmwf.int/display/CKB/How+to+download+ERA5)\n",
+    "- [https://fanwangecon.github.io/Py4Econ/getdata/envir/htmlpdfr/fs_ecmwf.html](https://fanwangecon.github.io/Py4Econ/getdata/envir/htmlpdfr/fs_ecmwf.html)\n",
+    "\n",
+    "How to register:\n",
+    "- [https://cds.climate.copernicus.eu/user/register](https://cds.climate.copernicus.eu/user/register)\n",
+    "\n",
+    "The Data\n",
+    "- [https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-single-levels?tab=overview](https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-single-levels?tab=overview)\n",
+    "- [https://cds.climate.copernicus.eu/#!/home](https://cds.climate.copernicus.eu/#!/home)"
+   ]
+  }
+ ],
+ "metadata": {
+  "colab": {
+   "collapsed_sections": [],
+   "include_colab_link": true,
+   "name": "get_ERA5_reanalysis_data",
+   "toc_visible": true
+  },
+  "kernel": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.19"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/tutorials/W1D2_Ocean-AtmosphereReanalysis/solutions/W1D2_Tutorial2_Solution_073b07d9.py b/tutorials/W1D2_Ocean-AtmosphereReanalysis/solutions/W1D2_Tutorial2_Solution_04b4bc1e.py
similarity index 99%
rename from tutorials/W1D2_Ocean-AtmosphereReanalysis/solutions/W1D2_Tutorial2_Solution_073b07d9.py
rename to tutorials/W1D2_Ocean-AtmosphereReanalysis/solutions/W1D2_Tutorial2_Solution_04b4bc1e.py
index 2951f7147..c2afa2031 100644
--- a/tutorials/W1D2_Ocean-AtmosphereReanalysis/solutions/W1D2_Tutorial2_Solution_073b07d9.py
+++ b/tutorials/W1D2_Ocean-AtmosphereReanalysis/solutions/W1D2_Tutorial2_Solution_04b4bc1e.py
@@ -2,4 +2,4 @@
 1. The high-frequency variability can largely be attributed to the diurnal cycle or the differences in solar radiation between night and day. This causes large variations in surface temperature, particularly over land and shallow water.
 2. The low-frequency variability can be attributed to synoptic patterns (e.g., weather) which can move cold or warm air around on timescales of days to weeks.
 3. We do not have a long enough time series for ENSO to show up, but ENSO could indirectly affect this time series by changing weather patterns on shorter timescales.
-""";
\ No newline at end of file
+"""
\ No newline at end of file
diff --git a/tutorials/W1D2_Ocean-AtmosphereReanalysis/solutions/W1D2_Tutorial2_Solution_64cd961b.py b/tutorials/W1D2_Ocean-AtmosphereReanalysis/solutions/W1D2_Tutorial2_Solution_c4a70d04.py
similarity index 98%
rename from tutorials/W1D2_Ocean-AtmosphereReanalysis/solutions/W1D2_Tutorial2_Solution_64cd961b.py
rename to tutorials/W1D2_Ocean-AtmosphereReanalysis/solutions/W1D2_Tutorial2_Solution_c4a70d04.py
index cbb6f9616..821cff0d7 100644
--- a/tutorials/W1D2_Ocean-AtmosphereReanalysis/solutions/W1D2_Tutorial2_Solution_64cd961b.py
+++ b/tutorials/W1D2_Ocean-AtmosphereReanalysis/solutions/W1D2_Tutorial2_Solution_c4a70d04.py
@@ -1,4 +1,4 @@
 
 """
 1. On hourly timescales, the largest changes are over land because it responds faster than the ocean to the diurnal cycle of solar radiation. This is because the ocean has a higher heat capacity than the land surface. On daily timescales, the surface atmospheric temperature shows comparable variations across both the ocean and land.
-""";
\ No newline at end of file
+"""
\ No newline at end of file
diff --git a/tutorials/W1D2_Ocean-AtmosphereReanalysis/solutions/W1D2_Tutorial2_Solution_e28a5729.py b/tutorials/W1D2_Ocean-AtmosphereReanalysis/solutions/W1D2_Tutorial2_Solution_d785de0b.py
similarity index 99%
rename from tutorials/W1D2_Ocean-AtmosphereReanalysis/solutions/W1D2_Tutorial2_Solution_e28a5729.py
rename to tutorials/W1D2_Ocean-AtmosphereReanalysis/solutions/W1D2_Tutorial2_Solution_d785de0b.py
index f935a26b1..62d9ac032 100644
--- a/tutorials/W1D2_Ocean-AtmosphereReanalysis/solutions/W1D2_Tutorial2_Solution_e28a5729.py
+++ b/tutorials/W1D2_Ocean-AtmosphereReanalysis/solutions/W1D2_Tutorial2_Solution_d785de0b.py
@@ -3,4 +3,4 @@
 2. The surface pressure, which is usually associated with storms, is dominated by the synoptic scale.
 3. The 10-meter wind speed shows influences from both the diurnal cycle and the synoptic scale.
 4. The ocean surface temperature shows some sensitivity to the diurnal cycle but is dominated by longer timescale (>weeks) variations than the atmospheric variables.
-""";
\ No newline at end of file
+"""
\ No newline at end of file
diff --git a/tutorials/W1D2_Ocean-AtmosphereReanalysis/solutions/W1D2_Tutorial3_Solution_2e3535c0.py b/tutorials/W1D2_Ocean-AtmosphereReanalysis/solutions/W1D2_Tutorial3_Solution_13648ee4.py
similarity index 98%
rename from tutorials/W1D2_Ocean-AtmosphereReanalysis/solutions/W1D2_Tutorial3_Solution_2e3535c0.py
rename to tutorials/W1D2_Ocean-AtmosphereReanalysis/solutions/W1D2_Tutorial3_Solution_13648ee4.py
index 8a9b87dcd..7476fd155 100644
--- a/tutorials/W1D2_Ocean-AtmosphereReanalysis/solutions/W1D2_Tutorial3_Solution_2e3535c0.py
+++ b/tutorials/W1D2_Ocean-AtmosphereReanalysis/solutions/W1D2_Tutorial3_Solution_13648ee4.py
@@ -1,4 +1,4 @@
 
 """
 1. The continents influence the strength of the winds, and since the continents are so unevenly distributed on the planet, the winds are weaker in the North than in the South. The strongest winds occur in the Southern Ocean, where there is little land, and must become very strong to create the same drag as over the large land masses of the Northern Hemisphere.
-""";
\ No newline at end of file
+"""
\ No newline at end of file
diff --git a/tutorials/W1D2_Ocean-AtmosphereReanalysis/solutions/W1D2_Tutorial3_Solution_9bbac31e.py b/tutorials/W1D2_Ocean-AtmosphereReanalysis/solutions/W1D2_Tutorial3_Solution_3c00b7bc.py
similarity index 99%
rename from tutorials/W1D2_Ocean-AtmosphereReanalysis/solutions/W1D2_Tutorial3_Solution_9bbac31e.py
rename to tutorials/W1D2_Ocean-AtmosphereReanalysis/solutions/W1D2_Tutorial3_Solution_3c00b7bc.py
index 5bcdc1553..45a3eedd4 100644
--- a/tutorials/W1D2_Ocean-AtmosphereReanalysis/solutions/W1D2_Tutorial3_Solution_9bbac31e.py
+++ b/tutorials/W1D2_Ocean-AtmosphereReanalysis/solutions/W1D2_Tutorial3_Solution_3c00b7bc.py
@@ -1,4 +1,4 @@
 '''
 1. The Hadley Cell is the tropical region containing the easterlies (a.k.a. trade winds), and the Ferrel Cell is the mid-latitude region containing the westerlies.
 2. Meridional winds are typically weaker and less variable than zonal winds. This is due to the general circulation of the atmosphere, which primarily moves air in the east-west direction rather than north-south.TODO add smt here regarding longtiude and latitude
-''';
\ No newline at end of file
+'''
\ No newline at end of file
diff --git a/tutorials/W1D2_Ocean-AtmosphereReanalysis/solutions/W1D2_Tutorial3_Solution_a061ee5b.py b/tutorials/W1D2_Ocean-AtmosphereReanalysis/solutions/W1D2_Tutorial3_Solution_a061ee5b.py
deleted file mode 100644
index 8e4a576bc..000000000
--- a/tutorials/W1D2_Ocean-AtmosphereReanalysis/solutions/W1D2_Tutorial3_Solution_a061ee5b.py
+++ /dev/null
@@ -1,23 +0,0 @@
-var='u10'
-season='DJF'
-F, ax = set_projection_figure(projection = ccrs.PlateCarree())
-ax.set_title('Zonal Wind DJF mean | '+ var , loc ='left')
-dataplot = ...
-_ = ... # colorbar
-plt.show()
-
-season='JJA'
-F, ax = set_projection_figure(projection = ccrs.PlateCarree())
-ax.set_title('Zonal Wind DJF mean | '+ var , loc ='left')
-dataplot = ...
-_ = ... # colorbar
-plt.show()
-
-# difference:
-pdata = ...
-
-F, ax = set_projection_figure(projection = ccrs.PlateCarree())
-ax.set_title(... , loc ='left')
-dataplot = ...
-_ = ... # colorbar
-plt.show()
\ No newline at end of file
diff --git a/tutorials/W1D2_Ocean-AtmosphereReanalysis/solutions/W1D2_Tutorial3_Solution_f288b0e0.py b/tutorials/W1D2_Ocean-AtmosphereReanalysis/solutions/W1D2_Tutorial3_Solution_f288b0e0.py
new file mode 100644
index 000000000..844b057b6
--- /dev/null
+++ b/tutorials/W1D2_Ocean-AtmosphereReanalysis/solutions/W1D2_Tutorial3_Solution_f288b0e0.py
@@ -0,0 +1,29 @@
+var='u10'
+season='DJF'
+F, ax = set_projection_figure(projection = ccrs.PlateCarree())
+ax.set_title('Zonal Wind DJF mean | '+ var , loc ='left')
+dataplot = ax.contourf(ERA5_season_u10.longitude, ERA5_season_u10.latitude, ERA5_season_u10.sel(season=season),
+                       levels = colorlevels_clim,
+                       transform=ccrs.PlateCarree(), cmap= plt.cm.coolwarm)
+_ = plt.colorbar(dataplot, orientation='vertical', label = 'Wind speed (m/s)', shrink= 0.55 , pad = 0.11) # colorbar
+plt.show()
+
+season='JJA'
+F, ax = set_projection_figure(projection = ccrs.PlateCarree())
+ax.set_title('Zonal Wind DJF mean | '+ var , loc ='left')
+dataplot = ax.contourf(ERA5_season_u10.longitude, ERA5_season_u10.latitude, ERA5_season_u10.sel(season=season),
+                       levels = colorlevels_clim,
+                       transform=ccrs.PlateCarree(), cmap= plt.cm.coolwarm)
+_ = plt.colorbar(dataplot, orientation='vertical', label = 'Wind speed (m/s)', shrink= 0.55 , pad = 0.11) # colorbar
+plt.show()
+
+# difference:
+pdata = ERA5_season_u10.sel(season='DJF') - ERA5_season_u10.sel(season='JJA')
+
+F, ax = set_projection_figure(projection = ccrs.PlateCarree())
+ax.set_title('Zonal Wind DJF mean - JJA mean | '+ var , loc ='left')
+dataplot = ax.contourf(ERA5_season_u10.longitude, ERA5_season_u10.latitude,pdata ,
+                       levels = colorlevels_clim,
+                       transform=ccrs.PlateCarree(), cmap= plt.cm.coolwarm)
+_ = plt.colorbar(dataplot, orientation='vertical', label = 'Wind speed (m/s)', shrink= 0.55 , pad = 0.11) # colorbar
+plt.show()
\ No newline at end of file
diff --git a/tutorials/W1D2_Ocean-AtmosphereReanalysis/solutions/W1D2_Tutorial4_Solution_3ab596b6.py b/tutorials/W1D2_Ocean-AtmosphereReanalysis/solutions/W1D2_Tutorial4_Solution_3561fefc.py
similarity index 99%
rename from tutorials/W1D2_Ocean-AtmosphereReanalysis/solutions/W1D2_Tutorial4_Solution_3ab596b6.py
rename to tutorials/W1D2_Ocean-AtmosphereReanalysis/solutions/W1D2_Tutorial4_Solution_3561fefc.py
index 9d86109e3..ce4f40b95 100644
--- a/tutorials/W1D2_Ocean-AtmosphereReanalysis/solutions/W1D2_Tutorial4_Solution_3ab596b6.py
+++ b/tutorials/W1D2_Ocean-AtmosphereReanalysis/solutions/W1D2_Tutorial4_Solution_3561fefc.py
@@ -2,4 +2,4 @@
 """
 1. The atmospheric dataset has a higher output frequency than the oceanic dataset because of the different timescales on which the atmosphere and the ocean change significantly. The atmosphere has a lower heat capacity (i.e., thermal inertia) and density than the ocean. This means that the temperature and wind speed (which is related to momentum) of the atmosphere can change rapidly (over minutes to hours), while the ocean temperature and currents change more slowly.
 2. The atmosphere plays a faster, more immediate role in the climate system than the ocean. It reacts quickly to heat and pressure differences, driving weather and synoptic features. The ocean, on the other hand, plays a longer-term role in the climate system and provides a buffering effect against rapid atmospheric changes.
-""";
\ No newline at end of file
+"""
\ No newline at end of file
diff --git a/tutorials/W1D2_Ocean-AtmosphereReanalysis/solutions/W1D2_Tutorial4_Solution_ec97d7c5.py b/tutorials/W1D2_Ocean-AtmosphereReanalysis/solutions/W1D2_Tutorial4_Solution_c7eff2a7.py
similarity index 98%
rename from tutorials/W1D2_Ocean-AtmosphereReanalysis/solutions/W1D2_Tutorial4_Solution_ec97d7c5.py
rename to tutorials/W1D2_Ocean-AtmosphereReanalysis/solutions/W1D2_Tutorial4_Solution_c7eff2a7.py
index 8742eb1b5..07494b3f3 100644
--- a/tutorials/W1D2_Ocean-AtmosphereReanalysis/solutions/W1D2_Tutorial4_Solution_ec97d7c5.py
+++ b/tutorials/W1D2_Ocean-AtmosphereReanalysis/solutions/W1D2_Tutorial4_Solution_c7eff2a7.py
@@ -2,4 +2,4 @@
 """
 1. Yes, the surface currents are deflected relative to the surface winds, and this seems to happen globally.
 2. The deflection of the ocean surface current is to the left of the wind in the Southern Hemisphere, and is to the right of the wind in the Northern Hemisphere. This property is predicted by Ekman flow.
-""";
\ No newline at end of file
+"""
\ No newline at end of file
diff --git a/tutorials/W1D2_Ocean-AtmosphereReanalysis/solutions/W1D2_Tutorial5_Solution_0e98a4a4.py b/tutorials/W1D2_Ocean-AtmosphereReanalysis/solutions/W1D2_Tutorial5_Solution_67b02b01.py
similarity index 99%
rename from tutorials/W1D2_Ocean-AtmosphereReanalysis/solutions/W1D2_Tutorial5_Solution_0e98a4a4.py
rename to tutorials/W1D2_Ocean-AtmosphereReanalysis/solutions/W1D2_Tutorial5_Solution_67b02b01.py
index 06124bdcb..5178ce8c8 100644
--- a/tutorials/W1D2_Ocean-AtmosphereReanalysis/solutions/W1D2_Tutorial5_Solution_0e98a4a4.py
+++ b/tutorials/W1D2_Ocean-AtmosphereReanalysis/solutions/W1D2_Tutorial5_Solution_67b02b01.py
@@ -2,4 +2,4 @@
 """
 1. When salinity rises, the water's capacity to contract in response to added salt (haline contraction coefficient) generally increases. Similarly, as temperature decreases, water's volume expansion due to heating (thermal expansion coefficient) generally decreases. These variations can significantly affect seawater density, creating pressure gradients that in turn influence the intensity and direction of ocean currents.
 2. The surface water in this region has a larger density than the surface water surrounding it, making it relatively likely that this surface water will be dense enough to sink and mix with the waters below. Conversely, the same latitude in the Pacific is much less dense (due to fresher water) and there is no deep water formation that takes place here.
-""";
\ No newline at end of file
+"""
\ No newline at end of file
diff --git a/tutorials/W1D2_Ocean-AtmosphereReanalysis/solutions/W1D2_Tutorial6_Solution_29b1198d.py b/tutorials/W1D2_Ocean-AtmosphereReanalysis/solutions/W1D2_Tutorial6_Solution_04fceaff.py
similarity index 98%
rename from tutorials/W1D2_Ocean-AtmosphereReanalysis/solutions/W1D2_Tutorial6_Solution_29b1198d.py
rename to tutorials/W1D2_Ocean-AtmosphereReanalysis/solutions/W1D2_Tutorial6_Solution_04fceaff.py
index bbcf5e6ac..f7f3751f1 100644
--- a/tutorials/W1D2_Ocean-AtmosphereReanalysis/solutions/W1D2_Tutorial6_Solution_29b1198d.py
+++ b/tutorials/W1D2_Ocean-AtmosphereReanalysis/solutions/W1D2_Tutorial6_Solution_04fceaff.py
@@ -1,4 +1,4 @@
 
 """
 1. The total heat gain is around 190 ZJ, while the upper layers have gained roughly 130 ZJ (above 700 m) and 35 ZJ (700-2000 m). This means the upper 2000 m contain (130+35)/190 = 87% of the ocean's heat gain, despite containing only ~50% of the ocean's water (see the volume plot you created in Section 1).
-""";
\ No newline at end of file
+"""
\ No newline at end of file
diff --git a/tutorials/W1D2_Ocean-AtmosphereReanalysis/solutions/W1D2_Tutorial6_Solution_387259da.py b/tutorials/W1D2_Ocean-AtmosphereReanalysis/solutions/W1D2_Tutorial6_Solution_d0a20187.py
similarity index 98%
rename from tutorials/W1D2_Ocean-AtmosphereReanalysis/solutions/W1D2_Tutorial6_Solution_387259da.py
rename to tutorials/W1D2_Ocean-AtmosphereReanalysis/solutions/W1D2_Tutorial6_Solution_d0a20187.py
index 1b506a421..595f84924 100644
--- a/tutorials/W1D2_Ocean-AtmosphereReanalysis/solutions/W1D2_Tutorial6_Solution_387259da.py
+++ b/tutorials/W1D2_Ocean-AtmosphereReanalysis/solutions/W1D2_Tutorial6_Solution_d0a20187.py
@@ -1,4 +1,4 @@
 
 """
 1. The volume as a function of depth has a shape that is almost identical to the ocean heat content plot, which indicates that the ocean heat content above each depth is primarily shaped by depth-variations in the global ocean's area.
-""";
\ No newline at end of file
+"""
\ No newline at end of file
diff --git a/tutorials/W1D2_Ocean-AtmosphereReanalysis/static/W1D2_Tutorial3_Solution_35f2d318_0.png b/tutorials/W1D2_Ocean-AtmosphereReanalysis/static/W1D2_Tutorial3_Solution_35f2d318_0.png
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HcmV?d00001

diff --git a/tutorials/W1D2_Ocean-AtmosphereReanalysis/student/W1D2_Intro.ipynb b/tutorials/W1D2_Ocean-AtmosphereReanalysis/student/W1D2_Intro.ipynb
index 6598ae9fe..858ae927d 100644
--- a/tutorials/W1D2_Ocean-AtmosphereReanalysis/student/W1D2_Intro.ipynb
+++ b/tutorials/W1D2_Ocean-AtmosphereReanalysis/student/W1D2_Intro.ipynb
@@ -66,6 +66,36 @@
     "3. Analyze ocean and atmosphere reanalysis products on different spatial and temporal scales."
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "cda25c98-a47f-403b-8aeb-d2d34e3c0f8e",
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D2_Intro\""
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "a79a31b2",
@@ -144,6 +174,20 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "d1cd2985-22ed-4de3-8f2d-e825f18433e8",
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Oceans_in_Climate_Video\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "8249df54",
@@ -169,14 +213,22 @@
     "\n",
     "link_id = \"2pxs6\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "5492dc34-28d1-47ef-bc82-609b4b208424",
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Oceans_in_Climate_Slides\")"
    ]
   }
  ],
diff --git a/tutorials/W1D2_Ocean-AtmosphereReanalysis/student/W1D2_Tutorial1.ipynb b/tutorials/W1D2_Ocean-AtmosphereReanalysis/student/W1D2_Tutorial1.ipynb
index eeb011b83..33dbc913a 100644
--- a/tutorials/W1D2_Ocean-AtmosphereReanalysis/student/W1D2_Tutorial1.ipynb
+++ b/tutorials/W1D2_Ocean-AtmosphereReanalysis/student/W1D2_Tutorial1.ipynb
@@ -125,13 +125,24 @@
    },
    "outputs": [],
    "source": [
-    "# @title Figure Settings\n",
-    "import ipywidgets as widgets  # interactive display\n",
+    "# @title Install and import feedback gadget\n",
     "\n",
-    "%config InlineBackend.figure_format = 'retina'\n",
-    "plt.style.use(\n",
-    "    \"https://raw.githubusercontent.com/neuromatch/climate-course-content/main/cma.mplstyle\"\n",
-    ")"
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D2_T1\""
    ]
   },
   {
@@ -219,6 +230,19 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_ENSO_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -240,14 +264,21 @@
     "\n",
     "link_id = \"t65v8\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_ENSO_Slides\")"
    ]
   },
   {
@@ -436,21 +467,6 @@
     "</details>"
    ]
   },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "execution": {}
-   },
-   "source": [
-    "<details>\n",
-    "<summary><font color='orangered'>Click here for a description of the plot  </font></summary>\n",
-    "A map plot showing the sea surface temperature (SST) in January 2000 ranging from -2°C to 30°C from the CESM Earth system model's historical simulation for the Sixth Phase of the Coupled Intercomparison Project (CMIP6). Equatorial regions show the warmest temperatures, and polar regions the lowest. A few larger patterns indicate that more than just the latitude is important to create the spatial SST distribution.\n",
-    "\n",
-    "*** \n",
-    "\n",
-    "</details>"
-   ]
-  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -508,21 +524,6 @@
     "</details>"
    ]
   },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "execution": {}
-   },
-   "source": [
-    "<details>\n",
-    "<summary><font color='orangered'>Click here for a description of the plot  </font></summary>\n",
-    "An interactive map plot showing the sea surface temperature (SST) from January 2000 until October 2000  ranging from -2°C to 30°C from the CESM Earth system model's historical simulation for the Sixth Phase of the Coupled Intercomparison Project (CMIP6). Over the annual cycle, the warm and cold SST regions shift depending on the solar input. A few larger patterns indicate that more than just the latitude is important to create the spatial SST distribution, e.g. the equatorial pacific shows a cooler SST trench over the entire year compared to the surrounding subtropical waters.\n",
-    "\n",
-    "*** \n",
-    "\n",
-    "</details>"
-   ]
-  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -770,81 +771,6 @@
     "</details>"
    ]
   },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "execution": {}
-   },
-   "source": [
-    "<details>\n",
-    "<summary><font color='orangered'>Click here for a description of the plot  </font></summary>\n",
-    "A map plot zoomed into the Pacific Ocean showing the sea surface temperature (SST) in the Niño3.4 region in January 2000 ranging from -2°C to 30°C from the CESM Earth system models historical simulation for the Sixth Phase of the Coupled Intercomparison Project (CMIP6). The closer to the equator, the colder the water masses at the surface caused by upwelling from below induced by easterly winds and consequent Ekman transport.\n",
-    "\n",
-    "*** \n",
-    "\n",
-    "</details>"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "execution": {}
-   },
-   "source": [
-    "### Interactive Demo 2.2"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "execution": {}
-   },
-   "source": [
-    "Below we plot an interactive version of the Niño 3.4 region. You can explore the data by zooming in with the tools from the righthand toolbar and visualize what the next few time steps look like in the model by using the interactive slider bar on the most right. Note that the color bar and the corresponding SST scale have changed to make the changing pattern more visible. \n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
-   "outputs": [],
-   "source": [
-    "# again more complicated code that allows interactive plots\n",
-    "gv.extension(\"bokeh\")  # load Bokeh\n",
-    "dataset_plot = gv.Dataset(\n",
-    "    ds_SST.where(\n",
-    "    (ds_SST.lat > -5) & (ds_SST.lat < 5) & (ds_SST.lon > 190) & (ds_SST.lon < 240)\n",
-    ").isel(time=slice(0, 10))\n",
-    ")  # slice only the first 10 timepoint, as it is a time consuming task\n",
-    "images = dataset_plot.to(gv.Image, [\"longitude\", \"latitude\"], \"tos\", \"time\")\n",
-    "# aesthetics\n",
-    "images.opts(\n",
-    "    cmap=\"coolwarm\",\n",
-    "    colorbar=True,\n",
-    "    width=600,\n",
-    "    height=400,\n",
-    "    projection=ccrs.Robinson(central_longitude=180),\n",
-    "    clabel=\"Sea Surface Temperature [˚C]\",\n",
-    ") * gf.coastline"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "execution": {}
-   },
-   "source": [
-    "<details>\n",
-    "<summary><font color='orangered'>Click here for a description of the plot  </font></summary>\n",
-    "An interactive map plot showing the sea surface temperature (SST) from January 2000 until October 2000  ranging from 23.5°C to 30.5°C from the CESM Earth system model's historical simulation for the Sixth Phase of the Coupled Intercomparison Project (CMIP6). Over the annual cycle, the SST increases in the northern hemispherical summer. The closer to the equator, the colder the water masses at the surface caused by upwelling induced by easterly winds and consequent Ekman transport. The more west in the region the warmer the water masses also caused by this transport.\n",
-    "\n",
-    "*** \n",
-    "\n",
-    "</details>"
-   ]
-  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -1075,10 +1001,23 @@
     "execution": {}
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/solutions/W1D2_Tutorial1_Solution_2ba7b5d4.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D2_Ocean-AtmosphereReanalysis/solutions/W1D2_Tutorial1_Solution_2ba7b5d4.py)\n",
     "\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_3\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
diff --git a/tutorials/W1D2_Ocean-AtmosphereReanalysis/student/W1D2_Tutorial2.ipynb b/tutorials/W1D2_Ocean-AtmosphereReanalysis/student/W1D2_Tutorial2.ipynb
index db4f2e8bd..42f13e6a1 100644
--- a/tutorials/W1D2_Ocean-AtmosphereReanalysis/student/W1D2_Tutorial2.ipynb
+++ b/tutorials/W1D2_Ocean-AtmosphereReanalysis/student/W1D2_Tutorial2.ipynb
@@ -105,6 +105,35 @@
     "warnings.filterwarnings('ignore')"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D2_T2\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -152,25 +181,6 @@
     ")"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "cellView": "form",
-    "execution": {},
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "# @title Figure Settings\n",
-    "import ipywidgets as widgets  # interactive display\n",
-    "\n",
-    "%config InlineBackend.figure_format = 'retina'\n",
-    "plt.style.use(\n",
-    "    \"https://raw.githubusercontent.com/neuromatch/climate-course-content/main/cma.mplstyle\"\n",
-    ")"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -229,6 +239,19 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_ECMWF_Reanalysis_Video\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -250,7 +273,7 @@
    "source": [
     "## Section 1.1: Accessing ERA5 Data\n",
     "\n",
-    "You will access the data through our OSF cloud storage to simplify the downloading process. If you are keen to download the data yourself or are simply interested in exploring other variables, please have a look into the ```get_ERA5_reanalysis_data.ipynb``` notebook, where we use the Climate Data Store (CDS) API to get a subset of the huge [ECMWF ERA5 Reanalysis](https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-single-levels?tab=overview) data set.\n",
+    "You will access the data through our OSF cloud storage to simplify the downloading process. If you are keen to download the data yourself or are simply interested in exploring other variables, please have a look into the [```get_ERA5_reanalysis_data.ipynb```](https://github.com/neuromatch/climate-course-content/blob/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/get_ERA5_reanalysis_data.ipynb) notebook, where we use the Climate Data Store (CDS) API to get a subset of the huge [ECMWF ERA5 Reanalysis](https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-single-levels?tab=overview) data set.\n",
     "\n",
     "Let's select a specific year and month to work with, March of 2018:"
    ]
@@ -462,45 +485,6 @@
     "ds_surface_temp_2m_day = ds_surface_temp_2m.groupby(\"time.day\").mean()"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "execution": {},
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "# interactive plot of hourly frequency of surface temperature\n",
-    "# this cell may take a little longer as it contains several maps in a single plotting function\n",
-    "dataset_plot = gv.Dataset(\n",
-    "    ds_surface_temp_2m_hour.isel(hour=slice(0, 12))\n",
-    ")  # only the first 12 time steps (midnight to noon), as it is a time-consuming task\n",
-    "images = dataset_plot.to(\n",
-    "    gv.Image, [\"longitude\", \"latitude\"], [\"t2m\"], \"hour\"\n",
-    ")\n",
-    "images.opts(\n",
-    "    cmap=\"coolwarm\",\n",
-    "    colorbar=True,\n",
-    "    width=600,\n",
-    "    height=400,\n",
-    "    projection=ccrs.PlateCarree(),\n",
-    "    clabel=\"2m Air Temperature (K)\",\n",
-    ") * gf.coastline"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
-   "outputs": [],
-   "source": [
-    "# average temperatures over the whole day after grouping by the day\n",
-    "ds_surface_temp_2m_day = ds_surface_temp_2m.groupby(\"time.day\").mean()"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -533,7 +517,8 @@
     "execution": {}
    },
    "source": [
-    "### Question 2\n",
+    "### Questions 2\n",
+    "\n",
     "1. What differences do you notice between the hourly and daily interactive plots, and are there any interesting spatial patterns of these temperature changes?"
    ]
   },
@@ -544,10 +529,23 @@
     "execution": {}
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/solutions/W1D2_Tutorial2_Solution_64cd961b.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D2_Ocean-AtmosphereReanalysis/solutions/W1D2_Tutorial2_Solution_c4a70d04.py)\n",
     "\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_2\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -621,10 +619,23 @@
     "execution": {}
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/solutions/W1D2_Tutorial2_Solution_073b07d9.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D2_Ocean-AtmosphereReanalysis/solutions/W1D2_Tutorial2_Solution_04b4bc1e.py)\n",
     "\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_3_1\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -698,10 +709,23 @@
     "execution": {}
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/solutions/W1D2_Tutorial2_Solution_e28a5729.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D2_Ocean-AtmosphereReanalysis/solutions/W1D2_Tutorial2_Solution_d785de0b.py)\n",
     "\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_3_2\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -723,7 +747,7 @@
    "source": [
     "# Resources\n",
     "\n",
-    "Data for this tutorial can be accessed [here](https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-single-levels?tab=overview). We summarized the download procedure in a separate notebook named ```get_ERA5_reanalysis_data.ipynb```."
+    "Data for this tutorial can be accessed [here](https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-single-levels?tab=overview). We summarized the download procedure in a separate notebook named [```get_ERA5_reanalysis_data.ipynb```](https://github.com/neuromatch/climate-course-content/blob/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/get_ERA5_reanalysis_data.ipynb)."
    ]
   }
  ],
diff --git a/tutorials/W1D2_Ocean-AtmosphereReanalysis/student/W1D2_Tutorial3.ipynb b/tutorials/W1D2_Ocean-AtmosphereReanalysis/student/W1D2_Tutorial3.ipynb
index cbddcdb35..cf707ee16 100644
--- a/tutorials/W1D2_Ocean-AtmosphereReanalysis/student/W1D2_Tutorial3.ipynb
+++ b/tutorials/W1D2_Ocean-AtmosphereReanalysis/student/W1D2_Tutorial3.ipynb
@@ -27,7 +27,7 @@
     "\n",
     "**Production editors:** Wesley Banfield, Paul Heubel, Jenna Pearson, Konstantine Tsafatinos, Chi Zhang, Ohad Zivan\n",
     "\n",
-    "**Our 2024 Sponsors:** NFDI4Earth, CMIP\n"
+    "**Our 2024 Sponsors:** CMIP, NFDI4Earth\n"
    ]
   },
   {
@@ -99,6 +99,35 @@
     "warnings.filterwarnings(\"ignore\")"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D2_T3\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -256,6 +285,19 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Wind_Driven_Circulation_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -275,16 +317,23 @@
     "from ipywidgets import widgets\n",
     "from IPython.display import IFrame\n",
     "\n",
-    "link_id = \"ebz7w\"\n",
+    "link_id = \"t6c78\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Wind_Driven_Circulation_Slides\")"
    ]
   },
   {
@@ -378,18 +427,6 @@
     "ERA5_mean = ERA5_mm.mean(\"time\")"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
-   "outputs": [],
-   "source": [
-    "# take the temporal mean over 26 years (Jan 1980 - Dec 2005)\n",
-    "ERA5_mean = ERA5_mm.mean(\"time\")"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -484,7 +521,7 @@
     "dataplot = ax.contourf(\n",
     "    ERA5_mean.longitude,\n",
     "    ERA5_mean.latitude,\n",
-    "    ERA5_ANN[var],\n",
+    "    ERA5_mean[var],\n",
     "    levels=colorlevels_clim,\n",
     "    transform=ccrs.PlateCarree(),\n",
     "    cmap=plt.cm.coolwarm,\n",
@@ -499,11 +536,11 @@
     "execution": {}
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/solutions/W1D2_Tutorial3_Solution_5569b155.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D2_Ocean-AtmosphereReanalysis/solutions/W1D2_Tutorial3_Solution_5569b155.py)\n",
     "\n",
     "*Example output:*\n",
     "\n",
-    "<img alt='Solution hint' align='left' width=610.0 height=301.0 src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/static/W1D2_Tutorial3_Solution_5569b155_1.png>\n",
+    "<img alt='Solution hint' align='left' width=610.0 height=301.0 src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D2_Ocean-AtmosphereReanalysis/static/W1D2_Tutorial3_Solution_5569b155_1.png>\n",
     "\n"
    ]
   },
@@ -522,6 +559,19 @@
     "</details>"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Coding_Exercise_1_1\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -540,10 +590,23 @@
     "execution": {}
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/solutions/W1D2_Tutorial3_Solution_9bbac31e.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D2_Ocean-AtmosphereReanalysis/solutions/W1D2_Tutorial3_Solution_3c00b7bc.py)\n",
     "\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_1_1\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -616,50 +679,21 @@
     "execution": {}
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/solutions/W1D2_Tutorial3_Solution_2e3535c0.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D2_Ocean-AtmosphereReanalysis/solutions/W1D2_Tutorial3_Solution_13648ee4.py)\n",
     "\n"
    ]
   },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "execution": {}
-   },
-   "source": [
-    "# Section 2: Monthly Climatology\n",
-    "\n",
-    "Now, you should examine how the zonal mean winds vary throughout the seasons. You will focus on the zonal wind component and create a special type of diagram called a Hovmöller diagram. In this diagram, the horizontal axis represents latitude, while the vertical axis represents time.\n",
-    "\n",
-    "By using the [Hovmöller diagram](https://en.wikipedia.org/wiki/Hovm%C3%B6ller_diagram), you can visualize how the average east-west winds change over the annual cycle.\n",
-    "\n",
-    "At first, we average our original dataset over all longitudes to get the zonal mean of all variables. We then temporally average it with respect to all months, resulting in a data set with twelve time steps which represent the mean of every month over the whole period of January 1980 to December 2005 for all three variables (`u10`, `v10` and `si10`)."
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "cellView": "form",
     "execution": {}
    },
    "outputs": [],
    "source": [
-    "# Note how we use several commands in one line.\n",
-    "# Python performs them in order. First, calculate the zonal mean, then group by month, and lastly calculate the mean.\n",
-    "# The groupby method hereby regroups the data by month, such that all Januarys, all Februaries, .. can be averaged.\n",
-    "\n",
-    "ERA5_zmean_mmean = ERA5_mm.mean(\"longitude\").groupby(\"time.month\").mean()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
-   "outputs": [],
-   "source": [
-    "# Have a look at our new dataset, which incorporates the zonal mean and the temporal mean of every month\n",
-    "ERA5_zmean_mmean"
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_1_2\")"
    ]
   },
   {
@@ -668,11 +702,13 @@
     "execution": {}
    },
    "source": [
-    "We plot the zonal wind component `u10` of the wind vector versus month and latitude, i.e. the aforementioned Hovmöller diagram, which is a special type of [heatmap](https://en.wikipedia.org/wiki/Heat_map) and might remind you of the [Warming Stripes](https://en.wikipedia.org/wiki/Warming_stripes).\n",
+    "# Section 2: Monthly Climatology\n",
     "\n",
-    "It allows us to recognize both spatial (abscissa/ x-axis) and temporal changes (ordinate/ y-axis) in our variables. \n",
+    "Now, you should examine how the zonal mean winds vary throughout the seasons. You will focus on the zonal wind component and create a special type of diagram called a Hovmöller diagram. In this diagram, the horizontal axis represents latitude, while the vertical axis represents time.\n",
     "\n",
-    "Note that xarray uses the metadata of the dataset to label the axes, hence it does not look as pretty and insightful as our previous plots. If you have difficulties to interpret the output, perhaps it helps to look at the previous blue line plot, to compare the axes and to try to understand how the shown extrema translate into colors of the Hovmöller diagram."
+    "By using the [Hovmöller diagram](https://en.wikipedia.org/wiki/Hovm%C3%B6ller_diagram), you can visualize how the average east-west winds change over the annual cycle.\n",
+    "\n",
+    "At first, we average our original dataset over all longitudes to get the zonal mean of all variables. We then temporally average it with respect to all months, resulting in a data set with twelve time steps which represent the mean of every month over the whole period of January 1980 to December 2005 for all three variables (`u10`, `v10` and `si10`)."
    ]
   },
   {
@@ -772,11 +808,11 @@
     "execution": {}
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/solutions/W1D2_Tutorial3_Solution_35f2d318.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D2_Ocean-AtmosphereReanalysis/solutions/W1D2_Tutorial3_Solution_35f2d318.py)\n",
     "\n",
     "*Example output:*\n",
     "\n",
-    "<img alt='Solution hint' align='left' width=759.0 height=574.0 src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/static/W1D2_Tutorial3_Solution_35f2d318_0.png>\n",
+    "<img alt='Solution hint' align='left' width=759.0 height=574.0 src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D2_Ocean-AtmosphereReanalysis/static/W1D2_Tutorial3_Solution_35f2d318_0.png>\n",
     "\n"
    ]
   },
@@ -795,6 +831,19 @@
     "</details>"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Coding_Exercises_2\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -846,7 +895,7 @@
     "execution": {}
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/solutions/W1D2_Tutorial3_Solution_ceab6b1d.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D2_Ocean-AtmosphereReanalysis/solutions/W1D2_Tutorial3_Solution_ceab6b1d.py)\n",
     "\n"
    ]
   },
@@ -854,30 +903,24 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "cellView": "form",
     "execution": {}
    },
    "outputs": [],
    "source": [
-    "ERA5_season_u10"
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Bonus_Coding_Exercise_3_1\")"
    ]
   },
   {
-   "cell_type": "markdown",
+   "cell_type": "code",
+   "execution_count": null,
    "metadata": {
-    "colab_type": "text",
     "execution": {}
    },
+   "outputs": [],
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/solutions/W1D2_Tutorial3_Solution_a061ee5b.py)\n",
-    "\n",
-    "*Example output:*\n",
-    "\n",
-    "<img alt='Solution hint' align='left' width=615.0 height=341.0 src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/static/W1D2_Tutorial3_Solution_a061ee5b_0.png>\n",
-    "\n",
-    "<img alt='Solution hint' align='left' width=615.0 height=341.0 src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/static/W1D2_Tutorial3_Solution_a061ee5b_1.png>\n",
-    "\n",
-    "<img alt='Solution hint' align='left' width=615.0 height=341.0 src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/static/W1D2_Tutorial3_Solution_a061ee5b_2.png>\n",
-    "\n"
+    "ERA5_season_u10"
    ]
   },
   {
@@ -892,33 +935,59 @@
     "season='DJF'\n",
     "F, ax = set_projection_figure(projection = ccrs.PlateCarree())\n",
     "ax.set_title('Zonal Wind DJF mean | '+ var , loc ='left')\n",
-    "dataplot = ax.contourf(ERA5_season_u10.longitude, ERA5_season_u10.latitude, ERA5_season_u10.sel(season=season),\n",
-    "                       levels = colorlevels_clim,\n",
-    "                       transform=ccrs.PlateCarree(), cmap= plt.cm.coolwarm)\n",
-    "_ = plt.colorbar(dataplot, orientation='vertical', label = 'Wind speed (m/s)', shrink= 0.55 , pad = 0.11) # colorbar\n",
+    "dataplot = ...\n",
+    "_ = ... # colorbar\n",
     "plt.show()\n",
     "\n",
     "season='JJA'\n",
     "F, ax = set_projection_figure(projection = ccrs.PlateCarree())\n",
     "ax.set_title('Zonal Wind DJF mean | '+ var , loc ='left')\n",
-    "dataplot = ax.contourf(ERA5_season_u10.longitude, ERA5_season_u10.latitude, ERA5_season_u10.sel(season=season),\n",
-    "                       levels = colorlevels_clim,\n",
-    "                       transform=ccrs.PlateCarree(), cmap= plt.cm.coolwarm)\n",
-    "_ = plt.colorbar(dataplot, orientation='vertical', label = 'Wind speed (m/s)', shrink= 0.55 , pad = 0.11) # colorbar\n",
+    "dataplot = ...\n",
+    "_ = ... # colorbar\n",
     "plt.show()\n",
     "\n",
     "# difference:\n",
-    "pdata = ERA5_season_u10.sel(season='DJF') - ERA5_season_u10.sel(season='JJA')\n",
+    "pdata = ...\n",
     "\n",
     "F, ax = set_projection_figure(projection = ccrs.PlateCarree())\n",
-    "ax.set_title('Zonal Wind DJF mean - JJA mean | '+ var , loc ='left')\n",
-    "dataplot = ax.contourf(ERA5_season_u10.longitude, ERA5_season_u10.latitude,pdata ,\n",
-    "                       levels = colorlevels_clim,\n",
-    "                       transform=ccrs.PlateCarree(), cmap= plt.cm.coolwarm)\n",
-    "_ = plt.colorbar(dataplot, orientation='vertical', label = 'Wind speed (m/s)', shrink= 0.55 , pad = 0.11) # colorbar\n",
+    "ax.set_title(... , loc ='left')\n",
+    "dataplot = ...\n",
+    "_ = ... # colorbar\n",
     "plt.show()"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "colab_type": "text",
+    "execution": {}
+   },
+   "source": [
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D2_Ocean-AtmosphereReanalysis/solutions/W1D2_Tutorial3_Solution_f288b0e0.py)\n",
+    "\n",
+    "*Example output:*\n",
+    "\n",
+    "<img alt='Solution hint' align='left' width=610.0 height=301.0 src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D2_Ocean-AtmosphereReanalysis/static/W1D2_Tutorial3_Solution_f288b0e0_0.png>\n",
+    "\n",
+    "<img alt='Solution hint' align='left' width=610.0 height=301.0 src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D2_Ocean-AtmosphereReanalysis/static/W1D2_Tutorial3_Solution_f288b0e0_1.png>\n",
+    "\n",
+    "<img alt='Solution hint' align='left' width=610.0 height=301.0 src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D2_Ocean-AtmosphereReanalysis/static/W1D2_Tutorial3_Solution_f288b0e0_2.png>\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Bonus_Coding_Exercise_3_2\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
diff --git a/tutorials/W1D2_Ocean-AtmosphereReanalysis/student/W1D2_Tutorial4.ipynb b/tutorials/W1D2_Ocean-AtmosphereReanalysis/student/W1D2_Tutorial4.ipynb
index 2368633af..47f857667 100644
--- a/tutorials/W1D2_Ocean-AtmosphereReanalysis/student/W1D2_Tutorial4.ipynb
+++ b/tutorials/W1D2_Ocean-AtmosphereReanalysis/student/W1D2_Tutorial4.ipynb
@@ -75,8 +75,7 @@
    "source": [
     "# installations ( uncomment and run this cell ONLY when using google colab or kaggle )\n",
     "\n",
-    "# !pip install cartopy\n",
-    "# !pip install geoviews"
+    "# !pip install cartopy"
    ]
   },
   {
@@ -99,6 +98,35 @@
     "warnings.filterwarnings(\"ignore\")"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D2_T4\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -145,24 +173,6 @@
     ")"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "cellView": "form",
-    "execution": {}
-   },
-   "outputs": [],
-   "source": [
-    "# @title Figure Settings\n",
-    "import ipywidgets as widgets  # interactive display\n",
-    "\n",
-    "%config InlineBackend.figure_format = 'retina'\n",
-    "plt.style.use(\n",
-    "    \"https://raw.githubusercontent.com/neuromatch/climate-course-content/main/cma.mplstyle\"\n",
-    ")"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -221,6 +231,19 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Ocean_Wind_Driven_Circulation_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -242,14 +265,21 @@
     "\n",
     "link_id = \"f8c5r\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Ocean_Wind_Driven_Circulation_Slides\")"
    ]
   },
   {
@@ -331,7 +361,6 @@
    },
    "outputs": [],
    "source": [
-    "#TODO file contains wrong variable EVEL instead of nvel CHECK ipynb file from Aurora\n",
     "# current in east/west direction labeled here as 'v'\n",
     "fname_ocn_surface_current_v = \"nvel_monthly_2016.nc\"\n",
     "url_ocn_surface_current_v = \"https://osf.io/vzdn4/download\"\n",
@@ -383,10 +412,23 @@
     "execution": {}
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/solutions/W1D2_Tutorial4_Solution_3ab596b6.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D2_Ocean-AtmosphereReanalysis/solutions/W1D2_Tutorial4_Solution_3561fefc.py)\n",
     "\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_1_1\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -638,10 +680,23 @@
     "execution": {}
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/solutions/W1D2_Tutorial4_Solution_ec97d7c5.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D2_Ocean-AtmosphereReanalysis/solutions/W1D2_Tutorial4_Solution_c7eff2a7.py)\n",
     "\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_3\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
diff --git a/tutorials/W1D2_Ocean-AtmosphereReanalysis/student/W1D2_Tutorial5.ipynb b/tutorials/W1D2_Ocean-AtmosphereReanalysis/student/W1D2_Tutorial5.ipynb
index 5cca5aede..7df295d02 100644
--- a/tutorials/W1D2_Ocean-AtmosphereReanalysis/student/W1D2_Tutorial5.ipynb
+++ b/tutorials/W1D2_Ocean-AtmosphereReanalysis/student/W1D2_Tutorial5.ipynb
@@ -107,6 +107,35 @@
     "import gsw"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D2_T5\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -153,24 +182,6 @@
     ")"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "cellView": "form",
-    "execution": {}
-   },
-   "outputs": [],
-   "source": [
-    "# @title Figure Settings\n",
-    "import ipywidgets as widgets  # interactive display\n",
-    "\n",
-    "%config InlineBackend.figure_format = 'retina'\n",
-    "plt.style.use(\n",
-    "    \"https://raw.githubusercontent.com/neuromatch/climate-course-content/main/cma.mplstyle\"\n",
-    ")"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -229,6 +240,19 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Thermohaline_Circulation_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -250,14 +274,21 @@
     "\n",
     "link_id = \"vdeq6\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Thermohaline_Circulation_Slides\")"
    ]
   },
   {
@@ -445,7 +476,7 @@
    },
    "source": [
     "## Section 2.1: Linearized Equation of State\n",
-    "Here we take the linearized equation of state from equation 1.57 in Vallis' textbook [\"*Atmospheric and Oceanic Fluid Dynamics*\"](https://www.cambridge.org/core/books/atmospheric-and-oceanic-fluid-dynamics/41379BDDC4257CBE11143C466F6428A4)\n",
+    "Here we take the linearized equation of state from equation 1.57 in Vallis' textbook [\"*Atmospheric and Oceanic Fluid Dynamics*\"](https://www.cambridge.org/core/books/atmospheric-and-oceanic-fluid-dynamics/41379BDDC4257CBE11143C466F6428A4) (not Open-access)\n",
     "\n",
     "$$ \\rho=\\rho_0[1-\\beta_T(T-T_0)+\\beta_S(S-S_0)+\\beta_p(p-p_0)] $$\n",
     "\n",
@@ -630,10 +661,23 @@
     "execution": {}
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/solutions/W1D2_Tutorial5_Solution_0e98a4a4.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D2_Ocean-AtmosphereReanalysis/solutions/W1D2_Tutorial5_Solution_67b02b01.py)\n",
     "\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_2_2\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
diff --git a/tutorials/W1D2_Ocean-AtmosphereReanalysis/student/W1D2_Tutorial6.ipynb b/tutorials/W1D2_Ocean-AtmosphereReanalysis/student/W1D2_Tutorial6.ipynb
index e3bba58dd..ab610f0b1 100644
--- a/tutorials/W1D2_Ocean-AtmosphereReanalysis/student/W1D2_Tutorial6.ipynb
+++ b/tutorials/W1D2_Ocean-AtmosphereReanalysis/student/W1D2_Tutorial6.ipynb
@@ -97,6 +97,35 @@
     "import tempfile"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D2_T6\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -143,24 +172,6 @@
     ")"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "cellView": "form",
-    "execution": {}
-   },
-   "outputs": [],
-   "source": [
-    "# @title Figure Settings\n",
-    "import ipywidgets as widgets  # interactive display\n",
-    "\n",
-    "%config InlineBackend.figure_format = 'retina'\n",
-    "plt.style.use(\n",
-    "    \"https://raw.githubusercontent.com/neuromatch/climate-course-content/main/cma.mplstyle\"\n",
-    ")"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -240,14 +251,8 @@
     "\n",
     "link_id = \"vyb68\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
    ]
   },
   {
@@ -316,29 +321,6 @@
     "The ECCO ocean temperature (`THETA`) is provided in the [SI unit](https://en.wikipedia.org/wiki/International_System_of_Units) Kelvin (K), which might be less intuitive to us. So let us now slice a few years from the data, average it temporally and convert it to degrees Celsius (°C)."
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
-   "outputs": [],
-   "source": [
-    "# Quick plot of the ocean temperature in Kelvin\n",
-    "theta_annual.sel(year=1992,Z=-5.0).plot(cmap=cmo.cm.thermal,\n",
-    "                                        add_labels=True\n",
-    "                                       )"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "execution": {}
-   },
-   "source": [
-    "The ECCO ocean temperature (`THETA`) is provided in the [SI unit](https://en.wikipedia.org/wiki/International_System_of_Units) Kelvin (K), which might be less intuitive to us. So let us now slice a few years from the data, average it temporally and convert it to degrees Celsius (°C)."
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -462,22 +444,6 @@
     "</details>"
    ]
   },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "execution": {}
-   },
-   "source": [
-    "<details>\n",
-    "<summary><font color='orangered'>Click here for a description of the plot  </font></summary>\n",
-    "Heat content that is contained in the water mass from the surface to the respective depth, for all depths calculated with a cumulative sum. \n",
-    "Hence, the overall global ocean heat, integrated from 6000m to the surface, is approximately 0.02 * 10^6 ZJ.\n",
-    "\n",
-    "***\n",
-    "\n",
-    "</details>"
-   ]
-  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -518,7 +484,7 @@
     "execution": {}
    },
    "source": [
-    "## Question 1\n",
+    "## Questions 1\n",
     "\n",
     "1. Based on the last two plots, are depth-variations in ocean heat content primarily due to vertical changes in the temperature or area of the ocean?\n"
    ]
@@ -530,10 +496,23 @@
     "execution": {}
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/solutions/W1D2_Tutorial6_Solution_387259da.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D2_Ocean-AtmosphereReanalysis/solutions/W1D2_Tutorial6_Solution_d0a20187.py)\n",
     "\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_1\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -688,10 +667,23 @@
     "execution": {}
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D2_StateoftheClimateOceanandAtmosphereReanalysis/solutions/W1D2_Tutorial6_Solution_29b1198d.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D2_Ocean-AtmosphereReanalysis/solutions/W1D2_Tutorial6_Solution_04fceaff.py)\n",
     "\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_2\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
diff --git a/tutorials/W1D2_Ocean-AtmosphereReanalysis/student/get_ERA5_reanalysis_data.ipynb b/tutorials/W1D2_Ocean-AtmosphereReanalysis/student/get_ERA5_reanalysis_data.ipynb
new file mode 100644
index 000000000..e25f38e1b
--- /dev/null
+++ b/tutorials/W1D2_Ocean-AtmosphereReanalysis/student/get_ERA5_reanalysis_data.ipynb
@@ -0,0 +1,216 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "0ea0e24d-c94e-4564-a259-c397aa887e91",
+   "metadata": {
+    "execution": {}
+   },
+   "source": [
+    "# Load ERA5 Reanalysis Data via the CDS API\n",
+    "\n",
+    "The code in this notebook was used to create the input data for Tutorial 2 using the ERA5 Reanalysis dataset computed by the European Copernicus Copernicus Climate Change Service (C3S) [Climate Data Store (CDS)](https://cds.climate.copernicus.eu/#!/home). It is provided here to give a better idea of how climate data can be obtained, in this case through an [API](https://cds.climate.copernicus.eu/api-how-to). CDS's machinery of working with Reanalysis (and other) data is very powerful and immensely useful. It was decided to download the data separately and load it from OSF in Tutorial 2 as it is not necessary (and too time-consuming) for every participant to sign up for an account and run this operation, unnecessarily using computing resources and blocking queues. \n",
+    "\n",
+    "Nevertheless, this is the way you can access large amounts of data assimilation (measurement-model) output that has been stored in the cloud. This is very useful to get easy access to such information. Feel free to modify the code to access different data and address your research questions.\n",
+    "\n",
+    "Before accessing data this way, please familiarize yourself with the CDS API documentation and resources linked within this notebook and listed at the end. \n",
+    "\n",
+    "This code works by setting up a rather large query, resulting in a download that is possible after creating a personal account. The actual computation is triggered by running the last cell of this section.\n",
+    "\n",
+    "Please DO NOT simply run it straightaway after modifications, the code takes quite a long time to run depending on the number of variables as well as temporal and spatial resolution, and thereby uses significant computing resources. Think first about what is it that you need.\n",
+    "\n",
+    "However, our example can give you a good idea of what data can be accessed via the CDS API, and Tutorial 2 of what can be done with it. \n",
+    "\n",
+    "Get excited, go explore, have fun!"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "6d2e6e35-1965-439d-97aa-0608dd46a3bc",
+   "metadata": {
+    "execution": {}
+   },
+   "source": [
+    "## Prerequisites\n",
+    "\n",
+    "We assume that you have installed all Python libraries that are necessary to build this course's book or to execute it via Colab or Kaggle, such that you have ```cdsapi``` installed already. First, you have to sign up for an account at the [Copernicus Climate Data Store](https://cds.climate.copernicus.eu/user/register) and accept the Copernicus license by creating a test download using the CDS Download web form interface. For more details [click here](https://confluence.ecmwf.int/display/CKB/How+to+download+ERA5#heading-3-DownloadingonlineERA5familydatathroughtheCDSwebinterface).\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "a4cf01ac-f46f-45da-b6fe-0e1701200ff0",
+   "metadata": {
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# Import the Copernicus cdsapi package\n",
+    "import cdsapi"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1d1066cf-f252-48c9-bd87-0a54c7e0fbf0",
+   "metadata": {
+    "execution": {}
+   },
+   "source": [
+    " We now retrieve the data by choosing a data set, i.e. ```reanalysis-era5-single-levels```;\n",
+    " our variables of interest\n",
+    "```\n",
+    "'10m_u_component_of_wind',\n",
+    "'10m_v_component_of_wind',\n",
+    "'2m_temperature',\n",
+    "'sea_surface_temperature',\n",
+    "'surface_pressure';\n",
+    "```\n",
+    "a year, i.e. ```2018```;\n",
+    "a month, i.e. March ```03```;\n",
+    "all days of this month ```01-31```; all hours of these days ```00:00-23:00```; the area of interest, i.e. longitude (```-90``` to ```-65```) and latitude (```30.2``` to ```55.2```); and finally the format, i.e. ```netcdf```. In summary, this results in a file of the size of 72 MB, while we only sliced one month of data in a smaller subregion. So be aware of modifying it to larger data sets, as this might crash your computer. \n",
+    "\n",
+    "Note that we did not write this ```retrieve()``` table on our own but copied the script that is shown once you have selected everything in the web [interface of CDS](https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-single-levels?tab=form) in the ***Download data*** tab and clicked on ***Show API Request***.\n",
+    "\n",
+    "Please also note that this data retrieval can sometimes take up to 24 hours, in reality, our experience shows a queue time of about an hour. The file ```download_month.nc``` is saved in your working directory but you can specify the path here if needed."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "45b705ae-9933-4f4c-a3dc-3548f8a41594",
+   "metadata": {
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "c = cdsapi.Client()\n",
+    "\n",
+    "res = c.retrieve(\n",
+    "    'reanalysis-era5-single-levels',\n",
+    "    {\n",
+    "        'product_type': 'reanalysis',\n",
+    "        'variable': [\n",
+    "            '10m_u_component_of_wind', '10m_v_component_of_wind', '2m_temperature',\n",
+    "            'sea_surface_temperature', 'surface_pressure',\n",
+    "        ],\n",
+    "        'year': '2018',\n",
+    "        'month': '03',\n",
+    "        'day': [\n",
+    "            '01', '02', '03',\n",
+    "            '04', '05', '06',\n",
+    "            '07', '08', '09',\n",
+    "            '10', '11', '12',\n",
+    "            '13', '14', '15',\n",
+    "            '16', '17', '18',\n",
+    "            '19', '20', '21',\n",
+    "            '22', '23', '24',\n",
+    "            '25', '26', '27',\n",
+    "            '28', '29', '30',\n",
+    "            '31',\n",
+    "        ],\n",
+    "        'time': [\n",
+    "            '00:00', '01:00', '02:00',\n",
+    "            '03:00', '04:00', '05:00',\n",
+    "            '06:00', '07:00', '08:00',\n",
+    "            '09:00', '10:00', '11:00',\n",
+    "            '12:00', '13:00', '14:00',\n",
+    "            '15:00', '16:00', '17:00',\n",
+    "            '18:00', '19:00', '20:00',\n",
+    "            '21:00', '22:00', '23:00',\n",
+    "        ],\n",
+    "        'area': [\n",
+    "            55.2, -90, 30.2,\n",
+    "            -65,\n",
+    "        ],\n",
+    "        'format': 'netcdf',\n",
+    "    },\n",
+    "    'download_month.nc')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "301328d1-cf3c-47d4-8191-dbd4bcc498a9",
+   "metadata": {
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# We follow https://confluence.ecmwf.int/display/CKB/How+to+download+ERA5 after Signing up for CDS via"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "a627e3ca-37b4-4a64-a841-b1d0f411856c",
+   "metadata": {
+    "execution": {}
+   },
+   "source": [
+    "## Selecting a Different Spatial Region\n",
+    "\n",
+    "Define another spatial region, such as where you live, by selecting a longitude and latitude range of your choice. To find the longitude and latitude coordinates of your region, you can use [Google Earth view](https://earth.google.com/), and read the position of your cursor in the lower right corner.\n",
+    "\n",
+    "### Note About the Geographic Coordinate System and the Coordinates Used in This Dataset\n",
+    "A point on Earth is described by latitude-longitude coordinates relative to the zero-meridian line going through Greenwich in London, UK (longitude = 0 degree) and the xero-latitude line along the equator (latitude = 0 degrees). Points east of Greenwich up to the *dateline* on the opposite side of the globe are referenced as 0 to +180 and points to the west of Greenwich are 0 to -180. -180 and +180 refer to the same longitude, the so-called *dateline* in the central Pacific. \n",
+    "\n",
+    "However, some data is referenced in a slightly different way where longitude runs from 0 to 360 rather than -180 to +180. Longitude increases as you move east of Greenwich, until you reach Greenwich again (0 or 360 degrees), rather than stopping at the *dateline*. "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "875cfd11-cce0-4e84-9744-192f7a3765f9",
+   "metadata": {
+    "execution": {}
+   },
+   "source": [
+    "## Helpful resources\n",
+    "\n",
+    "This bonus script is added for completeness and follows many great tutorials as well as other documentation that already exists out there. Please have a look at the following list that mentions a few:\n",
+    "\n",
+    "How to use the CDS API:\n",
+    "- [https://cds.climate.copernicus.eu/api-how-to](https://cds.climate.copernicus.eu/api-how-to)\n",
+    "- [https://confluence.ecmwf.int/display/CKB/How+to+download+ERA5](https://confluence.ecmwf.int/display/CKB/How+to+download+ERA5)\n",
+    "- [https://fanwangecon.github.io/Py4Econ/getdata/envir/htmlpdfr/fs_ecmwf.html](https://fanwangecon.github.io/Py4Econ/getdata/envir/htmlpdfr/fs_ecmwf.html)\n",
+    "\n",
+    "How to register:\n",
+    "- [https://cds.climate.copernicus.eu/user/register](https://cds.climate.copernicus.eu/user/register)\n",
+    "\n",
+    "The Data\n",
+    "- [https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-single-levels?tab=overview](https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-single-levels?tab=overview)\n",
+    "- [https://cds.climate.copernicus.eu/#!/home](https://cds.climate.copernicus.eu/#!/home)"
+   ]
+  }
+ ],
+ "metadata": {
+  "colab": {
+   "collapsed_sections": [],
+   "include_colab_link": true,
+   "name": "get_ERA5_reanalysis_data",
+   "toc_visible": true
+  },
+  "kernel": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.19"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/tutorials/W1D3_RemoteSensing/README.md b/tutorials/W1D3_RemoteSensing/README.md
index 90edc0f09..ff5bbd428 100644
--- a/tutorials/W1D3_RemoteSensing/README.md
+++ b/tutorials/W1D3_RemoteSensing/README.md
@@ -1,33 +1,33 @@
-# W1D3 - Remote Sensing Land Oceanand Atmosphere
+# W1D3 - Remote Sensing
 
 ## Instructor notebooks
 
 |   | Run | Run | View |
 | - | --- | --- | ---- |
-| Intro | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/W1D3_Intro.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/W1D3_Intro.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/W1D3_Intro.ipynb?flush_cache=true) |
-| Tutorial 1 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/instructor/W1D3_Tutorial1.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/instructor/W1D3_Tutorial1.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/instructor/W1D3_Tutorial1.ipynb?flush_cache=true) |
-| Tutorial 2 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/instructor/W1D3_Tutorial2.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/instructor/W1D3_Tutorial2.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/instructor/W1D3_Tutorial2.ipynb?flush_cache=true) |
-| Tutorial 3 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/instructor/W1D3_Tutorial3.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/instructor/W1D3_Tutorial3.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/instructor/W1D3_Tutorial3.ipynb?flush_cache=true) |
-| Tutorial 4 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/instructor/W1D3_Tutorial4.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/instructor/W1D3_Tutorial4.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/instructor/W1D3_Tutorial4.ipynb?flush_cache=true) |
-| Tutorial 5 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/instructor/W1D3_Tutorial5.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/instructor/W1D3_Tutorial5.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/instructor/W1D3_Tutorial5.ipynb?flush_cache=true) |
-| Tutorial 6 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/instructor/W1D3_Tutorial6.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/instructor/W1D3_Tutorial6.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/instructor/W1D3_Tutorial6.ipynb?flush_cache=true) |
-| Tutorial 7 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/instructor/W1D3_Tutorial7.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/instructor/W1D3_Tutorial7.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/instructor/W1D3_Tutorial7.ipynb?flush_cache=true) |
-| Tutorial 8 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/instructor/W1D3_Tutorial8.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/instructor/W1D3_Tutorial8.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/instructor/W1D3_Tutorial8.ipynb?flush_cache=true) |
-| Outro | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/W1D3_Outro.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/W1D3_Outro.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/W1D3_Outro.ipynb?flush_cache=true) |
+| Intro | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensing/W1D3_Intro.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D3_RemoteSensing/W1D3_Intro.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensing/W1D3_Intro.ipynb?flush_cache=true) |
+| Tutorial 1 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensing/instructor/W1D3_Tutorial1.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D3_RemoteSensing/instructor/W1D3_Tutorial1.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensing/instructor/W1D3_Tutorial1.ipynb?flush_cache=true) |
+| Tutorial 2 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensing/instructor/W1D3_Tutorial2.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D3_RemoteSensing/instructor/W1D3_Tutorial2.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensing/instructor/W1D3_Tutorial2.ipynb?flush_cache=true) |
+| Tutorial 3 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensing/instructor/W1D3_Tutorial3.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D3_RemoteSensing/instructor/W1D3_Tutorial3.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensing/instructor/W1D3_Tutorial3.ipynb?flush_cache=true) |
+| Tutorial 4 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensing/instructor/W1D3_Tutorial4.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D3_RemoteSensing/instructor/W1D3_Tutorial4.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensing/instructor/W1D3_Tutorial4.ipynb?flush_cache=true) |
+| Tutorial 5 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensing/instructor/W1D3_Tutorial5.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D3_RemoteSensing/instructor/W1D3_Tutorial5.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensing/instructor/W1D3_Tutorial5.ipynb?flush_cache=true) |
+| Tutorial 6 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensing/instructor/W1D3_Tutorial6.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D3_RemoteSensing/instructor/W1D3_Tutorial6.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensing/instructor/W1D3_Tutorial6.ipynb?flush_cache=true) |
+| Tutorial 7 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensing/instructor/W1D3_Tutorial7.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D3_RemoteSensing/instructor/W1D3_Tutorial7.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensing/instructor/W1D3_Tutorial7.ipynb?flush_cache=true) |
+| Tutorial 8 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensing/instructor/W1D3_Tutorial8.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D3_RemoteSensing/instructor/W1D3_Tutorial8.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensing/instructor/W1D3_Tutorial8.ipynb?flush_cache=true) |
+| Outro | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensing/W1D3_Outro.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D3_RemoteSensing/W1D3_Outro.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensing/W1D3_Outro.ipynb?flush_cache=true) |
 
 
 ## Student notebooks
 
 |   | Run | Run | View |
 | - | --- | --- | ---- |
-| Intro | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/W1D3_Intro.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/W1D3_Intro.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/W1D3_Intro.ipynb?flush_cache=true) |
-| Tutorial 1 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/student/W1D3_Tutorial1.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/student/W1D3_Tutorial1.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/student/W1D3_Tutorial1.ipynb?flush_cache=true) |
-| Tutorial 2 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/student/W1D3_Tutorial2.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/student/W1D3_Tutorial2.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/student/W1D3_Tutorial2.ipynb?flush_cache=true) |
-| Tutorial 3 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/student/W1D3_Tutorial3.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/student/W1D3_Tutorial3.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/student/W1D3_Tutorial3.ipynb?flush_cache=true) |
-| Tutorial 4 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/student/W1D3_Tutorial4.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/student/W1D3_Tutorial4.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/student/W1D3_Tutorial4.ipynb?flush_cache=true) |
-| Tutorial 5 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/student/W1D3_Tutorial5.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/student/W1D3_Tutorial5.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/student/W1D3_Tutorial5.ipynb?flush_cache=true) |
-| Tutorial 6 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/student/W1D3_Tutorial6.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/student/W1D3_Tutorial6.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/student/W1D3_Tutorial6.ipynb?flush_cache=true) |
-| Tutorial 7 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/student/W1D3_Tutorial7.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/student/W1D3_Tutorial7.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/student/W1D3_Tutorial7.ipynb?flush_cache=true) |
-| Tutorial 8 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/student/W1D3_Tutorial8.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/student/W1D3_Tutorial8.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/student/W1D3_Tutorial8.ipynb?flush_cache=true) |
-| Outro | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/W1D3_Outro.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/W1D3_Outro.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/W1D3_Outro.ipynb?flush_cache=true) |
+| Intro | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensing/W1D3_Intro.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D3_RemoteSensing/W1D3_Intro.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensing/W1D3_Intro.ipynb?flush_cache=true) |
+| Tutorial 1 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensing/student/W1D3_Tutorial1.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D3_RemoteSensing/student/W1D3_Tutorial1.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensing/student/W1D3_Tutorial1.ipynb?flush_cache=true) |
+| Tutorial 2 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensing/student/W1D3_Tutorial2.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D3_RemoteSensing/student/W1D3_Tutorial2.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensing/student/W1D3_Tutorial2.ipynb?flush_cache=true) |
+| Tutorial 3 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensing/student/W1D3_Tutorial3.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D3_RemoteSensing/student/W1D3_Tutorial3.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensing/student/W1D3_Tutorial3.ipynb?flush_cache=true) |
+| Tutorial 4 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensing/student/W1D3_Tutorial4.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D3_RemoteSensing/student/W1D3_Tutorial4.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensing/student/W1D3_Tutorial4.ipynb?flush_cache=true) |
+| Tutorial 5 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensing/student/W1D3_Tutorial5.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D3_RemoteSensing/student/W1D3_Tutorial5.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensing/student/W1D3_Tutorial5.ipynb?flush_cache=true) |
+| Tutorial 6 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensing/student/W1D3_Tutorial6.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D3_RemoteSensing/student/W1D3_Tutorial6.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensing/student/W1D3_Tutorial6.ipynb?flush_cache=true) |
+| Tutorial 7 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensing/student/W1D3_Tutorial7.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D3_RemoteSensing/student/W1D3_Tutorial7.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensing/student/W1D3_Tutorial7.ipynb?flush_cache=true) |
+| Tutorial 8 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensing/student/W1D3_Tutorial8.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D3_RemoteSensing/student/W1D3_Tutorial8.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensing/student/W1D3_Tutorial8.ipynb?flush_cache=true) |
+| Outro | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensing/W1D3_Outro.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D3_RemoteSensing/W1D3_Outro.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensing/W1D3_Outro.ipynb?flush_cache=true) |
 
diff --git a/tutorials/W1D3_RemoteSensing/W1D3_Intro.ipynb b/tutorials/W1D3_RemoteSensing/W1D3_Intro.ipynb
index 50cc828bb..dee46762d 100644
--- a/tutorials/W1D3_RemoteSensing/W1D3_Intro.ipynb
+++ b/tutorials/W1D3_RemoteSensing/W1D3_Intro.ipynb
@@ -59,7 +59,10 @@
    "cell_type": "code",
    "execution_count": null,
    "id": "0f182426-9adb-4879-9d1d-99fa9cc66d6e",
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Install and import feedback gadget\n",
@@ -97,7 +100,8 @@
    "execution_count": null,
    "id": "d745bf9b",
    "metadata": {
-    "cellView": "form"
+    "cellView": "form",
+    "execution": {}
    },
    "outputs": [],
    "source": [
@@ -162,7 +166,10 @@
    "cell_type": "code",
    "execution_count": null,
    "id": "8721bc44-ac4c-45c4-b377-8243def60b82",
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -184,7 +191,8 @@
    "execution_count": null,
    "id": "6158f5c7",
    "metadata": {
-    "cellView": "form"
+    "cellView": "form",
+    "execution": {}
    },
    "outputs": [],
    "source": [
@@ -202,7 +210,10 @@
    "cell_type": "code",
    "execution_count": null,
    "id": "cf8ee68d-b35e-46d9-8e77-aa275a193ced",
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -237,7 +248,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.18"
+   "version": "3.9.19"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/W1D3_RemoteSensing/W1D3_Tutorial1.ipynb b/tutorials/W1D3_RemoteSensing/W1D3_Tutorial1.ipynb
index 2ed1f5667..1106f71fb 100644
--- a/tutorials/W1D3_RemoteSensing/W1D3_Tutorial1.ipynb
+++ b/tutorials/W1D3_RemoteSensing/W1D3_Tutorial1.ipynb
@@ -53,7 +53,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Install and import feedback gadget\n",
@@ -146,7 +149,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -181,7 +187,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -540,7 +549,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.18"
+   "version": "3.9.19"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/W1D3_RemoteSensing/W1D3_Tutorial2.ipynb b/tutorials/W1D3_RemoteSensing/W1D3_Tutorial2.ipynb
index bff68fa77..d643f474c 100644
--- a/tutorials/W1D3_RemoteSensing/W1D3_Tutorial2.ipynb
+++ b/tutorials/W1D3_RemoteSensing/W1D3_Tutorial2.ipynb
@@ -50,7 +50,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Install and import feedback gadget\n",
@@ -78,6 +81,7 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -133,7 +137,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -145,6 +152,7 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
+    "execution": {},
     "pycharm": {
      "name": "#%%\n"
     },
@@ -167,7 +175,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -290,6 +301,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -457,7 +469,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "### Step 1: Describe your application interest. Be as specific as you can, this\n",
@@ -522,7 +536,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.18"
+   "version": "3.9.19"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/W1D3_RemoteSensing/W1D3_Tutorial3.ipynb b/tutorials/W1D3_RemoteSensing/W1D3_Tutorial3.ipynb
index e8b578cbd..97bb5da4f 100644
--- a/tutorials/W1D3_RemoteSensing/W1D3_Tutorial3.ipynb
+++ b/tutorials/W1D3_RemoteSensing/W1D3_Tutorial3.ipynb
@@ -61,6 +61,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": [
      "colab"
     ]
@@ -90,6 +91,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -110,7 +112,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Install and import feedback gadget\n",
@@ -138,6 +143,7 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -155,7 +161,8 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "form"
+    "cellView": "form",
+    "execution": {}
    },
    "outputs": [],
    "source": [
@@ -183,6 +190,7 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -238,7 +246,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -250,6 +261,7 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
+    "execution": {},
     "pycharm": {
      "name": "#%%\n"
     },
@@ -272,7 +284,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -355,6 +370,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -395,6 +411,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -413,6 +430,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -439,7 +457,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -462,6 +483,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -514,6 +536,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -537,6 +560,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -631,6 +655,7 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -677,6 +702,7 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -713,6 +739,7 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -741,6 +768,7 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -763,6 +791,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -797,6 +826,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -828,6 +858,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -874,7 +905,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -945,7 +979,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.18"
+   "version": "3.9.19"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/W1D3_RemoteSensing/W1D3_Tutorial4.ipynb b/tutorials/W1D3_RemoteSensing/W1D3_Tutorial4.ipynb
index c52dfa0f5..b977f175e 100644
--- a/tutorials/W1D3_RemoteSensing/W1D3_Tutorial4.ipynb
+++ b/tutorials/W1D3_RemoteSensing/W1D3_Tutorial4.ipynb
@@ -64,6 +64,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": [
      "colab"
     ]
@@ -93,6 +94,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -112,7 +114,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Install and import feedback gadget\n",
@@ -140,6 +145,7 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -157,7 +163,8 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "form"
+    "cellView": "form",
+    "execution": {}
    },
    "outputs": [],
    "source": [
@@ -185,6 +192,7 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -240,7 +248,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -252,6 +263,7 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
+    "execution": {},
     "pycharm": {
      "name": "#%%\n"
     },
@@ -274,7 +286,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -319,6 +334,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -336,6 +352,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -357,6 +374,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -391,6 +409,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -412,6 +431,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -430,6 +450,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -459,6 +480,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -499,6 +521,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -523,6 +546,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -582,6 +606,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -606,6 +631,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -636,7 +662,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -666,6 +695,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -681,7 +711,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -720,6 +753,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -768,6 +802,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -792,6 +827,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -814,6 +850,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -868,6 +905,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -885,7 +923,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -905,6 +946,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -951,6 +993,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -984,6 +1027,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -1030,7 +1074,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -1100,7 +1147,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.18"
+   "version": "3.9.19"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/W1D3_RemoteSensing/W1D3_Tutorial5.ipynb b/tutorials/W1D3_RemoteSensing/W1D3_Tutorial5.ipynb
index 21f3cbe92..7170f85b8 100644
--- a/tutorials/W1D3_RemoteSensing/W1D3_Tutorial5.ipynb
+++ b/tutorials/W1D3_RemoteSensing/W1D3_Tutorial5.ipynb
@@ -60,6 +60,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": [
      "colab"
     ]
@@ -89,7 +90,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# imports\n",
@@ -112,7 +115,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Install and import feedback gadget\n",
@@ -139,7 +145,8 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "form"
+    "cellView": "form",
+    "execution": {}
    },
    "outputs": [],
    "source": [
@@ -156,7 +163,8 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "form"
+    "cellView": "form",
+    "execution": {}
    },
    "outputs": [],
    "source": [
@@ -184,6 +192,7 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -239,7 +248,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -251,6 +263,7 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
+    "execution": {},
     "pycharm": {
      "name": "#%%\n"
     },
@@ -273,7 +286,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -309,7 +325,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# connect to the AWS S3 bucket for the GPCP Monthly Precipitation CDR data\n",
@@ -342,7 +360,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# calculate climatology using `.sel()` and `.groupby()` directly.\n",
@@ -368,7 +388,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# use `.groupby()` to calculate the monthly anomaly\n",
@@ -390,7 +412,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# an example of how to export the GPCP monthly anomaly data comparing to the climatology period of 1981-2010.\n",
@@ -411,7 +435,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# initate plot\n",
@@ -462,6 +488,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -494,7 +521,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# set up two subplots that share the x-axis to compare monthly precipitation and monthly anomaly\n",
@@ -560,7 +589,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# calculate 12-month rolling mean for the selected location\n",
@@ -571,7 +602,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# create the time series plot of monthly anomaly\n",
@@ -611,7 +644,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# calculate 24-month rolling mean\n",
@@ -635,7 +670,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# to_remove solution\n",
@@ -661,7 +698,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -684,6 +724,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -701,7 +742,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -724,7 +768,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# calculate the weights using the latitude coordinates\n",
@@ -736,7 +782,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# calculate weighted global monthly mean\n",
@@ -748,7 +796,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# create the time series plot of global weighted monthly anomaly\n",
@@ -778,7 +828,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# calculate unweighted global mean\n",
@@ -803,7 +855,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# to_remove solution\n",
@@ -832,7 +886,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -854,6 +911,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -870,7 +928,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -940,7 +1001,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.18"
+   "version": "3.9.19"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/W1D3_RemoteSensing/W1D3_Tutorial6.ipynb b/tutorials/W1D3_RemoteSensing/W1D3_Tutorial6.ipynb
index 8d832bcbd..6dbb016b3 100644
--- a/tutorials/W1D3_RemoteSensing/W1D3_Tutorial6.ipynb
+++ b/tutorials/W1D3_RemoteSensing/W1D3_Tutorial6.ipynb
@@ -61,6 +61,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": [
      "colab"
     ]
@@ -89,6 +90,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -111,7 +113,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Install and import feedback gadget\n",
@@ -139,6 +144,7 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -156,7 +162,8 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "form"
+    "cellView": "form",
+    "execution": {}
    },
    "outputs": [],
    "source": [
@@ -184,6 +191,7 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -239,7 +247,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -251,6 +262,7 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
+    "execution": {},
     "pycharm": {
      "name": "#%%\n"
     },
@@ -273,7 +285,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -323,6 +338,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -362,6 +378,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -378,6 +395,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -400,6 +418,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -440,6 +459,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -477,6 +497,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -490,6 +511,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -510,7 +532,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "nino34.to_netcdf('nino34_timeseries.nc')\n",
@@ -521,7 +545,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "nino34"
@@ -531,6 +557,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -557,6 +584,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -593,6 +621,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -646,6 +675,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -670,6 +700,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -707,6 +738,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -747,7 +779,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -771,6 +806,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -787,7 +823,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -856,7 +895,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.18"
+   "version": "3.9.19"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/W1D3_RemoteSensing/W1D3_Tutorial7.ipynb b/tutorials/W1D3_RemoteSensing/W1D3_Tutorial7.ipynb
index 61a415eb2..b708e7660 100644
--- a/tutorials/W1D3_RemoteSensing/W1D3_Tutorial7.ipynb
+++ b/tutorials/W1D3_RemoteSensing/W1D3_Tutorial7.ipynb
@@ -61,6 +61,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": [
      "colab"
     ]
@@ -88,6 +89,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -105,7 +107,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Install and import feedback gadget\n",
@@ -133,6 +138,7 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -150,7 +156,8 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "form"
+    "cellView": "form",
+    "execution": {}
    },
    "outputs": [],
    "source": [
@@ -180,6 +187,7 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -245,7 +253,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -257,6 +268,7 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
+    "execution": {},
     "pycharm": {
      "name": "#%%\n"
     },
@@ -279,7 +291,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -321,6 +336,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -337,6 +353,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -369,6 +386,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -384,6 +402,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -426,6 +445,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -490,6 +510,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -507,6 +528,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -522,6 +544,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -556,6 +579,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -614,6 +638,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -631,6 +656,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -679,6 +705,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -710,6 +737,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -725,7 +753,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -747,6 +778,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -814,6 +846,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -887,7 +920,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -955,7 +991,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.18"
+   "version": "3.9.19"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/W1D3_RemoteSensing/W1D3_Tutorial8.ipynb b/tutorials/W1D3_RemoteSensing/W1D3_Tutorial8.ipynb
index f3c644611..c3bb0a410 100644
--- a/tutorials/W1D3_RemoteSensing/W1D3_Tutorial8.ipynb
+++ b/tutorials/W1D3_RemoteSensing/W1D3_Tutorial8.ipynb
@@ -63,6 +63,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": [
      "colab"
     ]
@@ -92,6 +93,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 128816,
      "status": "ok",
@@ -123,7 +125,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Install and import feedback gadget\n",
@@ -151,6 +156,7 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
+    "execution": {},
     "executionInfo": {
      "elapsed": 325,
      "status": "ok",
@@ -178,7 +184,8 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "form"
+    "cellView": "form",
+    "execution": {}
    },
    "outputs": [],
    "source": [
@@ -206,6 +213,7 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -261,7 +269,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -273,6 +284,7 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
+    "execution": {},
     "pycharm": {
      "name": "#%%\n"
     },
@@ -295,7 +307,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -337,6 +352,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 4091,
      "status": "ok",
@@ -381,6 +397,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 16,
      "status": "ok",
@@ -412,6 +429,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 461,
      "status": "ok",
@@ -444,6 +462,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 64910,
      "status": "ok",
@@ -467,6 +486,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 4538,
      "status": "ok",
@@ -508,6 +528,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 186915,
      "status": "ok",
@@ -543,6 +564,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 18,
      "status": "ok",
@@ -577,6 +599,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 10612,
      "status": "ok",
@@ -658,6 +681,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 19,
      "status": "ok",
@@ -682,6 +706,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 7721,
      "status": "ok",
@@ -717,6 +742,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 1508,
      "status": "ok",
@@ -766,6 +792,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 5,
      "status": "ok",
@@ -789,6 +816,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 20565,
      "status": "ok",
@@ -833,6 +861,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -856,6 +885,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -900,6 +930,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -953,7 +984,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -1024,7 +1058,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.18"
+   "version": "3.9.19"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/W1D3_RemoteSensing/instructor/W1D3_Intro.ipynb b/tutorials/W1D3_RemoteSensing/instructor/W1D3_Intro.ipynb
index e442291c6..9014a229f 100644
--- a/tutorials/W1D3_RemoteSensing/instructor/W1D3_Intro.ipynb
+++ b/tutorials/W1D3_RemoteSensing/instructor/W1D3_Intro.ipynb
@@ -55,6 +55,36 @@
     "2. Access and analyze satellite remote sensing products for climate applications."
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "0f182426-9adb-4879-9d1d-99fa9cc66d6e",
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D3_Intro\""
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "52191a48",
@@ -132,6 +162,20 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "8721bc44-ac4c-45c4-b377-8243def60b82",
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Introduction_to_Remote_Sensing_Video\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "765617f2",
@@ -158,14 +202,22 @@
     "\n",
     "link_id = \"py527\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "cf8ee68d-b35e-46d9-8e77-aa275a193ced",
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Introduction_to_Remote_Sensing_Slides\")"
    ]
   }
  ],
diff --git a/tutorials/W1D3_RemoteSensing/instructor/W1D3_Tutorial1.ipynb b/tutorials/W1D3_RemoteSensing/instructor/W1D3_Tutorial1.ipynb
index 47cf2bd3d..0c4f4744b 100644
--- a/tutorials/W1D3_RemoteSensing/instructor/W1D3_Tutorial1.ipynb
+++ b/tutorials/W1D3_RemoteSensing/instructor/W1D3_Tutorial1.ipynb
@@ -50,6 +50,35 @@
     "- Appreciate the value and benefits of satellite remote sensing for climate studies through selected examples.\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D3_T1\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -117,6 +146,19 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Intro_Remote_Sensing_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -138,14 +180,21 @@
     "\n",
     "link_id = \"k6dre\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Intro_Remote_Sensing_Slides\")"
    ]
   },
   {
diff --git a/tutorials/W1D3_RemoteSensing/instructor/W1D3_Tutorial2.ipynb b/tutorials/W1D3_RemoteSensing/instructor/W1D3_Tutorial2.ipynb
index af1d2a521..a8a5e927c 100644
--- a/tutorials/W1D3_RemoteSensing/instructor/W1D3_Tutorial2.ipynb
+++ b/tutorials/W1D3_RemoteSensing/instructor/W1D3_Tutorial2.ipynb
@@ -47,6 +47,35 @@
     "- Navigate and utilize these datasets in your own climate-related studies or projects.\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D3_T2\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -105,6 +134,19 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Satellite_Climate_Data_Records_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -126,14 +168,21 @@
     "\n",
     "link_id = \"7vsqd\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Satellite_Climate_Data_Records_Slides\")"
    ]
   },
   {
@@ -263,7 +312,7 @@
     "\n",
     "Option C would be preferred. You need data that overlaps with your timeframe of interest, which eliminates Option A. In order to use data from multiple sensored the 'inter-satellite' calibration described above should be completed.\n",
     "\n",
-    "\"\"\";"
+    "\"\"\""
    ]
   },
   {
diff --git a/tutorials/W1D3_RemoteSensing/instructor/W1D3_Tutorial3.ipynb b/tutorials/W1D3_RemoteSensing/instructor/W1D3_Tutorial3.ipynb
index d551b7d6b..57fbcdcc8 100644
--- a/tutorials/W1D3_RemoteSensing/instructor/W1D3_Tutorial3.ipynb
+++ b/tutorials/W1D3_RemoteSensing/instructor/W1D3_Tutorial3.ipynb
@@ -109,6 +109,35 @@
     "import tempfile"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D3_T3\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -166,7 +195,7 @@
    },
    "outputs": [],
    "source": [
-    "# @title Video 1: Access and Vizualise Satellite CDR\n",
+    "# @title Video 1: Access and Visualize Satellite CDR\n",
     "\n",
     "from ipywidgets import widgets\n",
     "from IPython.display import YouTubeVideo\n",
@@ -214,6 +243,19 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Access_Visualize_Satellite_CDR_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -235,14 +277,21 @@
     "\n",
     "link_id = \"g9n5d\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Access_Visualize_Satellite_CDR_Slides\")"
    ]
   },
   {
@@ -280,38 +329,36 @@
     "execution": {}
    },
    "source": [
-    "TODO this needs major update! PH\n",
-    "\n",
     "If we go to the [cloud storage space (or a S3 bucket)](https://noaa-cdr-ndvi-pds.s3.amazonaws.com/index.html#data/) that hosts NOAA NDVI CDR data, you will see the pattern of how the NOAA NDVI CDR is organized:\n",
     "\n",
-    "`s3://noaa-cdr-ndvi-pds/data/2024/VIIRS-Land_v001-preliminary_NPP13C1_S-NPP_20240101_c20240110134720.nc`\n",
+    "`s3://noaa-cdr-ndvi-pds/data/2024/VIIRS-Land_v001_NPP13C1_S-NPP_20220101_c20240126162652.nc`\n",
     "\n",
     "We can take advantage of the pattern to search for the data file systematically. \n",
     "\n",
     "> Parent directory: `s3://noaa-cdr-ndvi-pds/data/`\n",
-    "> Sub-directory for each year: `2024/`\n",
-    "> File name of each day: `VIIRS-Land_v001-preliminary_NPP13C1_S-NPP_20240101_c20240110134720.nc`\n",
+    "> Sub-directory for each year: `2022/`\n",
+    "> File name of each day: `VIIRS-Land_v001_NPP13C1_S-NPP_20220101_c20240126162652.nc`\n",
     "\n",
     "The file name also has a clear pattern:\n",
     "\n",
     "> Sensor name: `VIIRS`  \n",
     "> Product category: `Land`  \n",
-    "> Product version: `v001-preliminary`  (*This might change soon*)\n",
-    "> Product type: `NPP13C1`  \n",
-    "> Satellite platform: `S-NPP`  \n",
-    "> Date of the data: `20240101`  \n",
-    "> Processing time: `c20240110134720` (*This will change for each file based on when the file was processed*)  \n",
+    "> Product version: `v001`\n",
+    "> Product type: `NPP13C1`  (*JP113C1 in 2024, so dependent on the satellite era*)\n",
+    "> Satellite platform: `S-NPP`  (*NOAA-20 in 2024, so dependent on the satellite era*)\n",
+    "> Date of the data: `20220101`  \n",
+    "> Processing time: `c20240126162652` (*This will change for each file based on when the file was processed*)  \n",
     "> File format: `.nc` (*netCDR-4 format*)\n",
     "\n",
     "In other words, if we are looking for the data of a specific day, we can easily locate where the file might be. \n",
     "\n",
-    "Note that the above example data is from 2024 and therefore very new, that is why it is called `v001-preliminary` at the moment. Quality control might soon lead to changes in the naming and availability.\n",
+    "Note that the above example data is from 2022, measurements from 2024 are very new, which is why there it was called `v001-preliminary` before. Quality control often leads to changes in the naming and availability. So be prepared that you have to check the data tree of your source regularly.\n",
     "\n",
-    "For example, if we want to find the VIIRS data for the day of *2014-03-12 (or March 12, 2014)*, you can use:\n",
+    "For example, if we now want to find the VIIRS data for the day of *2014-03-12 (or March 12, 2014)*, you can use:\n",
     "\n",
     "`s3://noaa-cdr-ndvi-pds/data/2014/VIIRS-Land_v001_NPP13C1_*_20140312_c*.nc`\n",
     "\n",
-    "You see, we had to remove the `preliminary` tag, as the `2014` data passed quality control already.\n",
+    "You see, we do not need a `preliminary` tag, as the `2014` data passed quality control already.\n",
     "\n",
     "The reason that we put `*` in the above directory is that we are not sure about what satellite platform this data is from and when the data was processed. The `*` is called a **wildcard**, and is used because we want *all* the files that contain our specific criteria, but do not want to have to specify all the other pieces of the filename we are not sure about yet. It should return all the data satisfying that initial criteria and you can refine further once you see what is available. Essentially, this first step helps to narrow down the data search.\n",
     "\n",
@@ -409,6 +456,19 @@
     "# VIIRS-Land_v001_NPP13C1_S-NPP_20190901_c20240125203558.nc"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Coding_Exercise_1_1\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -846,6 +906,19 @@
     "# )"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Coding_Exercise_1_4\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
diff --git a/tutorials/W1D3_RemoteSensing/instructor/W1D3_Tutorial4.ipynb b/tutorials/W1D3_RemoteSensing/instructor/W1D3_Tutorial4.ipynb
index 157f2818f..e97f39606 100644
--- a/tutorials/W1D3_RemoteSensing/instructor/W1D3_Tutorial4.ipynb
+++ b/tutorials/W1D3_RemoteSensing/instructor/W1D3_Tutorial4.ipynb
@@ -111,6 +111,35 @@
     "import tempfile"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D3_T4\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -216,6 +245,19 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Understanding_Climatology_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -237,14 +279,21 @@
     "\n",
     "link_id = \"2ak68\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Understanding_Climatology_Slides\")"
    ]
   },
   {
@@ -612,6 +661,19 @@
     ")"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Coding_Exercise_1_2\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -648,6 +710,19 @@
     "'''"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_1_2\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -847,6 +922,19 @@
     "\"\"\""
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_2_2\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -896,7 +984,7 @@
     "execution": {}
    },
    "source": [
-    "### Coding Exercises 2.1\n",
+    "### Coding Exercises 2.2\n",
     "\n",
     "As climate changes, the climatology of precipitation may also change. In fact, climate researchers recalculate a climatology every 10 years. This allows them to monitor how the norms of our climate system change. In this exercise, you will visualize how the climatology of our dataset changes depending on the reference period used.\n",
     "\n",
@@ -926,7 +1014,7 @@
     "\n",
     "# Define the figure and each axis for the 2 rows and 2 columns\n",
     "fig, axs = plt.subplots(\n",
-    "    nrows=2, ncols=2, subplot_kw={\"projection\": ccrs.Robinson()}, figsize=(12, 8)\n",
+    "    nrows=2, ncols=2, subplot_kw={\"projection\": ccrs.Robinson()}#, figsize=(12, 8)\n",
     ")\n",
     "\n",
     "# axs is a 2-dimensional array of `GeoAxes`. We will flatten it into a 1-D array\n",
@@ -964,7 +1052,7 @@
     "\n",
     "# Define the figure and each axis for the 2 rows and 2 columns\n",
     "fig, axs = plt.subplots(\n",
-    "    nrows=2, ncols=2, subplot_kw={\"projection\": ccrs.Robinson()}, figsize=(12, 8)\n",
+    "    nrows=2, ncols=2, subplot_kw={\"projection\": ccrs.Robinson()}#, figsize=(12, 8)\n",
     ")\n",
     "\n",
     "# axs is a 2-dimensional array of `GeoAxes`. We will flatten it into a 1-D array\n",
@@ -987,6 +1075,19 @@
     "    )"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Coding_Exercise_2_2\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
diff --git a/tutorials/W1D3_RemoteSensing/instructor/W1D3_Tutorial5.ipynb b/tutorials/W1D3_RemoteSensing/instructor/W1D3_Tutorial5.ipynb
index 354c693bf..afcfb7bea 100644
--- a/tutorials/W1D3_RemoteSensing/instructor/W1D3_Tutorial5.ipynb
+++ b/tutorials/W1D3_RemoteSensing/instructor/W1D3_Tutorial5.ipynb
@@ -112,6 +112,35 @@
     "from geoviews import Image as gvImage"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D3_T5\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -216,6 +245,19 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Calculating_Anomaly_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -237,14 +279,21 @@
     "\n",
     "link_id = \"kvdgr\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Calculating_Anomaly_Slides\")"
    ]
   },
   {
@@ -648,6 +697,19 @@
     "ax.grid(True)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Coding_Exercise_2_1\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -679,6 +741,19 @@
     "\"\"\""
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_2_1\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -812,6 +887,19 @@
     "ax.grid(True)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Coding_Exercise_2_2\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -841,6 +929,19 @@
     "\"\"\""
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_2_2\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
diff --git a/tutorials/W1D3_RemoteSensing/instructor/W1D3_Tutorial6.ipynb b/tutorials/W1D3_RemoteSensing/instructor/W1D3_Tutorial6.ipynb
index 00c65fb3c..efddf6fdd 100644
--- a/tutorials/W1D3_RemoteSensing/instructor/W1D3_Tutorial6.ipynb
+++ b/tutorials/W1D3_RemoteSensing/instructor/W1D3_Tutorial6.ipynb
@@ -110,6 +110,35 @@
     "from geoviews import Image as gvImage"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D3_T6\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -215,6 +244,19 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Satellite_Data_Climate_Variability_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -236,14 +278,21 @@
     "\n",
     "link_id = \"zkbaf\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Satellite_Data_Climate_Variability_Slides\")"
    ]
   },
   {
@@ -729,6 +778,19 @@
     "ax.legend()"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Coding_Exercise_1_2\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -757,7 +819,20 @@
     "1. The index using the 1982-2011 reference period is always a little larger than the 1991-2020 reference period curve.\n",
     "2. This means that the climatology values for the 1991-2020 reference period were larger than that of 1982-2011.\n",
     "3. This can help remove long term trends (e.g. from warming) that can obscure the anomalies and ensures the anomaly is to the correct 'normal'.\n",
-    "''';"
+    "'''"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_1_2\")"
    ]
   },
   {
diff --git a/tutorials/W1D3_RemoteSensing/instructor/W1D3_Tutorial7.ipynb b/tutorials/W1D3_RemoteSensing/instructor/W1D3_Tutorial7.ipynb
index f485e96d2..e7b591dfe 100644
--- a/tutorials/W1D3_RemoteSensing/instructor/W1D3_Tutorial7.ipynb
+++ b/tutorials/W1D3_RemoteSensing/instructor/W1D3_Tutorial7.ipynb
@@ -104,6 +104,35 @@
     "from scipy import stats"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D3_T7\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -221,6 +250,19 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Impact_of_Climate_Variability_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -242,14 +284,21 @@
     "\n",
     "link_id = \"tyjwu\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Impact_of_Climate_Variability_Slides\")"
    ]
   },
   {
@@ -701,6 +750,19 @@
     "\"\"\""
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_2\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -857,6 +919,19 @@
     "ax.set_ylabel(\"Precipitation Anomaly\\n(mm/day)\")"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Coding_Exercise_2\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
diff --git a/tutorials/W1D3_RemoteSensing/instructor/W1D3_Tutorial8.ipynb b/tutorials/W1D3_RemoteSensing/instructor/W1D3_Tutorial8.ipynb
index 7cbbca593..bda96a69a 100644
--- a/tutorials/W1D3_RemoteSensing/instructor/W1D3_Tutorial8.ipynb
+++ b/tutorials/W1D3_RemoteSensing/instructor/W1D3_Tutorial8.ipynb
@@ -122,6 +122,35 @@
     "from scipy import stats"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D3_T8\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -237,6 +266,19 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Verification_Satellite_Data_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -258,14 +300,21 @@
     "\n",
     "link_id = \"w3r49\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Verification_Satellite_Data_Slides\")"
    ]
   },
   {
@@ -860,7 +909,7 @@
     "ax.legend()\n",
     "\n",
     "# plot the scatter plot between nClimGrid and GPCP monthly precipitation CDR\n",
-    "fig, ax = plt.subplots(figsize=(12, 6))\n",
+    "fig, ax = plt.subplots()\n",
     "fig.suptitle(\"GPCP Precipitaion v.s. nClimGrid\")\n",
     "# ax.scatter(sat_clim_anom, obs_clim_anom, alpha=0.6)\n",
     "# Add 1:1 line\n",
@@ -917,7 +966,7 @@
     "ax.legend()\n",
     "\n",
     "# plot the scatter plot between nClimGrid and GPCP monthly precipitation CDR\n",
-    "fig, ax = plt.subplots(figsize=(12, 6))\n",
+    "fig, ax = plt.subplots()\n",
     "fig.suptitle(\"GPCP Precipitaion v.s. nClimGrid\")\n",
     "ax.scatter(sat_clim_anom, obs_clim_anom, alpha=0.6)\n",
     "# Add 1:1 line\n",
@@ -934,6 +983,19 @@
     "print(\"Corr Coef: \" + str(r) + \", p-val: \" + str(p))"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Coding_Exercise_1_5\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
diff --git a/tutorials/W1D3_RemoteSensing/solutions/W1D3_Tutorial2_Solution_1c4dc0c2.py b/tutorials/W1D3_RemoteSensing/solutions/W1D3_Tutorial2_Solution_a52e3825.py
similarity index 98%
rename from tutorials/W1D3_RemoteSensing/solutions/W1D3_Tutorial2_Solution_1c4dc0c2.py
rename to tutorials/W1D3_RemoteSensing/solutions/W1D3_Tutorial2_Solution_a52e3825.py
index d3962f651..2fff56b88 100644
--- a/tutorials/W1D3_RemoteSensing/solutions/W1D3_Tutorial2_Solution_1c4dc0c2.py
+++ b/tutorials/W1D3_RemoteSensing/solutions/W1D3_Tutorial2_Solution_a52e3825.py
@@ -3,4 +3,4 @@
 
 Option C would be preferred. You need data that overlaps with your timeframe of interest, which eliminates Option A. In order to use data from multiple sensored the 'inter-satellite' calibration described above should be completed.
 
-""";
\ No newline at end of file
+"""
\ No newline at end of file
diff --git a/tutorials/W1D3_RemoteSensing/solutions/W1D3_Tutorial4_Solution_2e446fac.py b/tutorials/W1D3_RemoteSensing/solutions/W1D3_Tutorial4_Solution_f1c5c17b.py
similarity index 98%
rename from tutorials/W1D3_RemoteSensing/solutions/W1D3_Tutorial4_Solution_2e446fac.py
rename to tutorials/W1D3_RemoteSensing/solutions/W1D3_Tutorial4_Solution_f1c5c17b.py
index 423fc44e9..6fc57cb34 100644
--- a/tutorials/W1D3_RemoteSensing/solutions/W1D3_Tutorial4_Solution_2e446fac.py
+++ b/tutorials/W1D3_RemoteSensing/solutions/W1D3_Tutorial4_Solution_f1c5c17b.py
@@ -13,7 +13,7 @@
 
 # Define the figure and each axis for the 2 rows and 2 columns
 fig, axs = plt.subplots(
-    nrows=2, ncols=2, subplot_kw={"projection": ccrs.Robinson()}, figsize=(12, 8)
+    nrows=2, ncols=2, subplot_kw={"projection": ccrs.Robinson()}#, figsize=(12, 8)
 )
 
 # axs is a 2-dimensional array of `GeoAxes`. We will flatten it into a 1-D array
diff --git a/tutorials/W1D3_RemoteSensing/solutions/W1D3_Tutorial6_Solution_6b7276d7.py b/tutorials/W1D3_RemoteSensing/solutions/W1D3_Tutorial6_Solution_52e2ab81.py
similarity index 98%
rename from tutorials/W1D3_RemoteSensing/solutions/W1D3_Tutorial6_Solution_6b7276d7.py
rename to tutorials/W1D3_RemoteSensing/solutions/W1D3_Tutorial6_Solution_52e2ab81.py
index 4c8d5c6d5..cbf1ea617 100644
--- a/tutorials/W1D3_RemoteSensing/solutions/W1D3_Tutorial6_Solution_6b7276d7.py
+++ b/tutorials/W1D3_RemoteSensing/solutions/W1D3_Tutorial6_Solution_52e2ab81.py
@@ -3,4 +3,4 @@
 1. The index using the 1982-2011 reference period is always a little larger than the 1991-2020 reference period curve.
 2. This means that the climatology values for the 1991-2020 reference period were larger than that of 1982-2011.
 3. This can help remove long term trends (e.g. from warming) that can obscure the anomalies and ensures the anomaly is to the correct 'normal'.
-''';
\ No newline at end of file
+'''
\ No newline at end of file
diff --git a/tutorials/W1D3_RemoteSensing/solutions/W1D3_Tutorial8_Solution_c234e6bc.py b/tutorials/W1D3_RemoteSensing/solutions/W1D3_Tutorial8_Solution_7b345f8a.py
similarity index 97%
rename from tutorials/W1D3_RemoteSensing/solutions/W1D3_Tutorial8_Solution_c234e6bc.py
rename to tutorials/W1D3_RemoteSensing/solutions/W1D3_Tutorial8_Solution_7b345f8a.py
index 23c2d0654..af944a32f 100644
--- a/tutorials/W1D3_RemoteSensing/solutions/W1D3_Tutorial8_Solution_c234e6bc.py
+++ b/tutorials/W1D3_RemoteSensing/solutions/W1D3_Tutorial8_Solution_7b345f8a.py
@@ -26,7 +26,7 @@
 ax.legend()
 
 # plot the scatter plot between nClimGrid and GPCP monthly precipitation CDR
-fig, ax = plt.subplots(figsize=(12, 6))
+fig, ax = plt.subplots()
 fig.suptitle("GPCP Precipitaion v.s. nClimGrid")
 ax.scatter(sat_clim_anom, obs_clim_anom, alpha=0.6)
 # Add 1:1 line
diff --git a/tutorials/W1D3_RemoteSensing/static/W1D3_Tutorial4_Solution_2e446fac_0.png b/tutorials/W1D3_RemoteSensing/static/W1D3_Tutorial4_Solution_2e446fac_0.png
deleted file mode 100644
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diff --git a/tutorials/W1D3_RemoteSensing/static/W1D3_Tutorial8_Solution_c234e6bc_2.png b/tutorials/W1D3_RemoteSensing/static/W1D3_Tutorial8_Solution_7b345f8a_2.png
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rename to tutorials/W1D3_RemoteSensing/static/W1D3_Tutorial8_Solution_7b345f8a_2.png
diff --git a/tutorials/W1D3_RemoteSensing/static/W1D3_Tutorial8_Solution_7b345f8a_3.png b/tutorials/W1D3_RemoteSensing/static/W1D3_Tutorial8_Solution_7b345f8a_3.png
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zoMBbyo(zdxho+wzbR!clEyR~5CMGtWX^eqXg}c9otE~L%uYD(_;hl|2y~?$x$4+3-
z129`X5vBBvI`PA0&{4AK361aB^n+9@S(gxGSC=fPv#&R42a6bGPAxP=YYXlQ!+GIv
zyXeNH&w!a&6+5#78oA9*Qg83N#0wmQHdc;$1*&~5Iy#zJwIK@K6X675XilgLT8KwZ
zitR)=967wt+{%fEz1O@&%(d8aN(G7w_C9a}dbPB+#-k@ew``)f-bF$c<!CL8M2Mx=
zzGcUkAvZZWGc#DqV~X|eg8gvJyR#`lm@M6hgZYPrY3u9rc64-*`4(v=qq|vy-}z(5
zFQ^~~tV$o()a><?%$|1q5k%BKI9Suua|ce2=fqC3?wA~Nb91%4*_xeYm!!eaYq2E4
zZ{1oB>%%n7cqxGW`htLrGl|K`GAb&95a{+`_X0G|u7Lq=>;kyk5Hi0MhE@&A8g>!*
zU>|_0npy&edBOVUj$tOIq*URlSoI@VCxDE**o|d$UF>ctDJ>=EVY|8c7%!4kwj-+6
z%kUh~RfQ~Ox%v3&@Cu7VL++mus7C~z$eI`w$Y?;LS|A9riVi~BT3VdE(&|vgPrXHZ
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z?R@`4<Ff^P&<Z++Zco<u<>-t-2mvNv99=1IAb`j!O2zJQ7es5^X8mi@&4=0HC@l#v
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z7-fe>3Uep$d5PO-rN6+}Z9;knJl@Bik291H7TMRI^yx$|oKLc=fsJeiF-g{2e=hi2
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mN3}Ej?^Iem^8eFIom-Z^=kaipSJ4hOd}w?1HM4df@%~>DsNWp`

diff --git a/tutorials/W1D3_RemoteSensing/student/W1D3_Intro.ipynb b/tutorials/W1D3_RemoteSensing/student/W1D3_Intro.ipynb
index 16d4e3262..ef3e87dcb 100644
--- a/tutorials/W1D3_RemoteSensing/student/W1D3_Intro.ipynb
+++ b/tutorials/W1D3_RemoteSensing/student/W1D3_Intro.ipynb
@@ -55,6 +55,36 @@
     "2. Access and analyze satellite remote sensing products for climate applications."
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "0f182426-9adb-4879-9d1d-99fa9cc66d6e",
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D3_Intro\""
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "52191a48",
@@ -132,6 +162,20 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "8721bc44-ac4c-45c4-b377-8243def60b82",
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Introduction_to_Remote_Sensing_Video\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "765617f2",
@@ -158,14 +202,22 @@
     "\n",
     "link_id = \"py527\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "cf8ee68d-b35e-46d9-8e77-aa275a193ced",
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Introduction_to_Remote_Sensing_Slides\")"
    ]
   }
  ],
diff --git a/tutorials/W1D3_RemoteSensing/student/W1D3_Tutorial1.ipynb b/tutorials/W1D3_RemoteSensing/student/W1D3_Tutorial1.ipynb
index d597d75a6..7f1fac337 100644
--- a/tutorials/W1D3_RemoteSensing/student/W1D3_Tutorial1.ipynb
+++ b/tutorials/W1D3_RemoteSensing/student/W1D3_Tutorial1.ipynb
@@ -50,6 +50,35 @@
     "- Appreciate the value and benefits of satellite remote sensing for climate studies through selected examples.\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D3_T1\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -117,6 +146,19 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Intro_Remote_Sensing_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -138,14 +180,21 @@
     "\n",
     "link_id = \"k6dre\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Intro_Remote_Sensing_Slides\")"
    ]
   },
   {
@@ -303,7 +352,7 @@
     "tags": []
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/solutions/W1D3_Tutorial1_Solution_cd96f472.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D3_RemoteSensing/solutions/W1D3_Tutorial1_Solution_cd96f472.py)\n",
     "\n"
    ]
   },
diff --git a/tutorials/W1D3_RemoteSensing/student/W1D3_Tutorial2.ipynb b/tutorials/W1D3_RemoteSensing/student/W1D3_Tutorial2.ipynb
index 759351547..122df0f09 100644
--- a/tutorials/W1D3_RemoteSensing/student/W1D3_Tutorial2.ipynb
+++ b/tutorials/W1D3_RemoteSensing/student/W1D3_Tutorial2.ipynb
@@ -47,6 +47,35 @@
     "- Navigate and utilize these datasets in your own climate-related studies or projects.\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D3_T2\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -105,6 +134,19 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Satellite_Climate_Data_Records_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -126,14 +168,21 @@
     "\n",
     "link_id = \"7vsqd\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Satellite_Climate_Data_Records_Slides\")"
    ]
   },
   {
@@ -256,7 +305,7 @@
     "tags": []
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/solutions/W1D3_Tutorial2_Solution_1c4dc0c2.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D3_RemoteSensing/solutions/W1D3_Tutorial2_Solution_a52e3825.py)\n",
     "\n"
    ]
   },
diff --git a/tutorials/W1D3_RemoteSensing/student/W1D3_Tutorial3.ipynb b/tutorials/W1D3_RemoteSensing/student/W1D3_Tutorial3.ipynb
index fb36287f5..fdd85f344 100644
--- a/tutorials/W1D3_RemoteSensing/student/W1D3_Tutorial3.ipynb
+++ b/tutorials/W1D3_RemoteSensing/student/W1D3_Tutorial3.ipynb
@@ -109,6 +109,35 @@
     "import tempfile"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D3_T3\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -166,7 +195,7 @@
    },
    "outputs": [],
    "source": [
-    "# @title Video 1: Access and Vizualise Satellite CDR\n",
+    "# @title Video 1: Access and Visualize Satellite CDR\n",
     "\n",
     "from ipywidgets import widgets\n",
     "from IPython.display import YouTubeVideo\n",
@@ -214,6 +243,19 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Access_Visualize_Satellite_CDR_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -235,14 +277,21 @@
     "\n",
     "link_id = \"g9n5d\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Access_Visualize_Satellite_CDR_Slides\")"
    ]
   },
   {
@@ -280,38 +329,36 @@
     "execution": {}
    },
    "source": [
-    "TODO this needs major update! PH\n",
-    "\n",
     "If we go to the [cloud storage space (or a S3 bucket)](https://noaa-cdr-ndvi-pds.s3.amazonaws.com/index.html#data/) that hosts NOAA NDVI CDR data, you will see the pattern of how the NOAA NDVI CDR is organized:\n",
     "\n",
-    "`s3://noaa-cdr-ndvi-pds/data/2024/VIIRS-Land_v001-preliminary_NPP13C1_S-NPP_20240101_c20240110134720.nc`\n",
+    "`s3://noaa-cdr-ndvi-pds/data/2024/VIIRS-Land_v001_NPP13C1_S-NPP_20220101_c20240126162652.nc`\n",
     "\n",
     "We can take advantage of the pattern to search for the data file systematically. \n",
     "\n",
     "> Parent directory: `s3://noaa-cdr-ndvi-pds/data/`\n",
-    "> Sub-directory for each year: `2024/`\n",
-    "> File name of each day: `VIIRS-Land_v001-preliminary_NPP13C1_S-NPP_20240101_c20240110134720.nc`\n",
+    "> Sub-directory for each year: `2022/`\n",
+    "> File name of each day: `VIIRS-Land_v001_NPP13C1_S-NPP_20220101_c20240126162652.nc`\n",
     "\n",
     "The file name also has a clear pattern:\n",
     "\n",
     "> Sensor name: `VIIRS`  \n",
     "> Product category: `Land`  \n",
-    "> Product version: `v001-preliminary`  (*This might change soon*)\n",
-    "> Product type: `NPP13C1`  \n",
-    "> Satellite platform: `S-NPP`  \n",
-    "> Date of the data: `20240101`  \n",
-    "> Processing time: `c20240110134720` (*This will change for each file based on when the file was processed*)  \n",
+    "> Product version: `v001`\n",
+    "> Product type: `NPP13C1`  (*JP113C1 in 2024, so dependent on the satellite era*)\n",
+    "> Satellite platform: `S-NPP`  (*NOAA-20 in 2024, so dependent on the satellite era*)\n",
+    "> Date of the data: `20220101`  \n",
+    "> Processing time: `c20240126162652` (*This will change for each file based on when the file was processed*)  \n",
     "> File format: `.nc` (*netCDR-4 format*)\n",
     "\n",
     "In other words, if we are looking for the data of a specific day, we can easily locate where the file might be. \n",
     "\n",
-    "Note that the above example data is from 2024 and therefore very new, that is why it is called `v001-preliminary` at the moment. Quality control might soon lead to changes in the naming and availability.\n",
+    "Note that the above example data is from 2022, measurements from 2024 are very new, which is why there it was called `v001-preliminary` before. Quality control often leads to changes in the naming and availability. So be prepared that you have to check the data tree of your source regularly.\n",
     "\n",
-    "For example, if we want to find the VIIRS data for the day of *2014-03-12 (or March 12, 2014)*, you can use:\n",
+    "For example, if we now want to find the VIIRS data for the day of *2014-03-12 (or March 12, 2014)*, you can use:\n",
     "\n",
     "`s3://noaa-cdr-ndvi-pds/data/2014/VIIRS-Land_v001_NPP13C1_*_20140312_c*.nc`\n",
     "\n",
-    "You see, we had to remove the `preliminary` tag, as the `2014` data passed quality control already.\n",
+    "You see, we do not need a `preliminary` tag, as the `2014` data passed quality control already.\n",
     "\n",
     "The reason that we put `*` in the above directory is that we are not sure about what satellite platform this data is from and when the data was processed. The `*` is called a **wildcard**, and is used because we want *all* the files that contain our specific criteria, but do not want to have to specify all the other pieces of the filename we are not sure about yet. It should return all the data satisfying that initial criteria and you can refine further once you see what is available. Essentially, this first step helps to narrow down the data search.\n",
     "\n",
@@ -387,10 +434,23 @@
     "tags": []
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/solutions/W1D3_Tutorial3_Solution_0726ff4a.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D3_RemoteSensing/solutions/W1D3_Tutorial3_Solution_0726ff4a.py)\n",
     "\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Coding_Exercise_1_1\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -786,10 +846,23 @@
     "tags": []
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/solutions/W1D3_Tutorial3_Solution_509be09f.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D3_RemoteSensing/solutions/W1D3_Tutorial3_Solution_509be09f.py)\n",
     "\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Coding_Exercise_1_4\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
diff --git a/tutorials/W1D3_RemoteSensing/student/W1D3_Tutorial4.ipynb b/tutorials/W1D3_RemoteSensing/student/W1D3_Tutorial4.ipynb
index bb19550a4..a292318e3 100644
--- a/tutorials/W1D3_RemoteSensing/student/W1D3_Tutorial4.ipynb
+++ b/tutorials/W1D3_RemoteSensing/student/W1D3_Tutorial4.ipynb
@@ -111,6 +111,35 @@
     "import tempfile"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D3_T4\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -216,6 +245,19 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Understanding_Climatology_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -237,14 +279,21 @@
     "\n",
     "link_id = \"2ak68\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Understanding_Climatology_Slides\")"
    ]
   },
   {
@@ -586,14 +635,27 @@
     "tags": []
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/solutions/W1D3_Tutorial4_Solution_8041e1ae.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D3_RemoteSensing/solutions/W1D3_Tutorial4_Solution_8041e1ae.py)\n",
     "\n",
     "*Example output:*\n",
     "\n",
-    "<img alt='Solution hint' align='left' width=775.0 height=347.0 src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/static/W1D3_Tutorial4_Solution_8041e1ae_0.png>\n",
+    "<img alt='Solution hint' align='left' width=775.0 height=347.0 src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D3_RemoteSensing/static/W1D3_Tutorial4_Solution_8041e1ae_0.png>\n",
     "\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Coding_Exercise_1_2\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -621,10 +683,23 @@
     "tags": []
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/solutions/W1D3_Tutorial4_Solution_de0347ea.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D3_RemoteSensing/solutions/W1D3_Tutorial4_Solution_de0347ea.py)\n",
     "\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_1_2\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -813,10 +888,23 @@
     "tags": []
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/solutions/W1D3_Tutorial4_Solution_213928a9.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D3_RemoteSensing/solutions/W1D3_Tutorial4_Solution_213928a9.py)\n",
     "\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_2_2\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -866,7 +954,7 @@
     "execution": {}
    },
    "source": [
-    "### Coding Exercises 2.1\n",
+    "### Coding Exercises 2.2\n",
     "\n",
     "As climate changes, the climatology of precipitation may also change. In fact, climate researchers recalculate a climatology every 10 years. This allows them to monitor how the norms of our climate system change. In this exercise, you will visualize how the climatology of our dataset changes depending on the reference period used.\n",
     "\n",
@@ -896,7 +984,7 @@
     "\n",
     "# Define the figure and each axis for the 2 rows and 2 columns\n",
     "fig, axs = plt.subplots(\n",
-    "    nrows=2, ncols=2, subplot_kw={\"projection\": ccrs.Robinson()}, figsize=(12, 8)\n",
+    "    nrows=2, ncols=2, subplot_kw={\"projection\": ccrs.Robinson()}#, figsize=(12, 8)\n",
     ")\n",
     "\n",
     "# axs is a 2-dimensional array of `GeoAxes`. We will flatten it into a 1-D array\n",
@@ -915,14 +1003,27 @@
     "tags": []
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/solutions/W1D3_Tutorial4_Solution_2e446fac.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D3_RemoteSensing/solutions/W1D3_Tutorial4_Solution_f1c5c17b.py)\n",
     "\n",
     "*Example output:*\n",
     "\n",
-    "<img alt='Solution hint' align='left' width=1176.0 height=574.0 src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/static/W1D3_Tutorial4_Solution_2e446fac_0.png>\n",
+    "<img alt='Solution hint' align='left' width=792.0 height=421.0 src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D3_RemoteSensing/static/W1D3_Tutorial4_Solution_f1c5c17b_0.png>\n",
     "\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Coding_Exercise_2_2\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
diff --git a/tutorials/W1D3_RemoteSensing/student/W1D3_Tutorial5.ipynb b/tutorials/W1D3_RemoteSensing/student/W1D3_Tutorial5.ipynb
index d85ff2629..fb701877f 100644
--- a/tutorials/W1D3_RemoteSensing/student/W1D3_Tutorial5.ipynb
+++ b/tutorials/W1D3_RemoteSensing/student/W1D3_Tutorial5.ipynb
@@ -112,6 +112,35 @@
     "from geoviews import Image as gvImage"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D3_T5\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -216,6 +245,19 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Calculating_Anomaly_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -237,14 +279,21 @@
     "\n",
     "link_id = \"kvdgr\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Calculating_Anomaly_Slides\")"
    ]
   },
   {
@@ -625,14 +674,27 @@
     "execution": {}
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/solutions/W1D3_Tutorial5_Solution_b9708e8c.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D3_RemoteSensing/solutions/W1D3_Tutorial5_Solution_b9708e8c.py)\n",
     "\n",
     "*Example output:*\n",
     "\n",
-    "<img alt='Solution hint' align='left' width=774.0 height=575.0 src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/static/W1D3_Tutorial5_Solution_b9708e8c_0.png>\n",
+    "<img alt='Solution hint' align='left' width=774.0 height=575.0 src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D3_RemoteSensing/static/W1D3_Tutorial5_Solution_b9708e8c_0.png>\n",
     "\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Coding_Exercise_2_1\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -653,10 +715,23 @@
     "tags": []
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/solutions/W1D3_Tutorial5_Solution_ccba41a0.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D3_RemoteSensing/solutions/W1D3_Tutorial5_Solution_ccba41a0.py)\n",
     "\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_2_1\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -764,14 +839,27 @@
     "execution": {}
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/solutions/W1D3_Tutorial5_Solution_ddf4939d.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D3_RemoteSensing/solutions/W1D3_Tutorial5_Solution_ddf4939d.py)\n",
     "\n",
     "*Example output:*\n",
     "\n",
-    "<img alt='Solution hint' align='left' width=775.0 height=575.0 src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/static/W1D3_Tutorial5_Solution_ddf4939d_0.png>\n",
+    "<img alt='Solution hint' align='left' width=775.0 height=575.0 src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D3_RemoteSensing/static/W1D3_Tutorial5_Solution_ddf4939d_0.png>\n",
     "\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Coding_Exercise_2_2\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -791,10 +879,23 @@
     "tags": []
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/solutions/W1D3_Tutorial5_Solution_ecc3a416.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D3_RemoteSensing/solutions/W1D3_Tutorial5_Solution_ecc3a416.py)\n",
     "\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_2_2\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
diff --git a/tutorials/W1D3_RemoteSensing/student/W1D3_Tutorial6.ipynb b/tutorials/W1D3_RemoteSensing/student/W1D3_Tutorial6.ipynb
index fe8a635b6..d96d12d86 100644
--- a/tutorials/W1D3_RemoteSensing/student/W1D3_Tutorial6.ipynb
+++ b/tutorials/W1D3_RemoteSensing/student/W1D3_Tutorial6.ipynb
@@ -110,6 +110,35 @@
     "from geoviews import Image as gvImage"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D3_T6\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -215,6 +244,19 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Satellite_Data_Climate_Variability_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -236,14 +278,21 @@
     "\n",
     "link_id = \"zkbaf\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Satellite_Data_Climate_Variability_Slides\")"
    ]
   },
   {
@@ -693,14 +742,27 @@
     "tags": []
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/solutions/W1D3_Tutorial6_Solution_3efa1010.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D3_RemoteSensing/solutions/W1D3_Tutorial6_Solution_3efa1010.py)\n",
     "\n",
     "*Example output:*\n",
     "\n",
-    "<img alt='Solution hint' align='left' width=775.0 height=575.0 src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/static/W1D3_Tutorial6_Solution_3efa1010_2.png>\n",
+    "<img alt='Solution hint' align='left' width=775.0 height=575.0 src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D3_RemoteSensing/static/W1D3_Tutorial6_Solution_3efa1010_2.png>\n",
     "\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Coding_Exercise_1_2\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -722,10 +784,23 @@
     "tags": []
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/solutions/W1D3_Tutorial6_Solution_6b7276d7.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D3_RemoteSensing/solutions/W1D3_Tutorial6_Solution_52e2ab81.py)\n",
     "\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_1_2\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
diff --git a/tutorials/W1D3_RemoteSensing/student/W1D3_Tutorial7.ipynb b/tutorials/W1D3_RemoteSensing/student/W1D3_Tutorial7.ipynb
index 6cb2a604a..e29930f3e 100644
--- a/tutorials/W1D3_RemoteSensing/student/W1D3_Tutorial7.ipynb
+++ b/tutorials/W1D3_RemoteSensing/student/W1D3_Tutorial7.ipynb
@@ -104,6 +104,35 @@
     "from scipy import stats"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D3_T7\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -221,6 +250,19 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Impact_of_Climate_Variability_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -242,14 +284,21 @@
     "\n",
     "link_id = \"tyjwu\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Impact_of_Climate_Variability_Slides\")"
    ]
   },
   {
@@ -692,10 +741,23 @@
     "tags": []
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/solutions/W1D3_Tutorial7_Solution_0feb6e7c.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D3_RemoteSensing/solutions/W1D3_Tutorial7_Solution_0feb6e7c.py)\n",
     "\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_2\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -783,16 +845,29 @@
     "tags": []
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/solutions/W1D3_Tutorial7_Solution_b556d229.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D3_RemoteSensing/solutions/W1D3_Tutorial7_Solution_b556d229.py)\n",
     "\n",
     "*Example output:*\n",
     "\n",
-    "<img alt='Solution hint' align='left' width=775.0 height=585.0 src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/static/W1D3_Tutorial7_Solution_b556d229_2.png>\n",
+    "<img alt='Solution hint' align='left' width=775.0 height=585.0 src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D3_RemoteSensing/static/W1D3_Tutorial7_Solution_b556d229_2.png>\n",
     "\n",
-    "<img alt='Solution hint' align='left' width=775.0 height=585.0 src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/static/W1D3_Tutorial7_Solution_b556d229_3.png>\n",
+    "<img alt='Solution hint' align='left' width=775.0 height=585.0 src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D3_RemoteSensing/static/W1D3_Tutorial7_Solution_b556d229_3.png>\n",
     "\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Coding_Exercise_2\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
diff --git a/tutorials/W1D3_RemoteSensing/student/W1D3_Tutorial8.ipynb b/tutorials/W1D3_RemoteSensing/student/W1D3_Tutorial8.ipynb
index ec71a25b7..52020301f 100644
--- a/tutorials/W1D3_RemoteSensing/student/W1D3_Tutorial8.ipynb
+++ b/tutorials/W1D3_RemoteSensing/student/W1D3_Tutorial8.ipynb
@@ -122,6 +122,35 @@
     "from scipy import stats"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D3_T8\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -237,6 +266,19 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Verification_Satellite_Data_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -258,14 +300,21 @@
     "\n",
     "link_id = \"w3r49\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Verification_Satellite_Data_Slides\")"
    ]
   },
   {
@@ -860,7 +909,7 @@
     "ax.legend()\n",
     "\n",
     "# plot the scatter plot between nClimGrid and GPCP monthly precipitation CDR\n",
-    "fig, ax = plt.subplots(figsize=(12, 6))\n",
+    "fig, ax = plt.subplots()\n",
     "fig.suptitle(\"GPCP Precipitaion v.s. nClimGrid\")\n",
     "# ax.scatter(sat_clim_anom, obs_clim_anom, alpha=0.6)\n",
     "# Add 1:1 line\n",
@@ -885,16 +934,29 @@
     "tags": []
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/solutions/W1D3_Tutorial8_Solution_c234e6bc.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D3_RemoteSensing/solutions/W1D3_Tutorial8_Solution_7b345f8a.py)\n",
     "\n",
     "*Example output:*\n",
     "\n",
-    "<img alt='Solution hint' align='left' width=774.0 height=575.0 src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/static/W1D3_Tutorial8_Solution_c234e6bc_2.png>\n",
+    "<img alt='Solution hint' align='left' width=774.0 height=575.0 src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D3_RemoteSensing/static/W1D3_Tutorial8_Solution_7b345f8a_2.png>\n",
     "\n",
-    "<img alt='Solution hint' align='left' width=1174.0 height=585.0 src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D3_RemoteSensingLandOceanandAtmosphere/static/W1D3_Tutorial8_Solution_c234e6bc_3.png>\n",
+    "<img alt='Solution hint' align='left' width=775.0 height=585.0 src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D3_RemoteSensing/static/W1D3_Tutorial8_Solution_7b345f8a_3.png>\n",
     "\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Coding_Exercise_1_5\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
diff --git a/tutorials/W1D4_Paleoclimate/W1D4_Intro.ipynb b/tutorials/W1D4_Paleoclimate/W1D4_Intro.ipynb
index 7cce61a03..c1c1b54ed 100644
--- a/tutorials/W1D4_Paleoclimate/W1D4_Intro.ipynb
+++ b/tutorials/W1D4_Paleoclimate/W1D4_Intro.ipynb
@@ -62,7 +62,10 @@
    "cell_type": "code",
    "execution_count": null,
    "id": "eb2c1de5-858c-41e5-81b9-4909854dbd27",
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Install and import feedback gadget\n",
@@ -100,7 +103,8 @@
    "execution_count": null,
    "id": "8cc5bcaf",
    "metadata": {
-    "cellView": "form"
+    "cellView": "form",
+    "execution": {}
    },
    "outputs": [],
    "source": [
@@ -156,7 +160,10 @@
    "cell_type": "code",
    "execution_count": null,
    "id": "5794e217-8ac9-4391-becc-685aeaa33ba4",
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -178,7 +185,8 @@
    "execution_count": null,
    "id": "9e57e0a2",
    "metadata": {
-    "cellView": "form"
+    "cellView": "form",
+    "execution": {}
    },
    "outputs": [],
    "source": [
@@ -196,7 +204,10 @@
    "cell_type": "code",
    "execution_count": null,
    "id": "2562974f-c9a0-4d70-91b6-87f22e0d2276",
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -231,7 +242,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.18"
+   "version": "3.9.19"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/W1D4_Paleoclimate/W1D4_Tutorial1.ipynb b/tutorials/W1D4_Paleoclimate/W1D4_Tutorial1.ipynb
index 8bae1dce3..8cbc63db6 100644
--- a/tutorials/W1D4_Paleoclimate/W1D4_Tutorial1.ipynb
+++ b/tutorials/W1D4_Paleoclimate/W1D4_Tutorial1.ipynb
@@ -60,7 +60,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# installations ( uncomment and run this cell ONLY when using google colab or kaggle )\n",
@@ -72,7 +74,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# imports\n",
@@ -92,7 +96,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Install and import feedback gadget\n",
@@ -119,7 +126,8 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "form"
+    "cellView": "form",
+    "execution": {}
    },
    "outputs": [],
    "source": [
@@ -136,7 +144,8 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "form"
+    "cellView": "form",
+    "execution": {}
    },
    "outputs": [],
    "source": [
@@ -255,6 +264,7 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -319,7 +329,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -331,6 +344,7 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
+    "execution": {},
     "pycharm": {
      "name": "#%%\n"
     },
@@ -353,7 +367,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -408,7 +425,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# Set the name to save the PAGES2K data\n",
@@ -439,6 +458,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 139313,
      "status": "ok",
@@ -474,6 +494,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 628,
      "status": "ok",
@@ -515,6 +536,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 5407,
      "status": "ok",
@@ -623,7 +645,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# to_remove explanation\n",
@@ -637,7 +661,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -706,7 +733,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.18"
+   "version": "3.9.19"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/W1D4_Paleoclimate/W1D4_Tutorial2.ipynb b/tutorials/W1D4_Paleoclimate/W1D4_Tutorial2.ipynb
index 75b7de88e..72200afc1 100644
--- a/tutorials/W1D4_Paleoclimate/W1D4_Tutorial2.ipynb
+++ b/tutorials/W1D4_Paleoclimate/W1D4_Tutorial2.ipynb
@@ -84,7 +84,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# installations ( uncomment and run this cell ONLY when using google colab or kaggle )\n",
@@ -96,7 +98,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# imports\n",
@@ -115,7 +119,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Install and import feedback gadget\n",
@@ -142,7 +149,8 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "form"
+    "cellView": "form",
+    "execution": {}
    },
    "outputs": [],
    "source": [
@@ -159,7 +167,8 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "form"
+    "cellView": "form",
+    "execution": {}
    },
    "outputs": [],
    "source": [
@@ -187,6 +196,7 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -242,7 +252,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -254,6 +267,7 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
+    "execution": {},
     "pycharm": {
      "name": "#%%\n"
     },
@@ -276,7 +290,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -312,7 +329,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# select data for the month of interest\n",
@@ -423,6 +442,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 1031,
      "status": "ok",
@@ -475,7 +495,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "ts_palmyra = pyleo.Series(\n",
@@ -501,7 +523,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "palmyra_stnd = ts_palmyra.standardize()\n",
@@ -522,7 +546,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# Download the data using the url\n",
@@ -550,7 +576,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "ts_line = pyleo.Series(\n",
@@ -567,7 +595,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "line_stnd = ts_line.standardize()\n",
@@ -588,7 +618,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# combine into a list\n",
@@ -598,7 +630,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# create multiseries\n",
@@ -609,6 +643,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 942,
      "status": "ok",
@@ -647,7 +682,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# to_remove explanation\n",
@@ -661,7 +698,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -690,6 +730,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 409,
      "status": "ok",
@@ -777,7 +818,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.18"
+   "version": "3.9.19"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/W1D4_Paleoclimate/W1D4_Tutorial3.ipynb b/tutorials/W1D4_Paleoclimate/W1D4_Tutorial3.ipynb
index 63de7db98..2e587aa07 100644
--- a/tutorials/W1D4_Paleoclimate/W1D4_Tutorial3.ipynb
+++ b/tutorials/W1D4_Paleoclimate/W1D4_Tutorial3.ipynb
@@ -60,7 +60,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# installations ( uncomment and run this cell ONLY when using google colab or kaggle )\n",
@@ -73,7 +75,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# imports\n",
@@ -93,7 +97,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Install and import feedback gadget\n",
@@ -120,7 +127,8 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "form"
+    "cellView": "form",
+    "execution": {}
    },
    "outputs": [],
    "source": [
@@ -137,7 +145,8 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "form"
+    "cellView": "form",
+    "execution": {}
    },
    "outputs": [],
    "source": [
@@ -179,6 +188,7 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -243,7 +253,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -255,6 +268,7 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
+    "execution": {},
     "pycharm": {
      "name": "#%%\n"
     },
@@ -277,7 +291,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -298,7 +315,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# set the name to save the Euro2k data\n",
@@ -317,7 +336,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# the LiPD object can be used to load datasets stored in the LiPD format.\n",
@@ -347,7 +368,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "def filter_data(dataset, archive_type, variable_name):\n",
@@ -392,7 +415,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "ts_list = d_euro.to_tso()"
@@ -410,7 +435,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# look at available entries for just one time-series\n",
@@ -420,7 +447,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# print relevant information for all entries\n",
@@ -442,6 +471,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 163,
      "status": "ok",
@@ -473,6 +503,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 187,
      "status": "ok",
@@ -503,6 +534,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 200,
      "status": "ok",
@@ -534,7 +566,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# initiate plot\n",
@@ -606,7 +640,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# to_remove solution\n",
@@ -675,7 +711,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -694,7 +733,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# standardize the data\n",
@@ -718,6 +759,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 4905,
      "status": "ok",
@@ -788,7 +830,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# to_remove explanation\n",
@@ -804,7 +848,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -871,7 +918,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.18"
+   "version": "3.9.19"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/W1D4_Paleoclimate/W1D4_Tutorial4.ipynb b/tutorials/W1D4_Paleoclimate/W1D4_Tutorial4.ipynb
index 8280b8098..234760ef0 100644
--- a/tutorials/W1D4_Paleoclimate/W1D4_Tutorial4.ipynb
+++ b/tutorials/W1D4_Paleoclimate/W1D4_Tutorial4.ipynb
@@ -59,7 +59,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# installations ( uncomment and run this cell ONLY when using google colab or kaggle )\n",
@@ -70,7 +72,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# imports\n",
@@ -85,7 +89,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Install and import feedback gadget\n",
@@ -112,7 +119,8 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "form"
+    "cellView": "form",
+    "execution": {}
    },
    "outputs": [],
    "source": [
@@ -129,7 +137,8 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "form"
+    "cellView": "form",
+    "execution": {}
    },
    "outputs": [],
    "source": [
@@ -157,6 +166,7 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -212,7 +222,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -224,6 +237,7 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
+    "execution": {},
     "pycharm": {
      "name": "#%%\n"
     },
@@ -246,7 +260,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -275,6 +292,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 853,
      "status": "ok",
@@ -313,7 +331,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "ts_co2 = pyleo.Series(\n",
@@ -340,6 +360,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 800,
      "status": "ok",
@@ -391,6 +412,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 1120,
      "status": "ok",
@@ -421,7 +443,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "dDts = pyleo.Series(\n",
@@ -439,6 +463,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 588,
      "status": "ok",
@@ -468,6 +493,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 690,
      "status": "ok",
@@ -514,7 +540,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# to_remove explanation\n",
@@ -531,7 +559,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -605,7 +636,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.18"
+   "version": "3.9.19"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/W1D4_Paleoclimate/W1D4_Tutorial5.ipynb b/tutorials/W1D4_Paleoclimate/W1D4_Tutorial5.ipynb
index f38d1c03c..4ba4b3942 100644
--- a/tutorials/W1D4_Paleoclimate/W1D4_Tutorial5.ipynb
+++ b/tutorials/W1D4_Paleoclimate/W1D4_Tutorial5.ipynb
@@ -60,7 +60,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# installations ( uncomment and run this cell ONLY when using google colab or kaggle )\n",
@@ -71,7 +73,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# imports\n",
@@ -88,7 +92,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Install and import feedback gadget\n",
@@ -115,7 +122,8 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "form"
+    "cellView": "form",
+    "execution": {}
    },
    "outputs": [],
    "source": [
@@ -132,7 +140,8 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "form"
+    "cellView": "form",
+    "execution": {}
    },
    "outputs": [],
    "source": [
@@ -160,6 +169,7 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -215,7 +225,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -227,6 +240,7 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
+    "execution": {},
     "pycharm": {
      "name": "#%%\n"
     },
@@ -249,7 +263,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -272,7 +289,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "filename_tang = \"tanganyika_dD.csv\"\n",
@@ -294,6 +313,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 736,
      "status": "ok",
@@ -345,6 +365,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 138,
      "status": "ok",
@@ -383,7 +404,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "tang_linear = ts_tang.interp()  # default method = 'linear'"
@@ -393,6 +416,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 167,
      "status": "ok",
@@ -423,6 +447,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 443,
      "status": "ok",
@@ -455,7 +480,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "ts_tang"
@@ -464,7 +491,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "tang_linear"
@@ -482,7 +511,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "fig, ax = plt.subplots()  # assign a new plot axis\n",
@@ -515,7 +546,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "tang_bin = (\n",
@@ -527,6 +560,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 457,
      "status": "ok",
@@ -569,7 +603,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# bin size of 500\n",
@@ -589,7 +625,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# to_remove solution\n",
@@ -611,7 +649,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -649,6 +690,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 484,
      "status": "ok",
@@ -673,6 +715,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 370,
      "status": "ok",
@@ -699,6 +742,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 354,
      "status": "ok",
@@ -731,7 +775,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "ts_tanganyika = pyleo.Series(\n",
@@ -780,7 +826,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "ts_list = [ts_tanganyika, ts_aden, ts_bosumtwi, ts_gc27]\n",
@@ -800,6 +848,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 756,
      "status": "ok",
@@ -831,6 +880,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 1048,
      "status": "ok",
@@ -864,7 +914,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "pca = PCA()\n",
@@ -886,6 +938,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 224,
      "status": "ok",
@@ -916,7 +969,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "africa_pc1 = africa_PCA.transform(africa_ct.to_pandas())"
@@ -925,7 +980,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "africa_mode1 = pyleo.Series(\n",
@@ -942,6 +999,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 1026,
      "status": "ok",
@@ -985,7 +1043,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# to_remove explanation\n",
@@ -1000,7 +1060,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -1079,7 +1142,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.18"
+   "version": "3.9.19"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/W1D4_Paleoclimate/W1D4_Tutorial6.ipynb b/tutorials/W1D4_Paleoclimate/W1D4_Tutorial6.ipynb
index 8f617556b..7c659c656 100644
--- a/tutorials/W1D4_Paleoclimate/W1D4_Tutorial6.ipynb
+++ b/tutorials/W1D4_Paleoclimate/W1D4_Tutorial6.ipynb
@@ -60,7 +60,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# installations ( uncomment and run this cell ONLY when using google colab or kaggle )\n",
@@ -71,7 +73,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# imports\n",
@@ -87,7 +91,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Install and import feedback gadget\n",
@@ -114,7 +121,8 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "form"
+    "cellView": "form",
+    "execution": {}
    },
    "outputs": [],
    "source": [
@@ -131,7 +139,8 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "form"
+    "cellView": "form",
+    "execution": {}
    },
    "outputs": [],
    "source": [
@@ -159,6 +168,7 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -214,7 +224,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -226,6 +239,7 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
+    "execution": {},
     "pycharm": {
      "name": "#%%\n"
     },
@@ -248,7 +262,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -279,6 +296,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 388,
      "status": "ok",
@@ -315,7 +333,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "ts_lr04 = pyleo.Series(\n",
@@ -342,6 +362,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 1136,
      "status": "ok",
@@ -376,7 +397,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# to_remove explanation\n",
@@ -391,7 +414,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -436,7 +462,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "fig, ax = plt.subplots()\n",
@@ -482,7 +510,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# Lomb-Scargle periodogram\n",
@@ -513,6 +543,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 81823,
      "status": "ok",
@@ -532,7 +563,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "lr04_ls_sd_sig.plot(xlabel=\"Period [kyrs]\")"
@@ -553,6 +586,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 722,
      "status": "ok",
@@ -602,7 +636,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# create a scalogram\n",
@@ -613,6 +649,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 1623,
      "status": "ok",
@@ -655,7 +692,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# to_remove explanation\n",
@@ -668,7 +707,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -738,7 +780,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.18"
+   "version": "3.9.19"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/W1D4_Paleoclimate/W1D4_Tutorial7.ipynb b/tutorials/W1D4_Paleoclimate/W1D4_Tutorial7.ipynb
index fae6fe3f8..8a150d95e 100644
--- a/tutorials/W1D4_Paleoclimate/W1D4_Tutorial7.ipynb
+++ b/tutorials/W1D4_Paleoclimate/W1D4_Tutorial7.ipynb
@@ -60,7 +60,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# installations ( uncomment and run this cell ONLY when using google colab or kaggle )\n",
@@ -77,6 +79,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 7892,
      "status": "ok",
@@ -108,7 +111,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Install and import feedback gadget\n",
@@ -135,7 +141,8 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "form"
+    "cellView": "form",
+    "execution": {}
    },
    "outputs": [],
    "source": [
@@ -152,7 +159,8 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "form"
+    "cellView": "form",
+    "execution": {}
    },
    "outputs": [],
    "source": [
@@ -180,6 +188,7 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -235,7 +244,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -247,6 +259,7 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
+    "execution": {},
     "pycharm": {
      "name": "#%%\n"
     },
@@ -269,7 +282,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -309,6 +325,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 927,
      "status": "ok",
@@ -364,7 +381,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# standardize the data\n",
@@ -374,7 +393,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# calculate the WWZ spectral analysis\n",
@@ -385,6 +406,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 1575,
      "status": "ok",
@@ -416,7 +438,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# perform significance test with 5 surrogates\n",
@@ -429,7 +453,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# to_remove solution\n",
@@ -444,7 +470,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -467,7 +496,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# specify time interval and units\n",
@@ -497,6 +528,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 540,
      "status": "ok",
@@ -535,6 +567,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 819,
      "status": "ok",
@@ -571,7 +604,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# calculate the WWZ spectral analysis\n",
@@ -582,6 +617,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 602,
      "status": "ok",
@@ -613,7 +649,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# to_remove explanation\n",
@@ -627,7 +665,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -692,7 +733,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.18"
+   "version": "3.9.19"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/W1D4_Paleoclimate/W1D4_Tutorial8.ipynb b/tutorials/W1D4_Paleoclimate/W1D4_Tutorial8.ipynb
index ee5aa441a..cd29c7741 100644
--- a/tutorials/W1D4_Paleoclimate/W1D4_Tutorial8.ipynb
+++ b/tutorials/W1D4_Paleoclimate/W1D4_Tutorial8.ipynb
@@ -94,7 +94,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Install and import feedback gadget\n",
@@ -224,7 +227,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -259,7 +265,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -365,7 +374,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -647,7 +659,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -748,7 +763,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -828,7 +846,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.18"
+   "version": "3.9.19"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/W1D4_Paleoclimate/W1D4_Tutorial9.ipynb b/tutorials/W1D4_Paleoclimate/W1D4_Tutorial9.ipynb
index 2e1e195c4..b39ad202c 100644
--- a/tutorials/W1D4_Paleoclimate/W1D4_Tutorial9.ipynb
+++ b/tutorials/W1D4_Paleoclimate/W1D4_Tutorial9.ipynb
@@ -95,7 +95,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Install and import feedback gadget\n",
@@ -225,7 +228,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -260,7 +266,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -413,7 +422,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -571,7 +583,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -638,7 +653,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.18"
+   "version": "3.9.19"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/W1D4_Paleoclimate/instructor/W1D4_Intro.ipynb b/tutorials/W1D4_Paleoclimate/instructor/W1D4_Intro.ipynb
index 5dd3dcae5..d18eb2ac5 100644
--- a/tutorials/W1D4_Paleoclimate/instructor/W1D4_Intro.ipynb
+++ b/tutorials/W1D4_Paleoclimate/instructor/W1D4_Intro.ipynb
@@ -58,6 +58,36 @@
     "3. Explain the benefits and limitations of reanalysis products for paleoclimate analysis."
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "eb2c1de5-858c-41e5-81b9-4909854dbd27",
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D4_Intro\""
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "6695fea7",
@@ -126,6 +156,20 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "5794e217-8ac9-4391-becc-685aeaa33ba4",
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Past_Climates_Inform_Our_Future_Video\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "a17e786a",
@@ -152,14 +196,22 @@
     "\n",
     "link_id = \"2pvrs\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "2562974f-c9a0-4d70-91b6-87f22e0d2276",
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Past_Climates_Inform_Our_Future_Slides\")"
    ]
   }
  ],
diff --git a/tutorials/W1D4_Paleoclimate/instructor/W1D4_Tutorial1.ipynb b/tutorials/W1D4_Paleoclimate/instructor/W1D4_Tutorial1.ipynb
index 2cff09fec..382fb6c93 100644
--- a/tutorials/W1D4_Paleoclimate/instructor/W1D4_Tutorial1.ipynb
+++ b/tutorials/W1D4_Paleoclimate/instructor/W1D4_Tutorial1.ipynb
@@ -67,7 +67,6 @@
    "source": [
     "# installations ( uncomment and run this cell ONLY when using google colab or kaggle )\n",
     "\n",
-    "# !pip install --no-binary shapely shapely --force # Add this to use cartopy. in this way it doesn't crush\n",
     "# !pip install cartopy\n",
     "# !pip install LiPD"
    ]
@@ -94,6 +93,35 @@
     "import cartopy.feature as cfeature"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D4_T1\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -298,6 +326,19 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_What_is_Paleoclimate_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -319,14 +360,21 @@
     "\n",
     "link_id = \"ae894\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_What_is_Paleoclimate_Slides\")"
    ]
   },
   {
@@ -610,6 +658,19 @@
     "\"\"\""
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_3\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
diff --git a/tutorials/W1D4_Paleoclimate/instructor/W1D4_Tutorial2.ipynb b/tutorials/W1D4_Paleoclimate/instructor/W1D4_Tutorial2.ipynb
index 75164fd2b..b2d8fb751 100644
--- a/tutorials/W1D4_Paleoclimate/instructor/W1D4_Tutorial2.ipynb
+++ b/tutorials/W1D4_Paleoclimate/instructor/W1D4_Tutorial2.ipynb
@@ -116,6 +116,35 @@
     "from matplotlib import patches"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D4_T2\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -220,6 +249,19 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Ocean_Climate_Proxies_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -241,14 +283,21 @@
     "\n",
     "link_id = \"qtkbv\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Ocean_Climate_Proxies_Slides\")"
    ]
   },
   {
@@ -643,7 +692,20 @@
     "\"\"\"\n",
     "1. In general when there is a recorded ENSO event in the ONI, there is an agreement with the coral records.  During El Niño Phases captured by the ONI (where SSTs are anomalously warm), we typically see a more negative d18O and vice versa for La Niña events.\n",
     "2. ENSO is an interannual occurrence, happening every 2-7 years. Within the d18O records, there are high-frequency signals. One thing (among many) we could do is remove these by filtering. This would help resolve our dataset into something more comparable to what the ONI is tracking.\n",
-    "\"\"\";"
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_2\")"
    ]
   },
   {
@@ -652,7 +714,7 @@
     "execution": {}
    },
    "source": [
-    "# Section 1.3: Make Warming Stripes Plot"
+    "# Section 3: Make Warming Stripes Plot"
    ]
   },
   {
diff --git a/tutorials/W1D4_Paleoclimate/instructor/W1D4_Tutorial3.ipynb b/tutorials/W1D4_Paleoclimate/instructor/W1D4_Tutorial3.ipynb
index 37b32638e..8a728b9ea 100644
--- a/tutorials/W1D4_Paleoclimate/instructor/W1D4_Tutorial3.ipynb
+++ b/tutorials/W1D4_Paleoclimate/instructor/W1D4_Tutorial3.ipynb
@@ -69,7 +69,7 @@
     "\n",
     "# !pip install LiPD\n",
     "# !pip install cartopy\n",
-    "# !pip install pyleoclim"
+    "# !pip install pyleoclim==0.14.0"
    ]
   },
   {
@@ -94,6 +94,35 @@
     "import sys"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D4_T3\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -221,6 +250,19 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Terrestrial_Climate_Proxies_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -242,14 +284,21 @@
     "\n",
     "link_id = \"6gcsh\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Terrestrial_Climate_Proxies_Slides\")"
    ]
   },
   {
@@ -661,6 +710,19 @@
     ")"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Coding_Exercises_2\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -785,6 +847,19 @@
     "\"\"\""
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_2\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
diff --git a/tutorials/W1D4_Paleoclimate/instructor/W1D4_Tutorial4.ipynb b/tutorials/W1D4_Paleoclimate/instructor/W1D4_Tutorial4.ipynb
index b8f781b7b..12f02ffa4 100644
--- a/tutorials/W1D4_Paleoclimate/instructor/W1D4_Tutorial4.ipynb
+++ b/tutorials/W1D4_Paleoclimate/instructor/W1D4_Tutorial4.ipynb
@@ -66,8 +66,7 @@
    "source": [
     "# installations ( uncomment and run this cell ONLY when using google colab or kaggle )\n",
     "\n",
-    "# !pip install pyleoclim\n",
-    "# !pip install cartopy"
+    "# !pip install pyleoclim"
    ]
   },
   {
@@ -87,6 +86,35 @@
     "import pyleoclim as pyleo"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D4_T4\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -191,6 +219,19 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Atmospheric_Climate_Proxies_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -212,14 +253,21 @@
     "\n",
     "link_id = \"szyhp\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Atmospheric_Climate_Proxies_Slides\")"
    ]
   },
   {
@@ -505,7 +553,20 @@
     "3. The cooling periods tend to be more gradual while warming periods are relatively rapid. This pattern is especially apparent over the past 400,000 years.\n",
     "4. These glacial-interglacial cycles are primarily driven by variations in Earth’s orbital parameters. These parameters include eccentricity, obliquity, and precession, which vary on timescales of ~100,000 years, ~40,000 years, and ~21,000 years, respectively. In later tutorials, we’ll learn how to identify temporal cyclicity in paleoclimate reconstructions and assess possible forcings with similar timescales of variation.\n",
     "\n",
-    "\"\"\";"
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_2\")"
    ]
   },
   {
diff --git a/tutorials/W1D4_Paleoclimate/instructor/W1D4_Tutorial5.ipynb b/tutorials/W1D4_Paleoclimate/instructor/W1D4_Tutorial5.ipynb
index 29f419414..2751600aa 100644
--- a/tutorials/W1D4_Paleoclimate/instructor/W1D4_Tutorial5.ipynb
+++ b/tutorials/W1D4_Paleoclimate/instructor/W1D4_Tutorial5.ipynb
@@ -89,6 +89,35 @@
     "from sklearn.decomposition import PCA"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D4_T5\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -193,6 +222,19 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Proxy_Data_Analysis_Tools_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -214,14 +256,21 @@
     "\n",
     "link_id = \"ujbqz\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Proxy_Data_Analysis_Tools_Slides\")"
    ]
   },
   {
@@ -599,6 +648,19 @@
     "_ = tang_bin_1000.plot(ax=ax, label=\"Binned 1000 yrs\")"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Coding_Exercises_2_2\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -994,7 +1056,20 @@
     "1. The overall trends are similar. However, there is more variability in the original δD records than in the PC1 time series. This makes sense because the principal component analysis identifies a common signal between original δD reconstructions and therefore is inherently less variable.\n",
     "2. The Gulf of Aden δD record is the most similar to the PC1 time series. The Lake Bosumtwi δD record is the least similar to the PC1 time series. This difference is particularly noticeable between 5,000-10,000 years ago.\n",
     "3. The PC1 time series suggests a drier climate (more positive δD) in Africa over the past 20,000 years. Recall that 20,000 years ago was the last glacial period. African rainfall increased ~15,000 years ago during the deglacial transition. There is a short period of drying ~12,000 years ago, which corresponds to the timing of the Younger Dryas (a millennial-scale, Northern Hemisphere high-latitude cooling event). This is followed by an increase in rainfall associated with what is known as the African Humid Period (a period of wet, humid conditions in northern and equatorial Africa, driven by intensification of the African monsoon). Finally, there is a decrease in rainfall over the past ~8,000 years towards the present. Note: δD only records qualitative changes in rainfall (i.e., wetter or drier relative to another time period), and does not provide quantitative measurements of the amount of rainfall.\n",
-    "\"\"\";"
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_3\")"
    ]
   },
   {
diff --git a/tutorials/W1D4_Paleoclimate/instructor/W1D4_Tutorial6.ipynb b/tutorials/W1D4_Paleoclimate/instructor/W1D4_Tutorial6.ipynb
index c845e7e80..8cbdd9e99 100644
--- a/tutorials/W1D4_Paleoclimate/instructor/W1D4_Tutorial6.ipynb
+++ b/tutorials/W1D4_Paleoclimate/instructor/W1D4_Tutorial6.ipynb
@@ -88,6 +88,35 @@
     "import pyleoclim as pyleo"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D4_T6\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -192,6 +221,19 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Spectral_Analysis_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -213,14 +255,21 @@
     "\n",
     "link_id = \"g7rp4\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Spectral_Analysis_Slides\")"
    ]
   },
   {
@@ -359,7 +408,20 @@
     "1. There are cyclical variations in d18O that record glacial and interglacial periods. Higher-than-standard global concentrations of light oxygen in ocean water indicate that global temperatures have warmed (i.e. an interglacial period), whereas higher-than-standard global concentrations of heavy oxygen in ocean water indicate that global temperatures were cooler (i.e. a glacial period).\n",
     "2. It appears as if the amplitudes of the glacial-interglacial cycles increased over the past 1 million years. Specifically, the amplitude changes ~700,000 years ago.\n",
     "3. It's difficult to determine the temporal frequency at which these glacial-interglacial cycles occur by just looking at the time series. We will explore a computational tool to more accurately determine the length of these cycles. By eye, you might note a ~100,000 year cycle however, among others that are harder to discern.\n",
-    "\"\"\";"
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_1\")"
    ]
   },
   {
@@ -642,6 +704,19 @@
     "\"\"\""
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_2_3\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
diff --git a/tutorials/W1D4_Paleoclimate/instructor/W1D4_Tutorial7.ipynb b/tutorials/W1D4_Paleoclimate/instructor/W1D4_Tutorial7.ipynb
index d6e8ec599..71b540d99 100644
--- a/tutorials/W1D4_Paleoclimate/instructor/W1D4_Tutorial7.ipynb
+++ b/tutorials/W1D4_Paleoclimate/instructor/W1D4_Tutorial7.ipynb
@@ -108,6 +108,35 @@
     "from climlab.solar.insolation import daily_insolation"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D4_T7\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -212,6 +241,19 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Interpreting_Climate_Forcings_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -233,14 +275,21 @@
     "\n",
     "link_id = \"ztfwk\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Interpreting_Climate_Forcings_Slides\")"
    ]
   },
   {
@@ -420,6 +469,19 @@
     "_ = d18O_wwz_sig.plot(xlabel=\"Period [kyrs]\")"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Coding_Exercises_1\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -599,7 +661,20 @@
     "\"\"\"\n",
     "1. The dominant spectral power for the insolation data is ~23,000 years, which is roughly the same signal observed in the spectral analysis of the speleothem d18O record.\n",
     "2. The relationship between solar insolation and monsoon intensity can be explained by the fact that solar insolation affects the temperature gradients between land and sea. During the summer, if there's high solar insolation, the land warms up more than the sea, leading to lower pressure over the land. This low pressure attracts moisture-rich air from the sea, causing the monsoon. Therefore, changes in solar insolation caused by Earth's orbital cycles could influence the intensity of monsoons. Specifically, the 23,000 year signal in these records suggests that precession-driven changes in insolation was the dominant forcing of monsoon intensity.\n",
-    "\"\"\";"
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_2\")"
    ]
   },
   {
diff --git a/tutorials/W1D4_Paleoclimate/instructor/W1D4_Tutorial8.ipynb b/tutorials/W1D4_Paleoclimate/instructor/W1D4_Tutorial8.ipynb
index 502b32a76..d9702ce05 100644
--- a/tutorials/W1D4_Paleoclimate/instructor/W1D4_Tutorial8.ipynb
+++ b/tutorials/W1D4_Paleoclimate/instructor/W1D4_Tutorial8.ipynb
@@ -91,6 +91,35 @@
     "import pyleoclim as pyleo"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D4_T8\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -195,6 +224,19 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Paleoclimate_Models_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -216,14 +258,21 @@
     "\n",
     "link_id = \"7p3zv\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Paleoclimate_Models_Slides\")"
    ]
   },
   {
@@ -319,7 +368,20 @@
     "\"\"\"\n",
     "1. Until about 1850, the overall temperature is relatively constant with a ~1ºC decrease from 600-1000 and a ~1.5ºC warming from 1000-1300. However, from 1850 to the present, temperature has increased by ~2.5ºC.\n",
     "2. This recent increase in temperature is likely due to the impacts of anthropogenic activities.\n",
-    "\"\"\";"
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_1\")"
    ]
   },
   {
@@ -591,7 +653,20 @@
     "1. The reconstructed Global Mean Surface Temperature (GMST) anomalies from the collective time series displays a variation within the range of 1.5 ˚C. The consistency among the reconstructed values tends to increase as we approach the present day, with more substantial variation observed between the years 1200 and 1800. These differences can be attributed to several factors. For instance, each model's unique sensitivity to different forcings and their distinct representations of physical processes or spatial resolutions can lead to variations in outcomes.\n",
     "2. In order to obtain the \"best\" simulation, a comparative analysis is conducted against observational or proxy data. The simulation that best mirrors the observed or reconstructed climate trends and variability over the same time period is often deemed the most reliable. However, it's essential to note that all models possess their own strengths and weaknesses, and the \"best\" model can depend on the specific climate variable or region of interest.\n",
     "\n",
-    "\"\"\";"
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_2\")"
    ]
   },
   {
@@ -682,7 +757,20 @@
     "1. The model temperatures exhibit greater variability compared to the proxy records due to the significantly lower sampling frequency of the proxies.\n",
     "2. Despite the differences in variability and temporal resolution, the overall temperature trends seen in the proxy record and GMST anomaly reconstructions from all PMIP3 simulations are similar. Overall, both the model and the proxy show relatively constant temperatures until ~1850 when temperature rapidly increases due to the influence of anthropogenic forcings, particularly the increase in greenhouse gas concentrations due to human activities.\n",
     "\n",
-    "\"\"\";"
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_3\")"
    ]
   },
   {
diff --git a/tutorials/W1D4_Paleoclimate/instructor/W1D4_Tutorial9.ipynb b/tutorials/W1D4_Paleoclimate/instructor/W1D4_Tutorial9.ipynb
index 81bc44b3f..e50e6f7b6 100644
--- a/tutorials/W1D4_Paleoclimate/instructor/W1D4_Tutorial9.ipynb
+++ b/tutorials/W1D4_Paleoclimate/instructor/W1D4_Tutorial9.ipynb
@@ -92,6 +92,35 @@
     "import cartopy.crs as ccrs"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D4_T9\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -196,6 +225,19 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Paleoclimate_Data_Assimilation_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -217,14 +259,21 @@
     "\n",
     "link_id = \"f2ynq\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Paleoclimate_Data_Assimilation_Slides\")"
    ]
   },
   {
@@ -367,7 +416,20 @@
     "1.In the span of the last 24,000 years, there has been a considerable shift in global temperatures, transitioning from the colder phase of the Last Glacial Maximum to the relatively warmer Holocene epoch we are currently experiencing. This transformation was not linear, with periods of rapid warming interspersed with intervals of relative stability or even temporary cooling.\n",
     "2.The increase in temperature around 17,000 years ago was likely driven by a combination of climate forcings: obliquity and eccentricity, both affect the amount of solar radiation reaching the Earth's surface.\n",
     "\n",
-    "\"\"\";"
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_1_1\")"
    ]
   },
   {
@@ -492,7 +554,7 @@
     "execution": {}
    },
    "source": [
-    "### Questions 1.1: Climate Connection\n",
+    "### Questions 1.2: Climate Connection\n",
     "\n",
     "Looking at both the map and zonal mean plot, consider the following questions: \n",
     "\n",
@@ -515,7 +577,20 @@
     "\n",
     "2. This pattern is known as polar amplification, which is caused by a number of factors including changes in albedo as ice sheets melt, changes in atmospheric and oceanic circulation, and changes in the distribution of solar insolation.\n",
     "\n",
-    "\"\"\";"
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_1_2\")"
    ]
   },
   {
diff --git a/tutorials/W1D4_Paleoclimate/solutions/W1D4_Tutorial2_Solution_2c43ca48.py b/tutorials/W1D4_Paleoclimate/solutions/W1D4_Tutorial2_Solution_8f319b78.py
similarity index 99%
rename from tutorials/W1D4_Paleoclimate/solutions/W1D4_Tutorial2_Solution_2c43ca48.py
rename to tutorials/W1D4_Paleoclimate/solutions/W1D4_Tutorial2_Solution_8f319b78.py
index 270a547c4..7d7105038 100644
--- a/tutorials/W1D4_Paleoclimate/solutions/W1D4_Tutorial2_Solution_2c43ca48.py
+++ b/tutorials/W1D4_Paleoclimate/solutions/W1D4_Tutorial2_Solution_8f319b78.py
@@ -2,4 +2,4 @@
 """
 1. In general when there is a recorded ENSO event in the ONI, there is an agreement with the coral records.  During El Niño Phases captured by the ONI (where SSTs are anomalously warm), we typically see a more negative d18O and vice versa for La Niña events.
 2. ENSO is an interannual occurrence, happening every 2-7 years. Within the d18O records, there are high-frequency signals. One thing (among many) we could do is remove these by filtering. This would help resolve our dataset into something more comparable to what the ONI is tracking.
-""";
\ No newline at end of file
+"""
\ No newline at end of file
diff --git a/tutorials/W1D4_Paleoclimate/solutions/W1D4_Tutorial4_Solution_b7a1b0c7.py b/tutorials/W1D4_Paleoclimate/solutions/W1D4_Tutorial4_Solution_0c62ceb1.py
similarity index 99%
rename from tutorials/W1D4_Paleoclimate/solutions/W1D4_Tutorial4_Solution_b7a1b0c7.py
rename to tutorials/W1D4_Paleoclimate/solutions/W1D4_Tutorial4_Solution_0c62ceb1.py
index 59e9f8f6f..c20412b03 100644
--- a/tutorials/W1D4_Paleoclimate/solutions/W1D4_Tutorial4_Solution_b7a1b0c7.py
+++ b/tutorials/W1D4_Paleoclimate/solutions/W1D4_Tutorial4_Solution_0c62ceb1.py
@@ -5,4 +5,4 @@
 3. The cooling periods tend to be more gradual while warming periods are relatively rapid. This pattern is especially apparent over the past 400,000 years.
 4. These glacial-interglacial cycles are primarily driven by variations in Earth’s orbital parameters. These parameters include eccentricity, obliquity, and precession, which vary on timescales of ~100,000 years, ~40,000 years, and ~21,000 years, respectively. In later tutorials, we’ll learn how to identify temporal cyclicity in paleoclimate reconstructions and assess possible forcings with similar timescales of variation.
 
-""";
\ No newline at end of file
+"""
\ No newline at end of file
diff --git a/tutorials/W1D4_Paleoclimate/solutions/W1D4_Tutorial5_Solution_599669bd.py b/tutorials/W1D4_Paleoclimate/solutions/W1D4_Tutorial5_Solution_b2ed69d2.py
similarity index 99%
rename from tutorials/W1D4_Paleoclimate/solutions/W1D4_Tutorial5_Solution_599669bd.py
rename to tutorials/W1D4_Paleoclimate/solutions/W1D4_Tutorial5_Solution_b2ed69d2.py
index 9a25f060a..800cacb7e 100644
--- a/tutorials/W1D4_Paleoclimate/solutions/W1D4_Tutorial5_Solution_599669bd.py
+++ b/tutorials/W1D4_Paleoclimate/solutions/W1D4_Tutorial5_Solution_b2ed69d2.py
@@ -3,4 +3,4 @@
 1. The overall trends are similar. However, there is more variability in the original δD records than in the PC1 time series. This makes sense because the principal component analysis identifies a common signal between original δD reconstructions and therefore is inherently less variable.
 2. The Gulf of Aden δD record is the most similar to the PC1 time series. The Lake Bosumtwi δD record is the least similar to the PC1 time series. This difference is particularly noticeable between 5,000-10,000 years ago.
 3. The PC1 time series suggests a drier climate (more positive δD) in Africa over the past 20,000 years. Recall that 20,000 years ago was the last glacial period. African rainfall increased ~15,000 years ago during the deglacial transition. There is a short period of drying ~12,000 years ago, which corresponds to the timing of the Younger Dryas (a millennial-scale, Northern Hemisphere high-latitude cooling event). This is followed by an increase in rainfall associated with what is known as the African Humid Period (a period of wet, humid conditions in northern and equatorial Africa, driven by intensification of the African monsoon). Finally, there is a decrease in rainfall over the past ~8,000 years towards the present. Note: δD only records qualitative changes in rainfall (i.e., wetter or drier relative to another time period), and does not provide quantitative measurements of the amount of rainfall.
-""";
\ No newline at end of file
+"""
\ No newline at end of file
diff --git a/tutorials/W1D4_Paleoclimate/solutions/W1D4_Tutorial6_Solution_7ad0d4e6.py b/tutorials/W1D4_Paleoclimate/solutions/W1D4_Tutorial6_Solution_a75a63b1.py
similarity index 99%
rename from tutorials/W1D4_Paleoclimate/solutions/W1D4_Tutorial6_Solution_7ad0d4e6.py
rename to tutorials/W1D4_Paleoclimate/solutions/W1D4_Tutorial6_Solution_a75a63b1.py
index 8ada1f468..54c0dac03 100644
--- a/tutorials/W1D4_Paleoclimate/solutions/W1D4_Tutorial6_Solution_7ad0d4e6.py
+++ b/tutorials/W1D4_Paleoclimate/solutions/W1D4_Tutorial6_Solution_a75a63b1.py
@@ -3,4 +3,4 @@
 1. There are cyclical variations in d18O that record glacial and interglacial periods. Higher-than-standard global concentrations of light oxygen in ocean water indicate that global temperatures have warmed (i.e. an interglacial period), whereas higher-than-standard global concentrations of heavy oxygen in ocean water indicate that global temperatures were cooler (i.e. a glacial period).
 2. It appears as if the amplitudes of the glacial-interglacial cycles increased over the past 1 million years. Specifically, the amplitude changes ~700,000 years ago.
 3. It's difficult to determine the temporal frequency at which these glacial-interglacial cycles occur by just looking at the time series. We will explore a computational tool to more accurately determine the length of these cycles. By eye, you might note a ~100,000 year cycle however, among others that are harder to discern.
-""";
\ No newline at end of file
+"""
\ No newline at end of file
diff --git a/tutorials/W1D4_Paleoclimate/solutions/W1D4_Tutorial7_Solution_ae0c8527.py b/tutorials/W1D4_Paleoclimate/solutions/W1D4_Tutorial7_Solution_f88c4da6.py
similarity index 99%
rename from tutorials/W1D4_Paleoclimate/solutions/W1D4_Tutorial7_Solution_ae0c8527.py
rename to tutorials/W1D4_Paleoclimate/solutions/W1D4_Tutorial7_Solution_f88c4da6.py
index 89b6e04b0..8b62b4494 100644
--- a/tutorials/W1D4_Paleoclimate/solutions/W1D4_Tutorial7_Solution_ae0c8527.py
+++ b/tutorials/W1D4_Paleoclimate/solutions/W1D4_Tutorial7_Solution_f88c4da6.py
@@ -2,4 +2,4 @@
 """
 1. The dominant spectral power for the insolation data is ~23,000 years, which is roughly the same signal observed in the spectral analysis of the speleothem d18O record.
 2. The relationship between solar insolation and monsoon intensity can be explained by the fact that solar insolation affects the temperature gradients between land and sea. During the summer, if there's high solar insolation, the land warms up more than the sea, leading to lower pressure over the land. This low pressure attracts moisture-rich air from the sea, causing the monsoon. Therefore, changes in solar insolation caused by Earth's orbital cycles could influence the intensity of monsoons. Specifically, the 23,000 year signal in these records suggests that precession-driven changes in insolation was the dominant forcing of monsoon intensity.
-""";
\ No newline at end of file
+"""
\ No newline at end of file
diff --git a/tutorials/W1D4_Paleoclimate/solutions/W1D4_Tutorial8_Solution_5bf60405.py b/tutorials/W1D4_Paleoclimate/solutions/W1D4_Tutorial8_Solution_243939d2.py
similarity index 98%
rename from tutorials/W1D4_Paleoclimate/solutions/W1D4_Tutorial8_Solution_5bf60405.py
rename to tutorials/W1D4_Paleoclimate/solutions/W1D4_Tutorial8_Solution_243939d2.py
index 52f9ace47..c2b96474b 100644
--- a/tutorials/W1D4_Paleoclimate/solutions/W1D4_Tutorial8_Solution_5bf60405.py
+++ b/tutorials/W1D4_Paleoclimate/solutions/W1D4_Tutorial8_Solution_243939d2.py
@@ -2,4 +2,4 @@
 """
 1. Until about 1850, the overall temperature is relatively constant with a ~1ºC decrease from 600-1000 and a ~1.5ºC warming from 1000-1300. However, from 1850 to the present, temperature has increased by ~2.5ºC.
 2. This recent increase in temperature is likely due to the impacts of anthropogenic activities.
-""";
\ No newline at end of file
+"""
\ No newline at end of file
diff --git a/tutorials/W1D4_Paleoclimate/solutions/W1D4_Tutorial8_Solution_743a99c5.py b/tutorials/W1D4_Paleoclimate/solutions/W1D4_Tutorial8_Solution_278fb208.py
similarity index 99%
rename from tutorials/W1D4_Paleoclimate/solutions/W1D4_Tutorial8_Solution_743a99c5.py
rename to tutorials/W1D4_Paleoclimate/solutions/W1D4_Tutorial8_Solution_278fb208.py
index 314a41a5c..3308b2e0b 100644
--- a/tutorials/W1D4_Paleoclimate/solutions/W1D4_Tutorial8_Solution_743a99c5.py
+++ b/tutorials/W1D4_Paleoclimate/solutions/W1D4_Tutorial8_Solution_278fb208.py
@@ -3,4 +3,4 @@
 1. The model temperatures exhibit greater variability compared to the proxy records due to the significantly lower sampling frequency of the proxies.
 2. Despite the differences in variability and temporal resolution, the overall temperature trends seen in the proxy record and GMST anomaly reconstructions from all PMIP3 simulations are similar. Overall, both the model and the proxy show relatively constant temperatures until ~1850 when temperature rapidly increases due to the influence of anthropogenic forcings, particularly the increase in greenhouse gas concentrations due to human activities.
 
-""";
\ No newline at end of file
+"""
\ No newline at end of file
diff --git a/tutorials/W1D4_Paleoclimate/solutions/W1D4_Tutorial8_Solution_233de275.py b/tutorials/W1D4_Paleoclimate/solutions/W1D4_Tutorial8_Solution_c7fb7c84.py
similarity index 99%
rename from tutorials/W1D4_Paleoclimate/solutions/W1D4_Tutorial8_Solution_233de275.py
rename to tutorials/W1D4_Paleoclimate/solutions/W1D4_Tutorial8_Solution_c7fb7c84.py
index c70362b62..ee1051876 100644
--- a/tutorials/W1D4_Paleoclimate/solutions/W1D4_Tutorial8_Solution_233de275.py
+++ b/tutorials/W1D4_Paleoclimate/solutions/W1D4_Tutorial8_Solution_c7fb7c84.py
@@ -3,4 +3,4 @@
 1. The reconstructed Global Mean Surface Temperature (GMST) anomalies from the collective time series displays a variation within the range of 1.5 ˚C. The consistency among the reconstructed values tends to increase as we approach the present day, with more substantial variation observed between the years 1200 and 1800. These differences can be attributed to several factors. For instance, each model's unique sensitivity to different forcings and their distinct representations of physical processes or spatial resolutions can lead to variations in outcomes.
 2. In order to obtain the "best" simulation, a comparative analysis is conducted against observational or proxy data. The simulation that best mirrors the observed or reconstructed climate trends and variability over the same time period is often deemed the most reliable. However, it's essential to note that all models possess their own strengths and weaknesses, and the "best" model can depend on the specific climate variable or region of interest.
 
-""";
\ No newline at end of file
+"""
\ No newline at end of file
diff --git a/tutorials/W1D4_Paleoclimate/solutions/W1D4_Tutorial9_Solution_59159894.py b/tutorials/W1D4_Paleoclimate/solutions/W1D4_Tutorial9_Solution_36373365.py
similarity index 99%
rename from tutorials/W1D4_Paleoclimate/solutions/W1D4_Tutorial9_Solution_59159894.py
rename to tutorials/W1D4_Paleoclimate/solutions/W1D4_Tutorial9_Solution_36373365.py
index 989b33b70..c55f3e9a0 100644
--- a/tutorials/W1D4_Paleoclimate/solutions/W1D4_Tutorial9_Solution_59159894.py
+++ b/tutorials/W1D4_Paleoclimate/solutions/W1D4_Tutorial9_Solution_36373365.py
@@ -4,4 +4,4 @@
 
 2. This pattern is known as polar amplification, which is caused by a number of factors including changes in albedo as ice sheets melt, changes in atmospheric and oceanic circulation, and changes in the distribution of solar insolation.
 
-""";
\ No newline at end of file
+"""
\ No newline at end of file
diff --git a/tutorials/W1D4_Paleoclimate/solutions/W1D4_Tutorial9_Solution_ace0594e.py b/tutorials/W1D4_Paleoclimate/solutions/W1D4_Tutorial9_Solution_ff1cd22c.py
similarity index 99%
rename from tutorials/W1D4_Paleoclimate/solutions/W1D4_Tutorial9_Solution_ace0594e.py
rename to tutorials/W1D4_Paleoclimate/solutions/W1D4_Tutorial9_Solution_ff1cd22c.py
index 1df93d0e1..ec5eedf09 100644
--- a/tutorials/W1D4_Paleoclimate/solutions/W1D4_Tutorial9_Solution_ace0594e.py
+++ b/tutorials/W1D4_Paleoclimate/solutions/W1D4_Tutorial9_Solution_ff1cd22c.py
@@ -3,4 +3,4 @@
 1.In the span of the last 24,000 years, there has been a considerable shift in global temperatures, transitioning from the colder phase of the Last Glacial Maximum to the relatively warmer Holocene epoch we are currently experiencing. This transformation was not linear, with periods of rapid warming interspersed with intervals of relative stability or even temporary cooling.
 2.The increase in temperature around 17,000 years ago was likely driven by a combination of climate forcings: obliquity and eccentricity, both affect the amount of solar radiation reaching the Earth's surface.
 
-""";
\ No newline at end of file
+"""
\ No newline at end of file
diff --git a/tutorials/W1D4_Paleoclimate/static/W1D4_Tutorial3_Solution_ead41c6f_1.png b/tutorials/W1D4_Paleoclimate/static/W1D4_Tutorial3_Solution_ead41c6f_1.png
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diff --git a/tutorials/W1D4_Paleoclimate/student/W1D4_Intro.ipynb b/tutorials/W1D4_Paleoclimate/student/W1D4_Intro.ipynb
index 908d9d6ed..b6b422850 100644
--- a/tutorials/W1D4_Paleoclimate/student/W1D4_Intro.ipynb
+++ b/tutorials/W1D4_Paleoclimate/student/W1D4_Intro.ipynb
@@ -58,6 +58,36 @@
     "3. Explain the benefits and limitations of reanalysis products for paleoclimate analysis."
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "eb2c1de5-858c-41e5-81b9-4909854dbd27",
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D4_Intro\""
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "6695fea7",
@@ -126,6 +156,20 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "5794e217-8ac9-4391-becc-685aeaa33ba4",
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Past_Climates_Inform_Our_Future_Video\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "a17e786a",
@@ -152,14 +196,22 @@
     "\n",
     "link_id = \"2pvrs\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "2562974f-c9a0-4d70-91b6-87f22e0d2276",
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Past_Climates_Inform_Our_Future_Slides\")"
    ]
   }
  ],
diff --git a/tutorials/W1D4_Paleoclimate/student/W1D4_Tutorial1.ipynb b/tutorials/W1D4_Paleoclimate/student/W1D4_Tutorial1.ipynb
index a64569b88..70532f2d5 100644
--- a/tutorials/W1D4_Paleoclimate/student/W1D4_Tutorial1.ipynb
+++ b/tutorials/W1D4_Paleoclimate/student/W1D4_Tutorial1.ipynb
@@ -67,7 +67,6 @@
    "source": [
     "# installations ( uncomment and run this cell ONLY when using google colab or kaggle )\n",
     "\n",
-    "# !pip install --no-binary shapely shapely --force # Add this to use cartopy. in this way it doesn't crush\n",
     "# !pip install cartopy\n",
     "# !pip install LiPD"
    ]
@@ -94,6 +93,35 @@
     "import cartopy.feature as cfeature"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D4_T1\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -298,6 +326,19 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_What_is_Paleoclimate_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -319,14 +360,21 @@
     "\n",
     "link_id = \"ae894\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_What_is_Paleoclimate_Slides\")"
    ]
   },
   {
@@ -605,6 +653,19 @@
     "\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_3\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
diff --git a/tutorials/W1D4_Paleoclimate/student/W1D4_Tutorial2.ipynb b/tutorials/W1D4_Paleoclimate/student/W1D4_Tutorial2.ipynb
index 96850d25d..52cbf420c 100644
--- a/tutorials/W1D4_Paleoclimate/student/W1D4_Tutorial2.ipynb
+++ b/tutorials/W1D4_Paleoclimate/student/W1D4_Tutorial2.ipynb
@@ -116,6 +116,35 @@
     "from matplotlib import patches"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D4_T2\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -220,6 +249,19 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Ocean_Climate_Proxies_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -241,14 +283,21 @@
     "\n",
     "link_id = \"qtkbv\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Ocean_Climate_Proxies_Slides\")"
    ]
   },
   {
@@ -637,17 +686,30 @@
     "execution": {}
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D4_Paleoclimate/solutions/W1D4_Tutorial2_Solution_2c43ca48.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D4_Paleoclimate/solutions/W1D4_Tutorial2_Solution_8f319b78.py)\n",
     "\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_2\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
     "execution": {}
    },
    "source": [
-    "# Section 1.3: Make Warming Stripes Plot"
+    "# Section 3: Make Warming Stripes Plot"
    ]
   },
   {
diff --git a/tutorials/W1D4_Paleoclimate/student/W1D4_Tutorial3.ipynb b/tutorials/W1D4_Paleoclimate/student/W1D4_Tutorial3.ipynb
index bbda0d4e4..744abc26a 100644
--- a/tutorials/W1D4_Paleoclimate/student/W1D4_Tutorial3.ipynb
+++ b/tutorials/W1D4_Paleoclimate/student/W1D4_Tutorial3.ipynb
@@ -69,7 +69,7 @@
     "\n",
     "# !pip install LiPD\n",
     "# !pip install cartopy\n",
-    "# !pip install pyleoclim"
+    "# !pip install pyleoclim==0.14.0"
    ]
   },
   {
@@ -94,6 +94,35 @@
     "import sys"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D4_T3\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -221,6 +250,19 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Terrestrial_Climate_Proxies_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -242,14 +284,21 @@
     "\n",
     "link_id = \"6gcsh\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Terrestrial_Climate_Proxies_Slides\")"
    ]
   },
   {
@@ -603,6 +652,19 @@
     "\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Coding_Exercises_2\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -720,6 +782,19 @@
     "\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_2\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
diff --git a/tutorials/W1D4_Paleoclimate/student/W1D4_Tutorial4.ipynb b/tutorials/W1D4_Paleoclimate/student/W1D4_Tutorial4.ipynb
index 641b619cb..29b2a9b67 100644
--- a/tutorials/W1D4_Paleoclimate/student/W1D4_Tutorial4.ipynb
+++ b/tutorials/W1D4_Paleoclimate/student/W1D4_Tutorial4.ipynb
@@ -66,8 +66,7 @@
    "source": [
     "# installations ( uncomment and run this cell ONLY when using google colab or kaggle )\n",
     "\n",
-    "# !pip install pyleoclim\n",
-    "# !pip install cartopy"
+    "# !pip install pyleoclim"
    ]
   },
   {
@@ -87,6 +86,35 @@
     "import pyleoclim as pyleo"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D4_T4\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -191,6 +219,19 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Atmospheric_Climate_Proxies_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -212,14 +253,21 @@
     "\n",
     "link_id = \"szyhp\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Atmospheric_Climate_Proxies_Slides\")"
    ]
   },
   {
@@ -496,10 +544,23 @@
     "execution": {}
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D4_Paleoclimate/solutions/W1D4_Tutorial4_Solution_b7a1b0c7.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D4_Paleoclimate/solutions/W1D4_Tutorial4_Solution_0c62ceb1.py)\n",
     "\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_2\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
diff --git a/tutorials/W1D4_Paleoclimate/student/W1D4_Tutorial5.ipynb b/tutorials/W1D4_Paleoclimate/student/W1D4_Tutorial5.ipynb
index d8c96af75..1a9804a65 100644
--- a/tutorials/W1D4_Paleoclimate/student/W1D4_Tutorial5.ipynb
+++ b/tutorials/W1D4_Paleoclimate/student/W1D4_Tutorial5.ipynb
@@ -89,6 +89,35 @@
     "from sklearn.decomposition import PCA"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D4_T5\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -193,6 +222,19 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Proxy_Data_Analysis_Tools_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -214,14 +256,21 @@
     "\n",
     "link_id = \"ujbqz\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Proxy_Data_Analysis_Tools_Slides\")"
    ]
   },
   {
@@ -588,6 +637,19 @@
     "\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Coding_Exercises_2_2\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -976,10 +1038,23 @@
     "execution": {}
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D4_Paleoclimate/solutions/W1D4_Tutorial5_Solution_599669bd.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D4_Paleoclimate/solutions/W1D4_Tutorial5_Solution_b2ed69d2.py)\n",
     "\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_3\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
diff --git a/tutorials/W1D4_Paleoclimate/student/W1D4_Tutorial6.ipynb b/tutorials/W1D4_Paleoclimate/student/W1D4_Tutorial6.ipynb
index 1270792a1..6a2fcd040 100644
--- a/tutorials/W1D4_Paleoclimate/student/W1D4_Tutorial6.ipynb
+++ b/tutorials/W1D4_Paleoclimate/student/W1D4_Tutorial6.ipynb
@@ -88,6 +88,35 @@
     "import pyleoclim as pyleo"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D4_T6\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -192,6 +221,19 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Spectral_Analysis_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -213,14 +255,21 @@
     "\n",
     "link_id = \"g7rp4\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Spectral_Analysis_Slides\")"
    ]
   },
   {
@@ -352,10 +401,23 @@
     "execution": {}
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D4_Paleoclimate/solutions/W1D4_Tutorial6_Solution_7ad0d4e6.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D4_Paleoclimate/solutions/W1D4_Tutorial6_Solution_a75a63b1.py)\n",
     "\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_1\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -632,6 +694,19 @@
     "\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_2_3\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
diff --git a/tutorials/W1D4_Paleoclimate/student/W1D4_Tutorial7.ipynb b/tutorials/W1D4_Paleoclimate/student/W1D4_Tutorial7.ipynb
index ed35afa98..a85dbfd9a 100644
--- a/tutorials/W1D4_Paleoclimate/student/W1D4_Tutorial7.ipynb
+++ b/tutorials/W1D4_Paleoclimate/student/W1D4_Tutorial7.ipynb
@@ -108,6 +108,35 @@
     "from climlab.solar.insolation import daily_insolation"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D4_T7\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -212,6 +241,19 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Interpreting_Climate_Forcings_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -233,14 +275,21 @@
     "\n",
     "link_id = \"ztfwk\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Interpreting_Climate_Forcings_Slides\")"
    ]
   },
   {
@@ -412,10 +461,23 @@
     "\n",
     "*Example output:*\n",
     "\n",
-    "<img alt='Solution hint' align='left' width=974.0 height=374.0 src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D4_Paleoclimate/static/W1D4_Tutorial7_Solution_9d3f401b_8.png>\n",
+    "<img alt='Solution hint' align='left' width=974.0 height=375.0 src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D4_Paleoclimate/static/W1D4_Tutorial7_Solution_9d3f401b_8.png>\n",
     "\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Coding_Exercises_1\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -589,10 +651,23 @@
     "execution": {}
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D4_Paleoclimate/solutions/W1D4_Tutorial7_Solution_ae0c8527.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D4_Paleoclimate/solutions/W1D4_Tutorial7_Solution_f88c4da6.py)\n",
     "\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_2\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
diff --git a/tutorials/W1D4_Paleoclimate/student/W1D4_Tutorial8.ipynb b/tutorials/W1D4_Paleoclimate/student/W1D4_Tutorial8.ipynb
index c151ac30a..4dae7213b 100644
--- a/tutorials/W1D4_Paleoclimate/student/W1D4_Tutorial8.ipynb
+++ b/tutorials/W1D4_Paleoclimate/student/W1D4_Tutorial8.ipynb
@@ -91,6 +91,35 @@
     "import pyleoclim as pyleo"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D4_T8\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -195,6 +224,19 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Paleoclimate_Models_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -216,14 +258,21 @@
     "\n",
     "link_id = \"7p3zv\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Paleoclimate_Models_Slides\")"
    ]
   },
   {
@@ -313,10 +362,23 @@
     "execution": {}
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D4_Paleoclimate/solutions/W1D4_Tutorial8_Solution_5bf60405.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D4_Paleoclimate/solutions/W1D4_Tutorial8_Solution_243939d2.py)\n",
     "\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_1\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -579,10 +641,23 @@
     "execution": {}
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D4_Paleoclimate/solutions/W1D4_Tutorial8_Solution_233de275.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D4_Paleoclimate/solutions/W1D4_Tutorial8_Solution_c7fb7c84.py)\n",
     "\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_2\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -664,10 +739,23 @@
     "execution": {}
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D4_Paleoclimate/solutions/W1D4_Tutorial8_Solution_743a99c5.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D4_Paleoclimate/solutions/W1D4_Tutorial8_Solution_278fb208.py)\n",
     "\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_3\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
diff --git a/tutorials/W1D4_Paleoclimate/student/W1D4_Tutorial9.ipynb b/tutorials/W1D4_Paleoclimate/student/W1D4_Tutorial9.ipynb
index 421af5141..4bbd44971 100644
--- a/tutorials/W1D4_Paleoclimate/student/W1D4_Tutorial9.ipynb
+++ b/tutorials/W1D4_Paleoclimate/student/W1D4_Tutorial9.ipynb
@@ -92,6 +92,35 @@
     "import cartopy.crs as ccrs"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D4_T9\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -196,6 +225,19 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Paleoclimate_Data_Assimilation_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -217,14 +259,21 @@
     "\n",
     "link_id = \"f2ynq\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Paleoclimate_Data_Assimilation_Slides\")"
    ]
   },
   {
@@ -360,10 +409,23 @@
     "execution": {}
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D4_Paleoclimate/solutions/W1D4_Tutorial9_Solution_ace0594e.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D4_Paleoclimate/solutions/W1D4_Tutorial9_Solution_ff1cd22c.py)\n",
     "\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_1_1\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -486,7 +548,7 @@
     "execution": {}
    },
    "source": [
-    "### Questions 1.1: Climate Connection\n",
+    "### Questions 1.2: Climate Connection\n",
     "\n",
     "Looking at both the map and zonal mean plot, consider the following questions: \n",
     "\n",
@@ -501,10 +563,23 @@
     "execution": {}
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D4_Paleoclimate/solutions/W1D4_Tutorial9_Solution_59159894.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D4_Paleoclimate/solutions/W1D4_Tutorial9_Solution_36373365.py)\n",
     "\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_1_2\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
diff --git a/tutorials/W1D5_IntroductiontoClimateModeling/README.md b/tutorials/W1D5_IntroductiontoClimateModeling/README.md
index 9ae99d105..29bad2477 100644
--- a/tutorials/W1D5_IntroductiontoClimateModeling/README.md
+++ b/tutorials/W1D5_IntroductiontoClimateModeling/README.md
@@ -1,33 +1,53 @@
-# W1D5 - Climate Modeling
+# W1D5 - Introductionto Climate Modeling
 
 ## Instructor notebooks
 
 |   | Run | Run | View |
 | - | --- | --- | ---- |
-| Intro | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_ClimateModeling/W1D5_Intro.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_ClimateModeling/W1D5_Intro.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_ClimateModeling/W1D5_Intro.ipynb?flush_cache=true) |
-| Tutorial 1 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_ClimateModeling/instructor/W1D5_Tutorial1.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_ClimateModeling/instructor/W1D5_Tutorial1.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_ClimateModeling/instructor/W1D5_Tutorial1.ipynb?flush_cache=true) |
-| Tutorial 2 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_ClimateModeling/instructor/W1D5_Tutorial2.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_ClimateModeling/instructor/W1D5_Tutorial2.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_ClimateModeling/instructor/W1D5_Tutorial2.ipynb?flush_cache=true) |
-| Tutorial 3 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_ClimateModeling/instructor/W1D5_Tutorial3.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_ClimateModeling/instructor/W1D5_Tutorial3.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_ClimateModeling/instructor/W1D5_Tutorial3.ipynb?flush_cache=true) |
-| Tutorial 4 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_ClimateModeling/instructor/W1D5_Tutorial4.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_ClimateModeling/instructor/W1D5_Tutorial4.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_ClimateModeling/instructor/W1D5_Tutorial4.ipynb?flush_cache=true) |
-| Tutorial 5 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_ClimateModeling/instructor/W1D5_Tutorial5.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_ClimateModeling/instructor/W1D5_Tutorial5.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_ClimateModeling/instructor/W1D5_Tutorial5.ipynb?flush_cache=true) |
-| Tutorial 6 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_ClimateModeling/instructor/W1D5_Tutorial6.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_ClimateModeling/instructor/W1D5_Tutorial6.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_ClimateModeling/instructor/W1D5_Tutorial6.ipynb?flush_cache=true) |
-| Tutorial 7 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_ClimateModeling/instructor/W1D5_Tutorial7.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_ClimateModeling/instructor/W1D5_Tutorial7.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_ClimateModeling/instructor/W1D5_Tutorial7.ipynb?flush_cache=true) |
-| Tutorial 8 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_ClimateModeling/instructor/W1D5_Tutorial8.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_ClimateModeling/instructor/W1D5_Tutorial8.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_ClimateModeling/instructor/W1D5_Tutorial8.ipynb?flush_cache=true) |
-| Outro | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_ClimateModeling/W1D5_Outro.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_ClimateModeling/W1D5_Outro.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_ClimateModeling/W1D5_Outro.ipynb?flush_cache=true) |
+| DaySummary | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/W1D5_DaySummary.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_IntroductiontoClimateModeling/W1D5_DaySummary.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/W1D5_DaySummary.ipynb?flush_cache=true) |
+| Intro | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/W1D5_Intro.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_IntroductiontoClimateModeling/W1D5_Intro.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/W1D5_Intro.ipynb?flush_cache=true) |
+| Outro | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/W1D5_Outro.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_IntroductiontoClimateModeling/W1D5_Outro.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/W1D5_Outro.ipynb?flush_cache=true) |
+| Tutorial 1 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/instructor/W1D5_Tutorial1.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_IntroductiontoClimateModeling/instructor/W1D5_Tutorial1.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/instructor/W1D5_Tutorial1.ipynb?flush_cache=true) |
+| Tutorial 2 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/instructor/W1D5_Tutorial2.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_IntroductiontoClimateModeling/instructor/W1D5_Tutorial2.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/instructor/W1D5_Tutorial2.ipynb?flush_cache=true) |
+| Tutorial 3 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/instructor/W1D5_Tutorial3.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_IntroductiontoClimateModeling/instructor/W1D5_Tutorial3.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/instructor/W1D5_Tutorial3.ipynb?flush_cache=true) |
+| Tutorial 4 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/instructor/W1D5_Tutorial4.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_IntroductiontoClimateModeling/instructor/W1D5_Tutorial4.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/instructor/W1D5_Tutorial4.ipynb?flush_cache=true) |
+| Tutorial 5 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/instructor/W1D5_Tutorial5.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_IntroductiontoClimateModeling/instructor/W1D5_Tutorial5.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/instructor/W1D5_Tutorial5.ipynb?flush_cache=true) |
+| Tutorial 6 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/instructor/W1D5_Tutorial6.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_IntroductiontoClimateModeling/instructor/W1D5_Tutorial6.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/instructor/W1D5_Tutorial6.ipynb?flush_cache=true) |
+| Tutorial 7 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/instructor/W1D5_Tutorial7.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_IntroductiontoClimateModeling/instructor/W1D5_Tutorial7.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/instructor/W1D5_Tutorial7.ipynb?flush_cache=true) |
+| Tutorial 8 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/instructor/W1D5_Tutorial8.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_IntroductiontoClimateModeling/instructor/W1D5_Tutorial8.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/instructor/W1D5_Tutorial8.ipynb?flush_cache=true) |
+| Tutorial 1 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/instructor/W1D5_Tutorial1.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_IntroductiontoClimateModeling/instructor/W1D5_Tutorial1.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/instructor/W1D5_Tutorial1.ipynb?flush_cache=true) |
+| Tutorial 2 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/instructor/W1D5_Tutorial2.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_IntroductiontoClimateModeling/instructor/W1D5_Tutorial2.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/instructor/W1D5_Tutorial2.ipynb?flush_cache=true) |
+| Tutorial 3 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/instructor/W1D5_Tutorial3.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_IntroductiontoClimateModeling/instructor/W1D5_Tutorial3.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/instructor/W1D5_Tutorial3.ipynb?flush_cache=true) |
+| Tutorial 4 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/instructor/W1D5_Tutorial4.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_IntroductiontoClimateModeling/instructor/W1D5_Tutorial4.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/instructor/W1D5_Tutorial4.ipynb?flush_cache=true) |
+| Tutorial 5 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/instructor/W1D5_Tutorial5.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_IntroductiontoClimateModeling/instructor/W1D5_Tutorial5.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/instructor/W1D5_Tutorial5.ipynb?flush_cache=true) |
+| Tutorial 6 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/instructor/W1D5_Tutorial6.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_IntroductiontoClimateModeling/instructor/W1D5_Tutorial6.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/instructor/W1D5_Tutorial6.ipynb?flush_cache=true) |
+| Tutorial 7 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/instructor/W1D5_Tutorial7.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_IntroductiontoClimateModeling/instructor/W1D5_Tutorial7.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/instructor/W1D5_Tutorial7.ipynb?flush_cache=true) |
+| Tutorial 8 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/instructor/W1D5_Tutorial8.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_IntroductiontoClimateModeling/instructor/W1D5_Tutorial8.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/instructor/W1D5_Tutorial8.ipynb?flush_cache=true) |
+| Outro | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/W1D5_Outro.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_IntroductiontoClimateModeling/W1D5_Outro.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/W1D5_Outro.ipynb?flush_cache=true) |
 
 
 ## Student notebooks
 
 |   | Run | Run | View |
 | - | --- | --- | ---- |
-| Intro | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_ClimateModeling/W1D5_Intro.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_ClimateModeling/W1D5_Intro.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_ClimateModeling/W1D5_Intro.ipynb?flush_cache=true) |
-| Tutorial 1 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_ClimateModeling/student/W1D5_Tutorial1.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_ClimateModeling/student/W1D5_Tutorial1.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_ClimateModeling/student/W1D5_Tutorial1.ipynb?flush_cache=true) |
-| Tutorial 2 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_ClimateModeling/student/W1D5_Tutorial2.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_ClimateModeling/student/W1D5_Tutorial2.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_ClimateModeling/student/W1D5_Tutorial2.ipynb?flush_cache=true) |
-| Tutorial 3 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_ClimateModeling/student/W1D5_Tutorial3.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_ClimateModeling/student/W1D5_Tutorial3.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_ClimateModeling/student/W1D5_Tutorial3.ipynb?flush_cache=true) |
-| Tutorial 4 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_ClimateModeling/student/W1D5_Tutorial4.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_ClimateModeling/student/W1D5_Tutorial4.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_ClimateModeling/student/W1D5_Tutorial4.ipynb?flush_cache=true) |
-| Tutorial 5 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_ClimateModeling/student/W1D5_Tutorial5.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_ClimateModeling/student/W1D5_Tutorial5.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_ClimateModeling/student/W1D5_Tutorial5.ipynb?flush_cache=true) |
-| Tutorial 6 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_ClimateModeling/student/W1D5_Tutorial6.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_ClimateModeling/student/W1D5_Tutorial6.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_ClimateModeling/student/W1D5_Tutorial6.ipynb?flush_cache=true) |
-| Tutorial 7 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_ClimateModeling/student/W1D5_Tutorial7.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_ClimateModeling/student/W1D5_Tutorial7.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_ClimateModeling/student/W1D5_Tutorial7.ipynb?flush_cache=true) |
-| Tutorial 8 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_ClimateModeling/student/W1D5_Tutorial8.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_ClimateModeling/student/W1D5_Tutorial8.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_ClimateModeling/student/W1D5_Tutorial8.ipynb?flush_cache=true) |
-| Outro | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_ClimateModeling/W1D5_Outro.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_ClimateModeling/W1D5_Outro.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_ClimateModeling/W1D5_Outro.ipynb?flush_cache=true) |
+| DaySummary | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/W1D5_DaySummary.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_IntroductiontoClimateModeling/W1D5_DaySummary.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/W1D5_DaySummary.ipynb?flush_cache=true) |
+| Intro | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/W1D5_Intro.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_IntroductiontoClimateModeling/W1D5_Intro.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/W1D5_Intro.ipynb?flush_cache=true) |
+| Outro | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/W1D5_Outro.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_IntroductiontoClimateModeling/W1D5_Outro.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/W1D5_Outro.ipynb?flush_cache=true) |
+| Tutorial 1 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial1.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial1.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial1.ipynb?flush_cache=true) |
+| Tutorial 2 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial2.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial2.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial2.ipynb?flush_cache=true) |
+| Tutorial 3 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial3.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial3.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial3.ipynb?flush_cache=true) |
+| Tutorial 4 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial4.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial4.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial4.ipynb?flush_cache=true) |
+| Tutorial 5 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial5.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial5.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial5.ipynb?flush_cache=true) |
+| Tutorial 6 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial6.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial6.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial6.ipynb?flush_cache=true) |
+| Tutorial 7 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial7.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial7.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial7.ipynb?flush_cache=true) |
+| Tutorial 8 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial8.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial8.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial8.ipynb?flush_cache=true) |
+| Tutorial 1 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial1.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial1.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial1.ipynb?flush_cache=true) |
+| Tutorial 2 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial2.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial2.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial2.ipynb?flush_cache=true) |
+| Tutorial 3 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial3.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial3.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial3.ipynb?flush_cache=true) |
+| Tutorial 4 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial4.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial4.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial4.ipynb?flush_cache=true) |
+| Tutorial 5 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial5.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial5.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial5.ipynb?flush_cache=true) |
+| Tutorial 6 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial6.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial6.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial6.ipynb?flush_cache=true) |
+| Tutorial 7 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial7.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial7.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial7.ipynb?flush_cache=true) |
+| Tutorial 8 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial8.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial8.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial8.ipynb?flush_cache=true) |
+| Outro | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/W1D5_Outro.ipynb) | [![Open In kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_IntroductiontoClimateModeling/W1D5_Outro.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/neuromatch/climate-course-content/blob/main/tutorials/W1D5_IntroductiontoClimateModeling/W1D5_Outro.ipynb?flush_cache=true) |
 
diff --git a/tutorials/W1D5_IntroductiontoClimateModeling/W1D5_Intro.ipynb b/tutorials/W1D5_IntroductiontoClimateModeling/W1D5_Intro.ipynb
index 61496bc6e..5b2b3b25e 100644
--- a/tutorials/W1D5_IntroductiontoClimateModeling/W1D5_Intro.ipynb
+++ b/tutorials/W1D5_IntroductiontoClimateModeling/W1D5_Intro.ipynb
@@ -60,7 +60,10 @@
    "cell_type": "code",
    "execution_count": null,
    "id": "2c799e08-2a4d-407e-bbc6-ce745e770fec",
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Install and import feedback gadget\n",
@@ -98,7 +101,8 @@
    "execution_count": null,
    "id": "a8dd85d1",
    "metadata": {
-    "cellView": "form"
+    "cellView": "form",
+    "execution": {}
    },
    "outputs": [],
    "source": [
@@ -154,7 +158,10 @@
    "cell_type": "code",
    "execution_count": null,
    "id": "c7420af4-ba59-43b7-a946-8eeb4e5bff71",
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -176,7 +183,8 @@
    "execution_count": null,
    "id": "bd95be61",
    "metadata": {
-    "cellView": "form"
+    "cellView": "form",
+    "execution": {}
    },
    "outputs": [],
    "source": [
@@ -194,7 +202,10 @@
    "cell_type": "code",
    "execution_count": null,
    "id": "8341016f-e8ab-4a65-9ff8-c619041f3da3",
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -229,7 +240,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.18"
+   "version": "3.9.19"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/W1D5_IntroductiontoClimateModeling/W1D5_Tutorial1.ipynb b/tutorials/W1D5_IntroductiontoClimateModeling/W1D5_Tutorial1.ipynb
index 67fd912a3..1071ee6ee 100644
--- a/tutorials/W1D5_IntroductiontoClimateModeling/W1D5_Tutorial1.ipynb
+++ b/tutorials/W1D5_IntroductiontoClimateModeling/W1D5_Tutorial1.ipynb
@@ -61,7 +61,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# imports\n",
@@ -72,7 +74,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Install and import feedback gadget\n",
@@ -99,7 +104,8 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "form"
+    "cellView": "form",
+    "execution": {}
    },
    "outputs": [],
    "source": [
@@ -117,6 +123,7 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -174,6 +181,7 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -229,7 +237,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -240,7 +251,8 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "form"
+    "cellView": "form",
+    "execution": {}
    },
    "outputs": [],
    "source": [
@@ -257,7 +269,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -321,7 +336,8 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "form"
+    "cellView": "form",
+    "execution": {}
    },
    "outputs": [],
    "source": [
@@ -415,7 +431,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# to_remove explanation\n",
@@ -428,7 +446,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -471,6 +492,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 33,
      "status": "ok",
@@ -520,7 +542,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# to_remove explanation\n",
@@ -535,7 +559,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -564,6 +591,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 31,
      "status": "ok",
@@ -594,6 +622,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 27,
      "status": "ok",
@@ -625,7 +654,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -706,6 +738,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 22,
      "status": "ok",
@@ -758,7 +791,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# to_remove explanation\n",
@@ -775,7 +810,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -804,6 +842,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 401,
      "status": "ok",
@@ -842,6 +881,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 5,
      "status": "ok",
@@ -881,7 +921,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -915,7 +958,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# define the emission temperature of the sun\n",
@@ -982,7 +1027,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# to_remove solution\n",
@@ -1058,7 +1105,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -1126,7 +1176,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.18"
+   "version": "3.9.19"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/W1D5_IntroductiontoClimateModeling/W1D5_Tutorial2.ipynb b/tutorials/W1D5_IntroductiontoClimateModeling/W1D5_Tutorial2.ipynb
index 5df999086..b7bfa2173 100644
--- a/tutorials/W1D5_IntroductiontoClimateModeling/W1D5_Tutorial2.ipynb
+++ b/tutorials/W1D5_IntroductiontoClimateModeling/W1D5_Tutorial2.ipynb
@@ -65,6 +65,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": [
      "colab"
     ]
@@ -79,7 +80,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Install and import feedback gadget\n",
@@ -106,7 +110,8 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "form"
+    "cellView": "form",
+    "execution": {}
    },
    "outputs": [],
    "source": [
@@ -124,6 +129,7 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -179,7 +185,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -191,6 +200,7 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
+    "execution": {},
     "pycharm": {
      "name": "#%%\n"
     },
@@ -213,7 +223,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -284,6 +297,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 17,
      "status": "ok",
@@ -332,7 +346,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# to_remove explanation\n",
@@ -346,7 +362,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -380,7 +399,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# plug into equation\n",
@@ -405,7 +426,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# to_remove explanation\n",
@@ -419,7 +442,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -477,6 +503,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 236,
      "status": "ok",
@@ -536,6 +563,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 4,
      "status": "ok",
@@ -581,7 +609,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# to_remove explanation\n",
@@ -595,7 +625,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -623,7 +656,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# define the observed insolation based on observations from the IPCC AR6 Figure 7.2\n",
@@ -661,6 +696,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 5,
      "status": "ok",
@@ -710,7 +746,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -779,7 +818,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.18"
+   "version": "3.9.19"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/W1D5_IntroductiontoClimateModeling/W1D5_Tutorial3.ipynb b/tutorials/W1D5_IntroductiontoClimateModeling/W1D5_Tutorial3.ipynb
index 3cc348d09..16bb8069f 100644
--- a/tutorials/W1D5_IntroductiontoClimateModeling/W1D5_Tutorial3.ipynb
+++ b/tutorials/W1D5_IntroductiontoClimateModeling/W1D5_Tutorial3.ipynb
@@ -65,6 +65,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": [
      "colab"
     ]
@@ -79,7 +80,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Install and import feedback gadget\n",
@@ -106,7 +110,8 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "form"
+    "cellView": "form",
+    "execution": {}
    },
    "outputs": [],
    "source": [
@@ -124,6 +129,7 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -188,7 +194,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -200,6 +209,7 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
+    "execution": {},
     "pycharm": {
      "name": "#%%\n"
     },
@@ -222,7 +232,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -303,7 +316,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# heat capacity of the ocean\n",
@@ -349,6 +364,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 308,
      "status": "ok",
@@ -380,6 +396,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 310,
      "status": "ok",
@@ -412,7 +429,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -440,7 +460,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# to_remove explanation\n",
@@ -454,7 +476,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -498,7 +523,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# define the time interval, currently one year expressed in seconds\n",
@@ -548,6 +575,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 6,
      "status": "ok",
@@ -589,6 +617,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 177,
      "status": "ok",
@@ -610,6 +639,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 921,
      "status": "ok",
@@ -651,7 +681,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# to_remove explanation\n",
@@ -664,7 +696,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -693,6 +728,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 165,
      "status": "error",
@@ -746,6 +782,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 1096,
      "status": "ok",
@@ -800,7 +837,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -838,6 +878,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 942,
      "status": "ok",
@@ -899,7 +940,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# to_remove explanation\n",
@@ -912,7 +955,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -944,7 +990,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# define your functions and constants\n",
@@ -1011,7 +1059,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# to_remove solution\n",
@@ -1077,7 +1127,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -1096,7 +1149,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# run the model to equilibrium without forcing and begining with T(0) = 288K\n",
@@ -1125,7 +1180,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# to_remove solution\n",
@@ -1156,7 +1213,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -1175,7 +1235,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# define the number of timesteps (years) to run the model\n",
@@ -1202,7 +1264,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# to_remove solution\n",
@@ -1235,7 +1299,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -1254,7 +1321,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# plot the time series\n",
@@ -1268,7 +1337,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# to_remove solution\n",
@@ -1284,7 +1355,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -1303,7 +1377,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# calculate equilibrium climate sensitivity\n",
@@ -1314,7 +1390,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# to_remove solution\n",
@@ -1327,7 +1405,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -1357,7 +1438,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# to_remove explanation\n",
@@ -1372,7 +1455,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -1442,7 +1528,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.18"
+   "version": "3.9.19"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/W1D5_IntroductiontoClimateModeling/W1D5_Tutorial4.ipynb b/tutorials/W1D5_IntroductiontoClimateModeling/W1D5_Tutorial4.ipynb
index c51490787..065638854 100644
--- a/tutorials/W1D5_IntroductiontoClimateModeling/W1D5_Tutorial4.ipynb
+++ b/tutorials/W1D5_IntroductiontoClimateModeling/W1D5_Tutorial4.ipynb
@@ -91,7 +91,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Install and import feedback gadget\n",
@@ -203,7 +206,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -238,7 +244,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -397,7 +406,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -549,7 +561,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -777,7 +792,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -890,7 +908,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -1016,7 +1037,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -1084,7 +1108,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.18"
+   "version": "3.9.19"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/W1D5_IntroductiontoClimateModeling/W1D5_Tutorial5.ipynb b/tutorials/W1D5_IntroductiontoClimateModeling/W1D5_Tutorial5.ipynb
index 27fbe6865..fa2f456d0 100644
--- a/tutorials/W1D5_IntroductiontoClimateModeling/W1D5_Tutorial5.ipynb
+++ b/tutorials/W1D5_IntroductiontoClimateModeling/W1D5_Tutorial5.ipynb
@@ -63,6 +63,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 161558,
      "status": "ok",
@@ -96,6 +97,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 10496,
      "status": "ok",
@@ -127,7 +129,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Install and import feedback gadget\n",
@@ -155,6 +160,7 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
+    "execution": {},
     "executionInfo": {
      "elapsed": 418,
      "status": "ok",
@@ -181,7 +187,8 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "form"
+    "cellView": "form",
+    "execution": {}
    },
    "outputs": [],
    "source": [
@@ -211,6 +218,7 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -276,7 +284,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -288,6 +299,7 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
+    "execution": {},
     "pycharm": {
      "name": "#%%\n"
     },
@@ -310,7 +322,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -345,6 +360,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 121302,
      "status": "ok",
@@ -370,7 +386,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# the specific humidity is stored in a variable called Q\n",
@@ -380,7 +398,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "ds.time"
@@ -399,6 +419,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 5500,
      "status": "ok",
@@ -433,6 +454,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 148,
      "status": "ok",
@@ -464,6 +486,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 3619,
      "status": "ok",
@@ -501,6 +524,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 115,
      "status": "ok",
@@ -532,6 +556,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 158,
      "status": "ok",
@@ -561,6 +586,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 125,
      "status": "ok",
@@ -590,6 +616,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 287,
      "status": "ok",
@@ -620,6 +647,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 158,
      "status": "ok",
@@ -666,7 +694,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# to_remove explanation\n",
@@ -679,7 +709,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -707,7 +740,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "fig, ax = plt.subplots()\n",
@@ -736,6 +771,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 2400,
      "status": "ok",
@@ -775,7 +811,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -804,6 +843,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 979,
      "status": "ok",
@@ -831,6 +871,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 7,
      "status": "ok",
@@ -865,7 +906,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# to setup the skewT and plot observations\n",
@@ -901,7 +944,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# to add a model derived profile to the skewT figure\n",
@@ -926,6 +971,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 2544,
      "status": "ok",
@@ -974,7 +1020,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# take a single step forward to the diagnostics are updated and there is some energy imbalance\n",
@@ -989,6 +1037,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 7,
      "status": "ok",
@@ -1019,6 +1068,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 2330,
      "status": "ok",
@@ -1059,7 +1109,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# to_remove explanation\n",
@@ -1073,7 +1125,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -1101,7 +1156,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# make an exact clone of our existing model\n",
@@ -1129,6 +1186,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 5291,
      "status": "ok",
@@ -1168,7 +1226,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -1232,7 +1293,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.18"
+   "version": "3.9.19"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/W1D5_IntroductiontoClimateModeling/W1D5_Tutorial6.ipynb b/tutorials/W1D5_IntroductiontoClimateModeling/W1D5_Tutorial6.ipynb
index 76057793c..7415ced6b 100644
--- a/tutorials/W1D5_IntroductiontoClimateModeling/W1D5_Tutorial6.ipynb
+++ b/tutorials/W1D5_IntroductiontoClimateModeling/W1D5_Tutorial6.ipynb
@@ -131,7 +131,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Install and import feedback gadget\n",
@@ -411,7 +414,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -446,7 +452,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -703,7 +712,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -795,7 +807,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -857,7 +872,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.18"
+   "version": "3.9.19"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/W1D5_IntroductiontoClimateModeling/W1D5_Tutorial7.ipynb b/tutorials/W1D5_IntroductiontoClimateModeling/W1D5_Tutorial7.ipynb
index 183f8b2a6..7a651e355 100644
--- a/tutorials/W1D5_IntroductiontoClimateModeling/W1D5_Tutorial7.ipynb
+++ b/tutorials/W1D5_IntroductiontoClimateModeling/W1D5_Tutorial7.ipynb
@@ -60,6 +60,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": [
      "colab"
     ]
@@ -81,6 +82,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 2,
      "status": "ok",
@@ -113,7 +115,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Install and import feedback gadget\n",
@@ -141,6 +146,7 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -160,6 +166,7 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -215,7 +222,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -227,6 +237,7 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
+    "execution": {},
     "pycharm": {
      "name": "#%%\n"
     },
@@ -249,7 +260,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -318,7 +332,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "col = intake.open_esm_datastore(\n",
@@ -368,7 +384,9 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "source": [
     "Now we will create a subset according to the provided facets using the `.search()` method, and finally open the cloud-stored [zarr stores](https://pangeo-data.github.io/pangeo-cmip6-cloud/overview.html) into Xarray datasets. \n",
     "\n",
@@ -390,6 +408,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 6561,
      "status": "ok",
@@ -439,7 +458,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "cat.keys()"
@@ -464,6 +485,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 1011,
      "status": "ok",
@@ -508,7 +530,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "ssp585 = dt[\"TaiESM1\"][\"ssp585\"].ds\n",
@@ -527,7 +551,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "ssp585.tos"
@@ -557,6 +583,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 11488,
      "status": "ok",
@@ -618,6 +645,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 163,
      "status": "error",
@@ -679,6 +707,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 36973,
      "status": "ok",
@@ -768,7 +797,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -795,6 +827,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -811,7 +844,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -848,6 +884,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 1822,
      "status": "ok",
@@ -888,6 +925,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -903,7 +941,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -927,6 +968,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 190,
      "status": "ok",
@@ -955,6 +997,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 9588,
      "status": "ok",
@@ -980,6 +1023,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 3184,
      "status": "ok",
@@ -1006,6 +1050,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 191,
      "status": "ok",
@@ -1039,6 +1084,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 21337,
      "status": "ok",
@@ -1103,6 +1149,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -1117,7 +1164,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -1190,7 +1240,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.18"
+   "version": "3.9.19"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/W1D5_IntroductiontoClimateModeling/W1D5_Tutorial8.ipynb b/tutorials/W1D5_IntroductiontoClimateModeling/W1D5_Tutorial8.ipynb
index 4b7421720..63f3de9e0 100644
--- a/tutorials/W1D5_IntroductiontoClimateModeling/W1D5_Tutorial8.ipynb
+++ b/tutorials/W1D5_IntroductiontoClimateModeling/W1D5_Tutorial8.ipynb
@@ -66,6 +66,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 90386,
      "status": "ok",
@@ -96,6 +97,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -115,7 +117,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Install and import feedback gadget\n",
@@ -143,6 +148,7 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -162,6 +168,7 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
+    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -217,7 +224,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -229,6 +239,7 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
+    "execution": {},
     "pycharm": {
      "name": "#%%\n"
     },
@@ -251,7 +262,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -283,6 +297,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 12915,
      "status": "ok",
@@ -336,7 +351,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "dt"
@@ -362,6 +379,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 313,
      "status": "error",
@@ -410,6 +428,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 4330,
      "status": "ok",
@@ -453,7 +472,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -509,6 +531,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 296,
      "status": "error",
@@ -546,6 +569,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "execution": {},
     "executionInfo": {
      "elapsed": 31727,
      "status": "ok",
@@ -585,7 +609,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -614,7 +641,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# to_remove explanation\n",
@@ -627,7 +656,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @title Submit your feedback\n",
@@ -698,7 +730,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.18"
+   "version": "3.9.19"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/W1D5_IntroductiontoClimateModeling/instructor/W1D5_Intro.ipynb b/tutorials/W1D5_IntroductiontoClimateModeling/instructor/W1D5_Intro.ipynb
index 4570d6cab..7c23f60df 100644
--- a/tutorials/W1D5_IntroductiontoClimateModeling/instructor/W1D5_Intro.ipynb
+++ b/tutorials/W1D5_IntroductiontoClimateModeling/instructor/W1D5_Intro.ipynb
@@ -56,6 +56,36 @@
     "* Access CMIP6 Earth system model data from cloud catalogs, and manipulate it by regridding and calculating global average properties."
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "2c799e08-2a4d-407e-bbc6-ce745e770fec",
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D5_Intro\""
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "491d4b6d",
@@ -124,6 +154,20 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "c7420af4-ba59-43b7-a946-8eeb4e5bff71",
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Climate_Modeling_Video\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "f46af996",
@@ -150,14 +194,22 @@
     "\n",
     "link_id = \"y2bdn\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "8341016f-e8ab-4a65-9ff8-c619041f3da3",
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Climate_Modeling_Slides\")"
    ]
   }
  ],
diff --git a/tutorials/W1D5_IntroductiontoClimateModeling/instructor/W1D5_Tutorial1.ipynb b/tutorials/W1D5_IntroductiontoClimateModeling/instructor/W1D5_Tutorial1.ipynb
index 64be9aac5..30afa45d1 100644
--- a/tutorials/W1D5_IntroductiontoClimateModeling/instructor/W1D5_Tutorial1.ipynb
+++ b/tutorials/W1D5_IntroductiontoClimateModeling/instructor/W1D5_Tutorial1.ipynb
@@ -71,6 +71,35 @@
     "import numpy as np"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D5_T1\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -205,6 +234,19 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_A_Simple_Greenhouse_Model_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -220,14 +262,21 @@
     "\n",
     "link_id = \"3c8nq\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_A_Simple_Greenhouse_Model_Slides\")"
    ]
   },
   {
@@ -391,7 +440,20 @@
     "\n",
     "\"\"\"\n",
     "1. Infrared.\n",
-    "\"\"\";"
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_1_1\")"
    ]
   },
   {
@@ -491,7 +553,20 @@
     "1. The calculated emission temperature of approximately 255 K or -18.2 C is significantly lower than the actual global mean surface temperature of approximately 288 K or 15 C.\n",
     "2. We would expect the corresponding outgoing longwave radiation to be higher than the observed 239 W/m², according to the Stefan-Boltzmann law.\n",
     "3. As the video explains, this simple model doesn't account for the atmospheric greenhouse effect due to greenhouse gases that absorb radiation at these wavelengths.\n",
-    "\"\"\";"
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_1_2\")"
    ]
   },
   {
@@ -578,6 +653,19 @@
     "print(\"OLR: \", OLR, \"W m^2\")"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Coding_Exercises_1_2\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -718,7 +806,20 @@
     "2. It implies that Earth's atmosphere is transparent to the sun's radiation. This is not exactly true, for example ozone interacts with ultraviolet light from the sun.\n",
     "   However, Earth's atmosphere does absorb largely in the infrared.\n",
     "3. Clouds, aerosols, and scattering just to name a few.\n",
-    "\"\"\";"
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_2_2\")"
    ]
   },
   {
@@ -821,6 +922,19 @@
     "ax.set_ylabel(\"Outgoing Longwave Radiation (W m$^{-2}$)\")"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Coding_Exercises_2_2\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -838,7 +952,9 @@
     "execution": {}
    },
    "source": [
-    "### Instructions\n",
+    "### Coding Exercises 3\n",
+    "\n",
+    "**Instructions**\n",
     "\n",
     "By defining a function for Planck's Law, plot the blackbody radiation curve for the sun, assuming an emission temperature of $5800 \\text{ K}$. Underlay an approximation of the visible range from the electromagnetic spectrum. This exercise should help you understand why we see in color as well as why the sun's radiation headed towards Earth is called incoming shortwave radiation."
    ]
@@ -992,6 +1108,19 @@
     "ax.legend(bbox_to_anchor=(0.5, 0.5))"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Coding_Exercises_3\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
diff --git a/tutorials/W1D5_IntroductiontoClimateModeling/instructor/W1D5_Tutorial2.ipynb b/tutorials/W1D5_IntroductiontoClimateModeling/instructor/W1D5_Tutorial2.ipynb
index bc2283200..2b86a8b9d 100644
--- a/tutorials/W1D5_IntroductiontoClimateModeling/instructor/W1D5_Tutorial2.ipynb
+++ b/tutorials/W1D5_IntroductiontoClimateModeling/instructor/W1D5_Tutorial2.ipynb
@@ -77,6 +77,35 @@
     "import matplotlib.pyplot as plt  # used for plotting"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D5_T2\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -153,6 +182,19 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Energy_Balance_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -174,14 +216,21 @@
     "\n",
     "link_id = \"ce6mx\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Energy_Balance_Slides\")"
    ]
   },
   {
@@ -307,7 +356,20 @@
     "\"\"\"\n",
     "1. If the insolation does not vary, a low albedo implies that Earth is less reflective (e.g less cloud, snow or ice cover) and vice versa for high albedo.\n",
     "2. Both. The reflected radiation is a function of land surface changes (e.g. glaciations and vegetation changes) and clouds (water vapor changes).  The radiation from the sun has also varied over time, which you will go into more detail in tutorial 4.\n",
-    "\"\"\";"
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_1_1\")"
    ]
   },
   {
@@ -374,7 +436,20 @@
     "\"\"\"\n",
     "1. It is slightly more. This means that Earth is absorbing more energy than it is losing. This is just to get you thinking about energy balance that will be discussed in the remainder of the tutorial.\n",
     "2. It does not take these into account. For example, ozone is a notable greenhouse gas that absorbs in the UV range.\n",
-    "\"\"\";"
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_1_2\")"
    ]
   },
   {
@@ -544,7 +619,20 @@
     "\"\"\"\n",
     "1. A decrease. A lower transmissivity means the atmosphere is less transparent, and therefore less radiation escapes to space.\n",
     "2. It is much higher because the greenhouse effect is stronger and trapping more heat.\n",
-    "\"\"\";"
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_3_1\")"
    ]
   },
   {
@@ -657,6 +745,19 @@
     "ax.set_ylabel(\"Equilibrium Temperature\")"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Coding_Exercises_3_1\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
diff --git a/tutorials/W1D5_IntroductiontoClimateModeling/instructor/W1D5_Tutorial3.ipynb b/tutorials/W1D5_IntroductiontoClimateModeling/instructor/W1D5_Tutorial3.ipynb
index 0103f0db5..5169444aa 100644
--- a/tutorials/W1D5_IntroductiontoClimateModeling/instructor/W1D5_Tutorial3.ipynb
+++ b/tutorials/W1D5_IntroductiontoClimateModeling/instructor/W1D5_Tutorial3.ipynb
@@ -77,6 +77,35 @@
     "import matplotlib.pyplot as plt  # used for plotting"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D5_T3\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -162,6 +191,19 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_A_Zero_Dimensional_Energy_Balance_Model_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -183,14 +225,21 @@
     "\n",
     "link_id = \"5mgns\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_A_Zero_Dimensional_Energy_Balance_Model_Slides\")"
    ]
   },
   {
@@ -379,6 +428,19 @@
     "d_oc"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Coding_Exercises_1_1\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -413,6 +475,19 @@
     "\"\"\""
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_1_1\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -620,6 +695,19 @@
     "\"\"\""
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_1_2\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -666,7 +754,7 @@
     "numtsteps = np.array([10, 5, 1]) * 3\n",
     "\n",
     "# for converting the number of seconds in a year\n",
-    "sec_2_yr = ...\n",
+    "sec_2_yr = 3.154e7\n",
     "\n",
     "fig, ax = plt.subplots()\n",
     "# loop through each choice of time step\n",
@@ -750,6 +838,19 @@
     "ax.legend()"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Coding_Exercises_1_2\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -855,6 +956,19 @@
     "\"\"\""
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_2_1\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -1016,6 +1130,19 @@
     "    return T_new, Ftoa"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Bonus_Coding_Exercises_3_1\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -1091,6 +1218,19 @@
     "print(Ftoa)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Bonus_Coding_Exercises_3_2\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -1166,6 +1306,19 @@
     "print(Ftoa_forced)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Bonus_Coding_Exercises_3_3\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -1211,6 +1364,19 @@
     "ax.set_ylabel(\"Global mean temperature (K)\")"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Bonus_Coding_Exercises_3_4\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -1250,6 +1416,19 @@
     "print(\"Equilibrium Climate Sensitivity: \", ecs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Bonus_Coding_Exercises_3_5\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -1287,6 +1466,19 @@
     "\"\"\""
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Bonus_Questions_3\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
diff --git a/tutorials/W1D5_IntroductiontoClimateModeling/instructor/W1D5_Tutorial4.ipynb b/tutorials/W1D5_IntroductiontoClimateModeling/instructor/W1D5_Tutorial4.ipynb
index 20c043078..d276be396 100644
--- a/tutorials/W1D5_IntroductiontoClimateModeling/instructor/W1D5_Tutorial4.ipynb
+++ b/tutorials/W1D5_IntroductiontoClimateModeling/instructor/W1D5_Tutorial4.ipynb
@@ -88,6 +88,35 @@
     "from scipy.optimize import brentq  # used for numerical root-finding to get the equilibria"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D5_T4\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -174,6 +203,19 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Climate_Feedbacks_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -195,14 +237,21 @@
     "\n",
     "link_id = \"btpwx\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Climate_Feedbacks_Slides\")"
    ]
   },
   {
@@ -351,7 +400,20 @@
     "\"\"\"\n",
     "1. Three times.\n",
     "2. When the graphs intersect, it means that ASR = OLR, and thus ASR-OLR = 0. These three intersections are the three temperatures for which energy balance is satisfied in our model.\n",
-    "\"\"\";"
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_1_1\")"
    ]
   },
   {
@@ -493,7 +555,20 @@
     "1. Two. Near 235K and 305K.\n",
     "2. They are the  first and third temperatures at which the ASR and OLR curves intersect, or energy balance is achieved.\n",
     "3. Near 245K.\n",
-    "\"\"\";"
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_1_2\")"
    ]
   },
   {
@@ -711,7 +786,20 @@
     "\n",
     "\"\"\"\n",
     "1. Two stable equilibria (near 235 K and 305K) and one unstable equilibrium (near 245 K). Yes, they do.\n",
-    "\"\"\";"
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_1_3\")"
    ]
   },
   {
@@ -814,7 +902,20 @@
     "\"\"\"\n",
     "1. One, cold.\n",
     "2. One, warm.\n",
-    "\"\"\";"
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_2_1\")"
    ]
   },
   {
@@ -930,7 +1031,20 @@
     "1. The transition occurs around 240K. This is the lower temperature limit at which the ice-albedo feedback would kick in if the Earth was warmed from below 240K.\n",
     "2. Initially, we have a cold equilibrium solution like the blue and orange lines of the figure in Section 2.1, so the model converges to the cold equilibrium temperature. However, as the insolation increases we reach a point where only a warm equilibrium state exists, like the green line. When this happens, the Earth cannot equilibrate in a cold state anymore so Earth's temperature continues rising until it reaches the warm equilibrium state.\n",
     "3. All the systems on this plot start at 220K, where Earth is in a completely frozen state with an albedo of 0.7. Initially, as the planet warms, the albedo stays at 0.7, however, when the insolation becomes high enough that the planet warms to 240K (i.e. there is no cold equilibrium state) the ice-albedo feedback causes the albedo to begin decreasing, representing the effect of ice & snow melt. This drop in albedo accelerates the warming of the planet over time, as seen in the plot, until Earth reaches its warm equilibrium temperature.\n",
-    "\"\"\";"
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_2_2\")"
    ]
   },
   {
diff --git a/tutorials/W1D5_IntroductiontoClimateModeling/instructor/W1D5_Tutorial5.ipynb b/tutorials/W1D5_IntroductiontoClimateModeling/instructor/W1D5_Tutorial5.ipynb
index 5b568f6a8..6a8cb28f7 100644
--- a/tutorials/W1D5_IntroductiontoClimateModeling/instructor/W1D5_Tutorial5.ipynb
+++ b/tutorials/W1D5_IntroductiontoClimateModeling/instructor/W1D5_Tutorial5.ipynb
@@ -126,6 +126,35 @@
     "import tempfile"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D5_T5\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -252,6 +281,19 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Vertical_Structure_of_the_Atmosphere_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -273,14 +315,21 @@
     "\n",
     "link_id = \"dxthu\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Vertical_Structure_of_the_Atmosphere_Slides\")"
    ]
   },
   {
@@ -657,6 +706,19 @@
     "\"\"\""
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_1\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -748,6 +810,19 @@
     "_ = ax.legend()"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Coding_Exercises_1\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -1049,6 +1124,19 @@
     "\"\"\""
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_3\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -1139,6 +1227,19 @@
     "    add_profile(skew, model)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Coding_Exercises_3\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
diff --git a/tutorials/W1D5_IntroductiontoClimateModeling/instructor/W1D5_Tutorial6.ipynb b/tutorials/W1D5_IntroductiontoClimateModeling/instructor/W1D5_Tutorial6.ipynb
index ece709023..ac95ad005 100644
--- a/tutorials/W1D5_IntroductiontoClimateModeling/instructor/W1D5_Tutorial6.ipynb
+++ b/tutorials/W1D5_IntroductiontoClimateModeling/instructor/W1D5_Tutorial6.ipynb
@@ -128,6 +128,35 @@
     "from matplotlib import animation"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D5_T6\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -382,6 +411,19 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Radiative_Convective_Equilibrium_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -403,14 +445,21 @@
     "\n",
     "link_id = \"msarf\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Radiative_Convective_Equilibrium_Slides\")"
    ]
   },
   {
@@ -657,7 +706,20 @@
     "\"\"\"\n",
     "1. In nature, convection changes the temperature of the atmospheric column faster than radiative processes because convection involves the quick movement of air (and heat) from one place to another. Our model takes this into account by having convective processes act instantaneously on instabilities due to unstable temperature profiles.\n",
     "2. Next steps could include expanding in space (x,y,z) and including other processes (such as dynamics) and additional components of the climate system (ocean, etc.). We'll talk about this more in Tutorial 7 where you will work with the Taiwan Earth System Model (TaiESM1).\n",
-    "\"\"\";"
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_2\")"
    ]
   },
   {
@@ -666,7 +728,7 @@
     "execution": {}
    },
    "source": [
-    "## Coding Exercises "
+    "## Coding Exercises 2"
    ]
   },
   {
@@ -744,6 +806,19 @@
     "animation.FuncAnimation(fig, animate, 50, fargs=(rcm, lines))"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Coding_Exercises_2\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
diff --git a/tutorials/W1D5_IntroductiontoClimateModeling/instructor/W1D5_Tutorial7.ipynb b/tutorials/W1D5_IntroductiontoClimateModeling/instructor/W1D5_Tutorial7.ipynb
index 8ad43d92b..fd90db8a2 100644
--- a/tutorials/W1D5_IntroductiontoClimateModeling/instructor/W1D5_Tutorial7.ipynb
+++ b/tutorials/W1D5_IntroductiontoClimateModeling/instructor/W1D5_Tutorial7.ipynb
@@ -112,6 +112,35 @@
     "import cartopy.crs as ccrs"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D5_T7\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -190,6 +219,19 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Recap_Earth_System_Models_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -211,14 +253,21 @@
     "\n",
     "link_id = \"x3kwy\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Recap_Earth_System_Models_Slides\")"
    ]
   },
   {
@@ -335,7 +384,9 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "source": [
     "Now we will create a subset according to the provided facets using the `.search()` method, and finally open the cloud-stored [zarr stores](https://pangeo-data.github.io/pangeo-cmip6-cloud/overview.html) into Xarray datasets. \n",
     "\n",
@@ -576,7 +627,7 @@
     "execution": {}
    },
    "source": [
-    "## Coding Exercise 2\n",
+    "## Coding Exercises 2\n",
     "\n",
     "Now that we can plot maps of CMIP6 data, let's look at some projected future changes using this data!\n",
     "\n",
@@ -745,6 +796,19 @@
     "ax_diff_jan.set_title(\"2100 vs. 2024 Difference (January)\")"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Coding_Exercises_2\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -776,7 +840,20 @@
     "1. Based on the top maps, it looks like the Equator and low latitudes warm significantly, and the higher latitudes also warm. The northern hemisphere warms more than the southern hemisphere. These changes agree qualitatively with the \"change map\" (bottom left), although the change map makes it clear that the Arctic surface waters are warming faster than the rest of the planet and that the warming is not spatially uniform anywhere (in fact parts of the North Atlantic cool slightly!). The warming in the low latitudes and Southern hemisphere is still significant, and shows interesting spatial patterns.\n",
     "2. There are various things you might notice. For example, the January maps show more warming in the Southern hemisphere than the July maps, consistent with the Southern hemisphere summer creating a warmer baseline and more potential for extreme heat. We also see warming in the Equatorial Pacific region for January, which was not present for July, which could be due to different ENSO phases across the two months and the two years. A final example is that the North Atlantic shows even stronger cooling in January than in July, this is a common signal in many climate models. This cooling can result from melting ice sheets and glaciers creating colder, fresher surface water, which increases stratification. This can reduce the amount of deep convection in the North Atlantic region (by trapping fresh cold water at the surface), weakening the thermohaline circulation.\n",
     "3. The metadata of the CMIP6 dataset we are using in the first two plots contains a long-name for the variable and its units, which are automatically used for the axis labels. When we perform a mathematical operation (subtraction) on the dataset to create a new DataArray, the long-name metadata is not transferred to the new array to avoid confusion in case the operation creates a new variable (that could also have different units). This leads to the plot using the variable name (tos) for the x-axis instead of the long name.\n",
-    "\"\"\";"
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_2\")"
    ]
   },
   {
@@ -860,7 +937,20 @@
     "\"\"\"\n",
     "1. For a regular latitude-longitude grid the plot should consist of straight lines from top to bottom, and straight lines from left to right, that are evenly spaced in each of those directions. The grid of TaiESM1 looks like a regular latitude-longitude grid in the Southern Hemisphere, but is quite different in the Northern Hemisphere, with the grid cells getting small (converging) at a \"grid North pole\" which is actually placed at ~75 degrees North and 40 degrees West. a large part of this \"grid North pole\" doesn't contain any grid points (the white hole).\n",
     "2. On a regular latitude-longitude grid, the grid cells rapidly get very small as you approach the pole which causes numerical issues for the ocean model. For example, the time step has to be reduced to physically capture the movement between the smallest cells, leading to many more computations required to evolve the model. This is not a problem for ocean models at the South Pole because the pole is on land! In the Northern hemisphere, it is common to move the \"grid North pole\" of ocean models to occur in a land region (e.g., Asian and/or North American continents), and sometimes there are poles in both these land masses!\n",
-    "\"\"\";"
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_3_1\")"
    ]
   },
   {
@@ -1070,7 +1160,20 @@
     "\n",
     "\"\"\"\n",
     "1. They look similar, which is what we expect from the regridding operation. It should not significantly change the underlying spatial information (i.e., the data), it should just adjust the locations at which that information is provided.\n",
-    "\"\"\";"
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_3_3\")"
    ]
   },
   {
diff --git a/tutorials/W1D5_IntroductiontoClimateModeling/instructor/W1D5_Tutorial8.ipynb b/tutorials/W1D5_IntroductiontoClimateModeling/instructor/W1D5_Tutorial8.ipynb
index 68fac6a83..554c27c5e 100644
--- a/tutorials/W1D5_IntroductiontoClimateModeling/instructor/W1D5_Tutorial8.ipynb
+++ b/tutorials/W1D5_IntroductiontoClimateModeling/instructor/W1D5_Tutorial8.ipynb
@@ -114,6 +114,35 @@
     "from xmip.postprocessing import _parse_metric"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D5_T8\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -192,6 +221,19 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Future_Climate_Scenarios_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -213,14 +255,21 @@
     "\n",
     "link_id = \"yg9du\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Future_Climate_Scenarios_Slides\")"
    ]
   },
   {
@@ -299,6 +348,17 @@
     "dt = cat.to_datatree(**kwargs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "dt"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -359,7 +419,7 @@
     "dt_with_area = DataTree()\n",
     "\n",
     "# add the sub-catalog to the DataTree object via map_over_subtree()\n",
-    "for model, subtree in dt_area.items():\n",
+    "for model, subtree in dt.items():\n",
     "    metric = dt_area[model][\"historical\"].ds[\"areacello\"]\n",
     "    dt_with_area[model] = subtree.map_over_subtree(_parse_metric, metric)\n",
     "\n",
@@ -411,6 +471,19 @@
     "    dt_with_area[model] = subtree.map_over_subtree(_parse_metric, metric)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Coding_Exercises_1_1\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -521,7 +594,7 @@
     "    \"\"\"Global average, weighted by the cell area\"\"\"\n",
     "    return ds.weighted(ds.areacello.fillna(0)).mean([\"x\", \"y\"], keep_attrs=True)\n",
     "\n",
-    "# average every dataset in the tree globally via map_over_subtree() function introduced in Tutorial\n",
+    "# average every dataset in the tree globally via map_over_subtree() function introduced in Tutorial 7\n",
     "dt_gm = dt_with_area.map_over_subtree(global_mean)\n",
     "\n",
     "# create plot\n",
@@ -537,6 +610,19 @@
     "ax.legend()"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Coding_Exercises_2_1\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -568,7 +654,20 @@
     "\n",
     "\"\"\"\n",
     "1. The plots show warming of the ocean surface under SSP1-2.6, and the even greater warming seen under SSP5-8.5. This is expected from the forcing, the emissions under both scenarios lead to an increase in radiative forcing later in the century (which warms the planet), with the highest radiative forcing and warming under the SSP5-8.5 scenario.\n",
-    "\"\"\";"
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_2_1\")"
    ]
   },
   {
diff --git a/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial1_Solution_83fdc728.py b/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial1_Solution_517af88a.py
similarity index 99%
rename from tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial1_Solution_83fdc728.py
rename to tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial1_Solution_517af88a.py
index 3b7f94e1e..1a1457009 100644
--- a/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial1_Solution_83fdc728.py
+++ b/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial1_Solution_517af88a.py
@@ -5,4 +5,4 @@
 2. It implies that Earth's atmosphere is transparent to the sun's radiation. This is not exactly true, for example ozone interacts with ultraviolet light from the sun.
    However, Earth's atmosphere does absorb largely in the infrared.
 3. Clouds, aerosols, and scattering just to name a few.
-""";
\ No newline at end of file
+"""
\ No newline at end of file
diff --git a/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial1_Solution_3a0c44b9.py b/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial1_Solution_c67198fd.py
similarity index 99%
rename from tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial1_Solution_3a0c44b9.py
rename to tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial1_Solution_c67198fd.py
index 95bb63c3b..7f6c97947 100644
--- a/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial1_Solution_3a0c44b9.py
+++ b/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial1_Solution_c67198fd.py
@@ -3,4 +3,4 @@
 1. The calculated emission temperature of approximately 255 K or -18.2 C is significantly lower than the actual global mean surface temperature of approximately 288 K or 15 C.
 2. We would expect the corresponding outgoing longwave radiation to be higher than the observed 239 W/m², according to the Stefan-Boltzmann law.
 3. As the video explains, this simple model doesn't account for the atmospheric greenhouse effect due to greenhouse gases that absorb radiation at these wavelengths.
-""";
\ No newline at end of file
+"""
\ No newline at end of file
diff --git a/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial1_Solution_bd931bda.py b/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial1_Solution_d8ea9414.py
similarity index 81%
rename from tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial1_Solution_bd931bda.py
rename to tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial1_Solution_d8ea9414.py
index 1bce708c1..6ff538cf7 100644
--- a/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial1_Solution_bd931bda.py
+++ b/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial1_Solution_d8ea9414.py
@@ -1,4 +1,4 @@
 
 """
 1. Infrared.
-""";
\ No newline at end of file
+"""
\ No newline at end of file
diff --git a/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial2_Solution_f766d310.py b/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial2_Solution_79b144ab.py
similarity index 98%
rename from tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial2_Solution_f766d310.py
rename to tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial2_Solution_79b144ab.py
index 07367d64f..25384d4bf 100644
--- a/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial2_Solution_f766d310.py
+++ b/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial2_Solution_79b144ab.py
@@ -2,4 +2,4 @@
 """
 1. A decrease. A lower transmissivity means the atmosphere is less transparent, and therefore less radiation escapes to space.
 2. It is much higher because the greenhouse effect is stronger and trapping more heat.
-""";
\ No newline at end of file
+"""
\ No newline at end of file
diff --git a/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial2_Solution_d879cd19.py b/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial2_Solution_826838b2.py
similarity index 98%
rename from tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial2_Solution_d879cd19.py
rename to tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial2_Solution_826838b2.py
index 9cd9312c2..8eb4fff88 100644
--- a/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial2_Solution_d879cd19.py
+++ b/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial2_Solution_826838b2.py
@@ -2,4 +2,4 @@
 """
 1. It is slightly more. This means that Earth is absorbing more energy than it is losing. This is just to get you thinking about energy balance that will be discussed in the remainder of the tutorial.
 2. It does not take these into account. For example, ozone is a notable greenhouse gas that absorbs in the UV range.
-""";
\ No newline at end of file
+"""
\ No newline at end of file
diff --git a/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial2_Solution_94090198.py b/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial2_Solution_daefe4d6.py
similarity index 99%
rename from tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial2_Solution_94090198.py
rename to tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial2_Solution_daefe4d6.py
index fa11471c7..fbe0f2e2f 100644
--- a/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial2_Solution_94090198.py
+++ b/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial2_Solution_daefe4d6.py
@@ -2,4 +2,4 @@
 """
 1. If the insolation does not vary, a low albedo implies that Earth is less reflective (e.g less cloud, snow or ice cover) and vice versa for high albedo.
 2. Both. The reflected radiation is a function of land surface changes (e.g. glaciations and vegetation changes) and clouds (water vapor changes).  The radiation from the sun has also varied over time, which you will go into more detail in tutorial 4.
-""";
\ No newline at end of file
+"""
\ No newline at end of file
diff --git a/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial4_Solution_b91846bf.py b/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial4_Solution_05d045f5.py
similarity index 97%
rename from tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial4_Solution_b91846bf.py
rename to tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial4_Solution_05d045f5.py
index 5f49946cf..da9dd3a02 100644
--- a/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial4_Solution_b91846bf.py
+++ b/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial4_Solution_05d045f5.py
@@ -3,4 +3,4 @@
 1. Two. Near 235K and 305K.
 2. They are the  first and third temperatures at which the ASR and OLR curves intersect, or energy balance is achieved.
 3. Near 245K.
-""";
\ No newline at end of file
+"""
\ No newline at end of file
diff --git a/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial4_Solution_b9dadf47.py b/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial4_Solution_0aa720cf.py
similarity index 96%
rename from tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial4_Solution_b9dadf47.py
rename to tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial4_Solution_0aa720cf.py
index ded33bb2f..e0726e48b 100644
--- a/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial4_Solution_b9dadf47.py
+++ b/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial4_Solution_0aa720cf.py
@@ -1,4 +1,4 @@
 
 """
 1. Two stable equilibria (near 235 K and 305K) and one unstable equilibrium (near 245 K). Yes, they do.
-""";
\ No newline at end of file
+"""
\ No newline at end of file
diff --git a/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial4_Solution_449c4dae.py b/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial4_Solution_197ae6c0.py
similarity index 98%
rename from tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial4_Solution_449c4dae.py
rename to tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial4_Solution_197ae6c0.py
index 4bf87a9ca..8143d1515 100644
--- a/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial4_Solution_449c4dae.py
+++ b/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial4_Solution_197ae6c0.py
@@ -2,4 +2,4 @@
 """
 1. Three times.
 2. When the graphs intersect, it means that ASR = OLR, and thus ASR-OLR = 0. These three intersections are the three temperatures for which energy balance is satisfied in our model.
-""";
\ No newline at end of file
+"""
\ No newline at end of file
diff --git a/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial4_Solution_66fe91b4.py b/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial4_Solution_523f25ea.py
similarity index 89%
rename from tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial4_Solution_66fe91b4.py
rename to tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial4_Solution_523f25ea.py
index 26e6b2e92..1db0262cd 100644
--- a/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial4_Solution_66fe91b4.py
+++ b/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial4_Solution_523f25ea.py
@@ -2,4 +2,4 @@
 """
 1. One, cold.
 2. One, warm.
-""";
\ No newline at end of file
+"""
\ No newline at end of file
diff --git a/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial4_Solution_81a4e015.py b/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial4_Solution_f13e9cfb.py
similarity index 99%
rename from tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial4_Solution_81a4e015.py
rename to tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial4_Solution_f13e9cfb.py
index 2970644ef..cb5b687fb 100644
--- a/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial4_Solution_81a4e015.py
+++ b/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial4_Solution_f13e9cfb.py
@@ -3,4 +3,4 @@
 1. The transition occurs around 240K. This is the lower temperature limit at which the ice-albedo feedback would kick in if the Earth was warmed from below 240K.
 2. Initially, we have a cold equilibrium solution like the blue and orange lines of the figure in Section 2.1, so the model converges to the cold equilibrium temperature. However, as the insolation increases we reach a point where only a warm equilibrium state exists, like the green line. When this happens, the Earth cannot equilibrate in a cold state anymore so Earth's temperature continues rising until it reaches the warm equilibrium state.
 3. All the systems on this plot start at 220K, where Earth is in a completely frozen state with an albedo of 0.7. Initially, as the planet warms, the albedo stays at 0.7, however, when the insolation becomes high enough that the planet warms to 240K (i.e. there is no cold equilibrium state) the ice-albedo feedback causes the albedo to begin decreasing, representing the effect of ice & snow melt. This drop in albedo accelerates the warming of the planet over time, as seen in the plot, until Earth reaches its warm equilibrium temperature.
-""";
\ No newline at end of file
+"""
\ No newline at end of file
diff --git a/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial6_Solution_b80d3364.py b/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial6_Solution_28fcad82.py
similarity index 99%
rename from tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial6_Solution_b80d3364.py
rename to tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial6_Solution_28fcad82.py
index e44845eb6..7ed0ac91e 100644
--- a/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial6_Solution_b80d3364.py
+++ b/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial6_Solution_28fcad82.py
@@ -2,4 +2,4 @@
 """
 1. In nature, convection changes the temperature of the atmospheric column faster than radiative processes because convection involves the quick movement of air (and heat) from one place to another. Our model takes this into account by having convective processes act instantaneously on instabilities due to unstable temperature profiles.
 2. Next steps could include expanding in space (x,y,z) and including other processes (such as dynamics) and additional components of the climate system (ocean, etc.). We'll talk about this more in Tutorial 7 where you will work with the Taiwan Earth System Model (TaiESM1).
-""";
\ No newline at end of file
+"""
\ No newline at end of file
diff --git a/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial7_Solution_f9a48a4e.py b/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial7_Solution_1a3fae1b.py
similarity index 98%
rename from tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial7_Solution_f9a48a4e.py
rename to tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial7_Solution_1a3fae1b.py
index b0f2b2562..5b1377bbe 100644
--- a/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial7_Solution_f9a48a4e.py
+++ b/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial7_Solution_1a3fae1b.py
@@ -1,4 +1,4 @@
 
 """
 1. They look similar, which is what we expect from the regridding operation. It should not significantly change the underlying spatial information (i.e., the data), it should just adjust the locations at which that information is provided.
-""";
\ No newline at end of file
+"""
\ No newline at end of file
diff --git a/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial7_Solution_1b6c6159.py b/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial7_Solution_a29ea5f6.py
similarity index 99%
rename from tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial7_Solution_1b6c6159.py
rename to tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial7_Solution_a29ea5f6.py
index b670daece..b90231548 100644
--- a/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial7_Solution_1b6c6159.py
+++ b/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial7_Solution_a29ea5f6.py
@@ -3,4 +3,4 @@
 1. Based on the top maps, it looks like the Equator and low latitudes warm significantly, and the higher latitudes also warm. The northern hemisphere warms more than the southern hemisphere. These changes agree qualitatively with the "change map" (bottom left), although the change map makes it clear that the Arctic surface waters are warming faster than the rest of the planet and that the warming is not spatially uniform anywhere (in fact parts of the North Atlantic cool slightly!). The warming in the low latitudes and Southern hemisphere is still significant, and shows interesting spatial patterns.
 2. There are various things you might notice. For example, the January maps show more warming in the Southern hemisphere than the July maps, consistent with the Southern hemisphere summer creating a warmer baseline and more potential for extreme heat. We also see warming in the Equatorial Pacific region for January, which was not present for July, which could be due to different ENSO phases across the two months and the two years. A final example is that the North Atlantic shows even stronger cooling in January than in July, this is a common signal in many climate models. This cooling can result from melting ice sheets and glaciers creating colder, fresher surface water, which increases stratification. This can reduce the amount of deep convection in the North Atlantic region (by trapping fresh cold water at the surface), weakening the thermohaline circulation.
 3. The metadata of the CMIP6 dataset we are using in the first two plots contains a long-name for the variable and its units, which are automatically used for the axis labels. When we perform a mathematical operation (subtraction) on the dataset to create a new DataArray, the long-name metadata is not transferred to the new array to avoid confusion in case the operation creates a new variable (that could also have different units). This leads to the plot using the variable name (tos) for the x-axis instead of the long name.
-""";
\ No newline at end of file
+"""
\ No newline at end of file
diff --git a/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial7_Solution_0c8cd563.py b/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial7_Solution_aabbdc88.py
similarity index 99%
rename from tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial7_Solution_0c8cd563.py
rename to tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial7_Solution_aabbdc88.py
index 78296ff20..42d0d4bb7 100644
--- a/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial7_Solution_0c8cd563.py
+++ b/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial7_Solution_aabbdc88.py
@@ -2,4 +2,4 @@
 """
 1. For a regular latitude-longitude grid the plot should consist of straight lines from top to bottom, and straight lines from left to right, that are evenly spaced in each of those directions. The grid of TaiESM1 looks like a regular latitude-longitude grid in the Southern Hemisphere, but is quite different in the Northern Hemisphere, with the grid cells getting small (converging) at a "grid North pole" which is actually placed at ~75 degrees North and 40 degrees West. a large part of this "grid North pole" doesn't contain any grid points (the white hole).
 2. On a regular latitude-longitude grid, the grid cells rapidly get very small as you approach the pole which causes numerical issues for the ocean model. For example, the time step has to be reduced to physically capture the movement between the smallest cells, leading to many more computations required to evolve the model. This is not a problem for ocean models at the South Pole because the pole is on land! In the Northern hemisphere, it is common to move the "grid North pole" of ocean models to occur in a land region (e.g., Asian and/or North American continents), and sometimes there are poles in both these land masses!
-""";
\ No newline at end of file
+"""
\ No newline at end of file
diff --git a/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial8_Solution_a3bbf318.py b/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial8_Solution_b0a7a57f.py
similarity index 98%
rename from tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial8_Solution_a3bbf318.py
rename to tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial8_Solution_b0a7a57f.py
index 617b4d5b0..1747b4cbd 100644
--- a/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial8_Solution_a3bbf318.py
+++ b/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial8_Solution_b0a7a57f.py
@@ -1,4 +1,4 @@
 
 """
 1. The plots show warming of the ocean surface under SSP1-2.6, and the even greater warming seen under SSP5-8.5. This is expected from the forcing, the emissions under both scenarios lead to an increase in radiative forcing later in the century (which warms the planet), with the highest radiative forcing and warming under the SSP5-8.5 scenario.
-""";
\ No newline at end of file
+"""
\ No newline at end of file
diff --git a/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial8_Solution_b22bf4a1.py b/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial8_Solution_d9dec401.py
similarity index 94%
rename from tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial8_Solution_b22bf4a1.py
rename to tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial8_Solution_d9dec401.py
index 081897de1..5e5a9f7db 100644
--- a/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial8_Solution_b22bf4a1.py
+++ b/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial8_Solution_d9dec401.py
@@ -3,7 +3,7 @@ def global_mean(ds: xr.Dataset) -> xr.Dataset:
     """Global average, weighted by the cell area"""
     return ds.weighted(ds.areacello.fillna(0)).mean(["x", "y"], keep_attrs=True)
 
-# average every dataset in the tree globally via map_over_subtree() function introduced in Tutorial
+# average every dataset in the tree globally via map_over_subtree() function introduced in Tutorial 7
 dt_gm = dt_with_area.map_over_subtree(global_mean)
 
 # create plot
diff --git a/tutorials/W1D5_IntroductiontoClimateModeling/static/W1D5_Tutorial8_Solution_b22bf4a1_1.png b/tutorials/W1D5_IntroductiontoClimateModeling/static/W1D5_Tutorial8_Solution_d9dec401_1.png
similarity index 100%
rename from tutorials/W1D5_IntroductiontoClimateModeling/static/W1D5_Tutorial8_Solution_b22bf4a1_1.png
rename to tutorials/W1D5_IntroductiontoClimateModeling/static/W1D5_Tutorial8_Solution_d9dec401_1.png
diff --git a/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Intro.ipynb b/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Intro.ipynb
index a2f7641aa..2b6acbf66 100644
--- a/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Intro.ipynb
+++ b/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Intro.ipynb
@@ -56,6 +56,36 @@
     "* Access CMIP6 Earth system model data from cloud catalogs, and manipulate it by regridding and calculating global average properties."
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "2c799e08-2a4d-407e-bbc6-ce745e770fec",
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D5_Intro\""
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "491d4b6d",
@@ -124,6 +154,20 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "c7420af4-ba59-43b7-a946-8eeb4e5bff71",
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Climate_Modeling_Video\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "f46af996",
@@ -150,14 +194,22 @@
     "\n",
     "link_id = \"y2bdn\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "8341016f-e8ab-4a65-9ff8-c619041f3da3",
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Climate_Modeling_Slides\")"
    ]
   }
  ],
diff --git a/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial1.ipynb b/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial1.ipynb
index 0cd6c5291..c34c55db0 100644
--- a/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial1.ipynb
+++ b/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial1.ipynb
@@ -71,6 +71,35 @@
     "import numpy as np"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D5_T1\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -205,6 +234,19 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_A_Simple_Greenhouse_Model_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -220,14 +262,21 @@
     "\n",
     "link_id = \"3c8nq\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_A_Simple_Greenhouse_Model_Slides\")"
    ]
   },
   {
@@ -386,10 +435,23 @@
     "execution": {}
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D5_ClimateModeling/solutions/W1D5_Tutorial1_Solution_bd931bda.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial1_Solution_d8ea9414.py)\n",
     "\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_1_1\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -480,10 +542,23 @@
     "execution": {}
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D5_ClimateModeling/solutions/W1D5_Tutorial1_Solution_3a0c44b9.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial1_Solution_c67198fd.py)\n",
     "\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_1_2\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -550,10 +625,23 @@
     }
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D5_ClimateModeling/solutions/W1D5_Tutorial1_Solution_a2d0f592.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial1_Solution_a2d0f592.py)\n",
     "\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Coding_Exercises_1_2\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -685,10 +773,23 @@
     "execution": {}
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D5_ClimateModeling/solutions/W1D5_Tutorial1_Solution_83fdc728.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial1_Solution_517af88a.py)\n",
     "\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_2_2\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -763,14 +864,27 @@
     }
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D5_ClimateModeling/solutions/W1D5_Tutorial1_Solution_a6ad63d3.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial1_Solution_a6ad63d3.py)\n",
     "\n",
     "*Example output:*\n",
     "\n",
-    "<img alt='Solution hint' align='left' width=775.0 height=575.0 src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_ClimateModeling/static/W1D5_Tutorial1_Solution_a6ad63d3_1.png>\n",
+    "<img alt='Solution hint' align='left' width=775.0 height=575.0 src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_IntroductiontoClimateModeling/static/W1D5_Tutorial1_Solution_a6ad63d3_1.png>\n",
     "\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Coding_Exercises_2_2\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -788,7 +902,9 @@
     "execution": {}
    },
    "source": [
-    "### Instructions\n",
+    "### Coding Exercises 3\n",
+    "\n",
+    "**Instructions**\n",
     "\n",
     "By defining a function for Planck's Law, plot the blackbody radiation curve for the sun, assuming an emission temperature of $5800 \\text{ K}$. Underlay an approximation of the visible range from the electromagnetic spectrum. This exercise should help you understand why we see in color as well as why the sun's radiation headed towards Earth is called incoming shortwave radiation."
    ]
@@ -869,14 +985,27 @@
     "execution": {}
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D5_ClimateModeling/solutions/W1D5_Tutorial1_Solution_46434603.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial1_Solution_46434603.py)\n",
     "\n",
     "*Example output:*\n",
     "\n",
-    "<img alt='Solution hint' align='left' width=775.0 height=574.0 src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_ClimateModeling/static/W1D5_Tutorial1_Solution_46434603_1.png>\n",
+    "<img alt='Solution hint' align='left' width=775.0 height=574.0 src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_IntroductiontoClimateModeling/static/W1D5_Tutorial1_Solution_46434603_1.png>\n",
     "\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Coding_Exercises_3\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
diff --git a/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial2.ipynb b/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial2.ipynb
index 1d82ce0d2..5412a27eb 100644
--- a/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial2.ipynb
+++ b/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial2.ipynb
@@ -77,6 +77,35 @@
     "import matplotlib.pyplot as plt  # used for plotting"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D5_T2\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -153,6 +182,19 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Energy_Balance_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -174,14 +216,21 @@
     "\n",
     "link_id = \"ce6mx\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Energy_Balance_Slides\")"
    ]
   },
   {
@@ -301,10 +350,23 @@
     "execution": {}
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D5_ClimateModeling/solutions/W1D5_Tutorial2_Solution_94090198.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial2_Solution_daefe4d6.py)\n",
     "\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_1_1\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -363,10 +425,23 @@
     "execution": {}
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D5_ClimateModeling/solutions/W1D5_Tutorial2_Solution_d879cd19.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial2_Solution_826838b2.py)\n",
     "\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_1_2\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -528,10 +603,23 @@
     "execution": {}
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D5_ClimateModeling/solutions/W1D5_Tutorial2_Solution_f766d310.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial2_Solution_79b144ab.py)\n",
     "\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_3_1\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -606,14 +694,27 @@
     }
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D5_ClimateModeling/solutions/W1D5_Tutorial2_Solution_3fa7479c.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial2_Solution_3fa7479c.py)\n",
     "\n",
     "*Example output:*\n",
     "\n",
-    "<img alt='Solution hint' align='left' width=775.0 height=575.0 src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_ClimateModeling/static/W1D5_Tutorial2_Solution_3fa7479c_2.png>\n",
+    "<img alt='Solution hint' align='left' width=775.0 height=575.0 src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_IntroductiontoClimateModeling/static/W1D5_Tutorial2_Solution_3fa7479c_2.png>\n",
     "\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Coding_Exercises_3_1\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
diff --git a/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial3.ipynb b/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial3.ipynb
index f28ffad70..83ea66ded 100644
--- a/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial3.ipynb
+++ b/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial3.ipynb
@@ -77,6 +77,35 @@
     "import matplotlib.pyplot as plt  # used for plotting"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D5_T3\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -162,6 +191,19 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_A_Zero_Dimensional_Energy_Balance_Model_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -183,14 +225,21 @@
     "\n",
     "link_id = \"5mgns\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_A_Zero_Dimensional_Energy_Balance_Model_Slides\")"
    ]
   },
   {
@@ -360,10 +409,23 @@
     }
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D5_ClimateModeling/solutions/W1D5_Tutorial3_Solution_a1d313aa.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial3_Solution_a1d313aa.py)\n",
     "\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Coding_Exercises_1_1\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -389,10 +451,23 @@
     "execution": {}
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D5_ClimateModeling/solutions/W1D5_Tutorial3_Solution_a860c046.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial3_Solution_a860c046.py)\n",
     "\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_1_1\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -592,10 +667,23 @@
     "execution": {}
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D5_ClimateModeling/solutions/W1D5_Tutorial3_Solution_7d35dd95.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial3_Solution_7d35dd95.py)\n",
     "\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_1_2\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -642,7 +730,7 @@
     "numtsteps = np.array([10, 5, 1]) * 3\n",
     "\n",
     "# for converting the number of seconds in a year\n",
-    "sec_2_yr = ...\n",
+    "sec_2_yr = 3.154e7\n",
     "\n",
     "fig, ax = plt.subplots()\n",
     "# loop through each choice of time step\n",
@@ -685,14 +773,27 @@
     }
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D5_ClimateModeling/solutions/W1D5_Tutorial3_Solution_5e19a97e.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial3_Solution_5e19a97e.py)\n",
     "\n",
     "*Example output:*\n",
     "\n",
-    "<img alt='Solution hint' align='left' width=775.0 height=574.0 src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_ClimateModeling/static/W1D5_Tutorial3_Solution_5e19a97e_1.png>\n",
+    "<img alt='Solution hint' align='left' width=775.0 height=574.0 src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_IntroductiontoClimateModeling/static/W1D5_Tutorial3_Solution_5e19a97e_1.png>\n",
     "\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Coding_Exercises_1_2\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -790,10 +891,23 @@
     "execution": {}
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D5_ClimateModeling/solutions/W1D5_Tutorial3_Solution_caa2deb1.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial3_Solution_caa2deb1.py)\n",
     "\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_2_1\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -892,10 +1006,23 @@
     "execution": {}
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D5_ClimateModeling/solutions/W1D5_Tutorial3_Solution_71e39306.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial3_Solution_71e39306.py)\n",
     "\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Bonus_Coding_Exercises_3_1\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -943,10 +1070,23 @@
     "execution": {}
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D5_ClimateModeling/solutions/W1D5_Tutorial3_Solution_35a3c870.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial3_Solution_35a3c870.py)\n",
     "\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Bonus_Coding_Exercises_3_2\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -992,10 +1132,23 @@
     "execution": {}
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D5_ClimateModeling/solutions/W1D5_Tutorial3_Solution_d7862a90.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial3_Solution_d7862a90.py)\n",
     "\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Bonus_Coding_Exercises_3_3\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -1028,14 +1181,27 @@
     "execution": {}
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D5_ClimateModeling/solutions/W1D5_Tutorial3_Solution_4ae01b99.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial3_Solution_4ae01b99.py)\n",
     "\n",
     "*Example output:*\n",
     "\n",
-    "<img alt='Solution hint' align='left' width=775.0 height=574.0 src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_ClimateModeling/static/W1D5_Tutorial3_Solution_4ae01b99_1.png>\n",
+    "<img alt='Solution hint' align='left' width=775.0 height=574.0 src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_IntroductiontoClimateModeling/static/W1D5_Tutorial3_Solution_4ae01b99_1.png>\n",
     "\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Bonus_Coding_Exercises_3_4\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -1065,10 +1231,23 @@
     "execution": {}
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D5_ClimateModeling/solutions/W1D5_Tutorial3_Solution_b87ad7af.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial3_Solution_b87ad7af.py)\n",
     "\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Bonus_Coding_Exercises_3_5\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -1096,10 +1275,23 @@
     "execution": {}
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D5_ClimateModeling/solutions/W1D5_Tutorial3_Solution_422bae10.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial3_Solution_422bae10.py)\n",
     "\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Bonus_Questions_3\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
diff --git a/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial4.ipynb b/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial4.ipynb
index c2b58e50d..985f85e9e 100644
--- a/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial4.ipynb
+++ b/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial4.ipynb
@@ -88,6 +88,35 @@
     "from scipy.optimize import brentq  # used for numerical root-finding to get the equilibria"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D5_T4\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -174,6 +203,19 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Climate_Feedbacks_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -195,14 +237,21 @@
     "\n",
     "link_id = \"btpwx\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Climate_Feedbacks_Slides\")"
    ]
   },
   {
@@ -345,10 +394,23 @@
     "execution": {}
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D5_ClimateModeling/solutions/W1D5_Tutorial4_Solution_449c4dae.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial4_Solution_197ae6c0.py)\n",
     "\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_1_1\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -481,10 +543,23 @@
     "execution": {}
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D5_ClimateModeling/solutions/W1D5_Tutorial4_Solution_b91846bf.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial4_Solution_05d045f5.py)\n",
     "\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_1_2\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -695,10 +770,23 @@
     "execution": {}
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D5_ClimateModeling/solutions/W1D5_Tutorial4_Solution_b9dadf47.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial4_Solution_0aa720cf.py)\n",
     "\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_1_3\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -793,10 +881,23 @@
     "execution": {}
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D5_ClimateModeling/solutions/W1D5_Tutorial4_Solution_66fe91b4.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial4_Solution_523f25ea.py)\n",
     "\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_2_1\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -903,10 +1004,23 @@
     "execution": {}
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D5_ClimateModeling/solutions/W1D5_Tutorial4_Solution_81a4e015.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial4_Solution_f13e9cfb.py)\n",
     "\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_2_2\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
diff --git a/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial5.ipynb b/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial5.ipynb
index 6d4df5495..82cdda8d0 100644
--- a/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial5.ipynb
+++ b/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial5.ipynb
@@ -126,6 +126,35 @@
     "import tempfile"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D5_T5\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -252,6 +281,19 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Vertical_Structure_of_the_Atmosphere_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -273,14 +315,21 @@
     "\n",
     "link_id = \"dxthu\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Vertical_Structure_of_the_Atmosphere_Slides\")"
    ]
   },
   {
@@ -649,10 +698,23 @@
     "execution": {}
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D5_ClimateModeling/solutions/W1D5_Tutorial5_Solution_012273c4.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial5_Solution_012273c4.py)\n",
     "\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_1\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -718,14 +780,27 @@
     }
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D5_ClimateModeling/solutions/W1D5_Tutorial5_Solution_0fd7e870.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial5_Solution_0fd7e870.py)\n",
     "\n",
     "*Example output:*\n",
     "\n",
-    "<img alt='Solution hint' align='left' width=774.0 height=575.0 src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_ClimateModeling/static/W1D5_Tutorial5_Solution_0fd7e870_0.png>\n",
+    "<img alt='Solution hint' align='left' width=774.0 height=575.0 src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_IntroductiontoClimateModeling/static/W1D5_Tutorial5_Solution_0fd7e870_0.png>\n",
     "\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Coding_Exercises_1\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -1018,10 +1093,23 @@
     "execution": {}
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D5_ClimateModeling/solutions/W1D5_Tutorial5_Solution_d21ca44b.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial5_Solution_d21ca44b.py)\n",
     "\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_3\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -1086,14 +1174,27 @@
     }
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D5_ClimateModeling/solutions/W1D5_Tutorial5_Solution_5eb5cfa0.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial5_Solution_5eb5cfa0.py)\n",
     "\n",
     "*Example output:*\n",
     "\n",
-    "<img alt='Solution hint' align='left' width=765.0 height=875.0 src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_ClimateModeling/static/W1D5_Tutorial5_Solution_5eb5cfa0_0.png>\n",
+    "<img alt='Solution hint' align='left' width=765.0 height=875.0 src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_IntroductiontoClimateModeling/static/W1D5_Tutorial5_Solution_5eb5cfa0_0.png>\n",
     "\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Coding_Exercises_3\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
diff --git a/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial6.ipynb b/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial6.ipynb
index d8c180865..e5d85aa9e 100644
--- a/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial6.ipynb
+++ b/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial6.ipynb
@@ -128,6 +128,35 @@
     "from matplotlib import animation"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D5_T6\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -382,6 +411,19 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Radiative_Convective_Equilibrium_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -403,14 +445,21 @@
     "\n",
     "link_id = \"msarf\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Radiative_Convective_Equilibrium_Slides\")"
    ]
   },
   {
@@ -651,17 +700,30 @@
     "execution": {}
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D5_ClimateModeling/solutions/W1D5_Tutorial6_Solution_b80d3364.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial6_Solution_28fcad82.py)\n",
     "\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_2\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
     "execution": {}
    },
    "source": [
-    "## Coding Exercises "
+    "## Coding Exercises 2"
    ]
   },
   {
@@ -721,10 +783,23 @@
     }
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D5_ClimateModeling/solutions/W1D5_Tutorial6_Solution_46d5cbad.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial6_Solution_46d5cbad.py)\n",
     "\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Coding_Exercises_2\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
diff --git a/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial7.ipynb b/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial7.ipynb
index c4d095c3d..c2730c1c6 100644
--- a/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial7.ipynb
+++ b/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial7.ipynb
@@ -112,6 +112,35 @@
     "import cartopy.crs as ccrs"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D5_T7\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -190,6 +219,19 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Recap_Earth_System_Models_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -211,14 +253,21 @@
     "\n",
     "link_id = \"x3kwy\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Recap_Earth_System_Models_Slides\")"
    ]
   },
   {
@@ -335,7 +384,9 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "source": [
     "Now we will create a subset according to the provided facets using the `.search()` method, and finally open the cloud-stored [zarr stores](https://pangeo-data.github.io/pangeo-cmip6-cloud/overview.html) into Xarray datasets. \n",
     "\n",
@@ -576,7 +627,7 @@
     "execution": {}
    },
    "source": [
-    "## Coding Exercise 2\n",
+    "## Coding Exercises 2\n",
     "\n",
     "Now that we can plot maps of CMIP6 data, let's look at some projected future changes using this data!\n",
     "\n",
@@ -670,14 +721,27 @@
     "tags": []
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D5_ClimateModeling/solutions/W1D5_Tutorial7_Solution_a73dfa84.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial7_Solution_a73dfa84.py)\n",
     "\n",
     "*Example output:*\n",
     "\n",
-    "<img alt='Solution hint' align='left' width=1173.0 height=580.0 src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_ClimateModeling/static/W1D5_Tutorial7_Solution_a73dfa84_1.png>\n",
+    "<img alt='Solution hint' align='left' width=1173.0 height=580.0 src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_IntroductiontoClimateModeling/static/W1D5_Tutorial7_Solution_a73dfa84_1.png>\n",
     "\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Coding_Exercises_2\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -702,10 +766,23 @@
     "tags": []
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D5_ClimateModeling/solutions/W1D5_Tutorial7_Solution_1b6c6159.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial7_Solution_a29ea5f6.py)\n",
     "\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_2\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -781,10 +858,23 @@
     "tags": []
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D5_ClimateModeling/solutions/W1D5_Tutorial7_Solution_0c8cd563.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial7_Solution_aabbdc88.py)\n",
     "\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_3_1\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -987,10 +1077,23 @@
     "tags": []
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D5_ClimateModeling/solutions/W1D5_Tutorial7_Solution_f9a48a4e.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial7_Solution_1a3fae1b.py)\n",
     "\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_3_3\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
diff --git a/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial8.ipynb b/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial8.ipynb
index 44712ed7e..ce885e9a6 100644
--- a/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial8.ipynb
+++ b/tutorials/W1D5_IntroductiontoClimateModeling/student/W1D5_Tutorial8.ipynb
@@ -114,6 +114,35 @@
     "from xmip.postprocessing import _parse_metric"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Install and import feedback gadget\n",
+    "\n",
+    "!pip3 install vibecheck datatops --quiet\n",
+    "\n",
+    "from vibecheck import DatatopsContentReviewContainer\n",
+    "def content_review(notebook_section: str):\n",
+    "    return DatatopsContentReviewContainer(\n",
+    "        \"\",  # No text prompt\n",
+    "        notebook_section,\n",
+    "        {\n",
+    "            \"url\": \"https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab\",\n",
+    "            \"name\": \"comptools_4clim\",\n",
+    "            \"user_key\": \"l5jpxuee\",\n",
+    "        },\n",
+    "    ).render()\n",
+    "\n",
+    "\n",
+    "feedback_prefix = \"W1D5_T8\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -192,6 +221,19 @@
     "display(tabs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Future_Climate_Scenarios_Video\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -213,14 +255,21 @@
     "\n",
     "link_id = \"yg9du\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Future_Climate_Scenarios_Slides\")"
    ]
   },
   {
@@ -299,6 +348,17 @@
     "dt = cat.to_datatree(**kwargs)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "dt"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -359,7 +419,7 @@
     "dt_with_area = DataTree()\n",
     "\n",
     "# add the sub-catalog to the DataTree object via map_over_subtree()\n",
-    "for model, subtree in dt_area.items():\n",
+    "for model, subtree in dt.items():\n",
     "    metric = dt_area[model][\"historical\"].ds[\"areacello\"]\n",
     "    dt_with_area[model] = subtree.map_over_subtree(_parse_metric, metric)"
    ]
@@ -382,10 +442,23 @@
     "tags": []
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D5_ClimateModeling/solutions/W1D5_Tutorial8_Solution_f150da13.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial8_Solution_f150da13.py)\n",
     "\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Coding_Exercises_1_1\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -487,14 +560,27 @@
     "tags": []
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D5_ClimateModeling/solutions/W1D5_Tutorial8_Solution_b22bf4a1.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial8_Solution_d9dec401.py)\n",
     "\n",
     "*Example output:*\n",
     "\n",
-    "<img alt='Solution hint' align='left' width=775.0 height=575.0 src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_ClimateModeling/static/W1D5_Tutorial8_Solution_b22bf4a1_1.png>\n",
+    "<img alt='Solution hint' align='left' width=775.0 height=575.0 src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W1D5_IntroductiontoClimateModeling/static/W1D5_Tutorial8_Solution_d9dec401_1.png>\n",
     "\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Coding_Exercises_2_1\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -521,10 +607,23 @@
     "execution": {}
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D5_ClimateModeling/solutions/W1D5_Tutorial8_Solution_a3bbf318.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W1D5_IntroductiontoClimateModeling/solutions/W1D5_Tutorial8_Solution_b0a7a57f.py)\n",
     "\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @title Submit your feedback\n",
+    "content_review(f\"{feedback_prefix}_Questions_2_1\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
diff --git a/tutorials/W2D1_AnEnsembleofFutures/W2D1_Intro.ipynb b/tutorials/W2D1_AnEnsembleofFutures/W2D1_Intro.ipynb
index 2825625e5..9bb811e7c 100644
--- a/tutorials/W2D1_AnEnsembleofFutures/W2D1_Intro.ipynb
+++ b/tutorials/W2D1_AnEnsembleofFutures/W2D1_Intro.ipynb
@@ -240,7 +240,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.18"
+   "version": "3.9.19"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/W2D1_AnEnsembleofFutures/W2D1_Tutorial1.ipynb b/tutorials/W2D1_AnEnsembleofFutures/W2D1_Tutorial1.ipynb
index f470377ba..c27edb86c 100644
--- a/tutorials/W2D1_AnEnsembleofFutures/W2D1_Tutorial1.ipynb
+++ b/tutorials/W2D1_AnEnsembleofFutures/W2D1_Tutorial1.ipynb
@@ -776,7 +776,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.18"
+   "version": "3.9.19"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/W2D1_AnEnsembleofFutures/W2D1_Tutorial2.ipynb b/tutorials/W2D1_AnEnsembleofFutures/W2D1_Tutorial2.ipynb
index 1198a6653..eec2f7adc 100644
--- a/tutorials/W2D1_AnEnsembleofFutures/W2D1_Tutorial2.ipynb
+++ b/tutorials/W2D1_AnEnsembleofFutures/W2D1_Tutorial2.ipynb
@@ -827,7 +827,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.18"
+   "version": "3.9.19"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/W2D1_AnEnsembleofFutures/W2D1_Tutorial3.ipynb b/tutorials/W2D1_AnEnsembleofFutures/W2D1_Tutorial3.ipynb
index f8b1e0947..5ad1f7a29 100644
--- a/tutorials/W2D1_AnEnsembleofFutures/W2D1_Tutorial3.ipynb
+++ b/tutorials/W2D1_AnEnsembleofFutures/W2D1_Tutorial3.ipynb
@@ -676,7 +676,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.18"
+   "version": "3.9.19"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/W2D1_AnEnsembleofFutures/W2D1_Tutorial4.ipynb b/tutorials/W2D1_AnEnsembleofFutures/W2D1_Tutorial4.ipynb
index 8099d3dba..864b09a54 100644
--- a/tutorials/W2D1_AnEnsembleofFutures/W2D1_Tutorial4.ipynb
+++ b/tutorials/W2D1_AnEnsembleofFutures/W2D1_Tutorial4.ipynb
@@ -709,7 +709,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.18"
+   "version": "3.9.19"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/W2D1_AnEnsembleofFutures/instructor/W2D1_Tutorial1.ipynb b/tutorials/W2D1_AnEnsembleofFutures/instructor/W2D1_Tutorial1.ipynb
index 68e5b3f70..5b35d65c5 100644
--- a/tutorials/W2D1_AnEnsembleofFutures/instructor/W2D1_Tutorial1.ipynb
+++ b/tutorials/W2D1_AnEnsembleofFutures/instructor/W2D1_Tutorial1.ipynb
@@ -409,14 +409,8 @@
     "\n",
     "link_id = \"dsm6a\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
    ]
   },
   {
diff --git a/tutorials/W2D1_AnEnsembleofFutures/instructor/W2D1_Tutorial2.ipynb b/tutorials/W2D1_AnEnsembleofFutures/instructor/W2D1_Tutorial2.ipynb
index e425ab4f7..b813544ba 100644
--- a/tutorials/W2D1_AnEnsembleofFutures/instructor/W2D1_Tutorial2.ipynb
+++ b/tutorials/W2D1_AnEnsembleofFutures/instructor/W2D1_Tutorial2.ipynb
@@ -580,7 +580,7 @@
     "\n",
     "\"\"\"\n",
     "1. Each of these models has slightly different physics, numerics, and discretization. During the Introduction to Climate Modeling day you showed that Earth's theoretical equilibrium temperature under fixed insolation changes as more details/complexity of the real Earth system are included. Similarly, the small differences between models result in each model having a slightly different equilibrium temperature for a given insolation, which also manifests in these long-term simulations.\n",
-    "\"\"\";"
+    "\"\"\""
    ]
   },
   {
@@ -753,7 +753,7 @@
     "\"\"\"\n",
     "1. The models agree much better across this time period, particularly in the reference period and during the rapid warming phase projected in the near future.\n",
     "2. There is variability at both ends of the scale, but the future (2080) period has more inter-model variability than the past (1850) period. This is likely because each of these models has to simulate a unique climate system, as we found in the last question, which leads to different responses to the rapid changes in effective radiative forcing that are projected in the near future.\n",
-    "\"\"\";"
+    "\"\"\""
    ]
   },
   {
diff --git a/tutorials/W2D1_AnEnsembleofFutures/instructor/W2D1_Tutorial3.ipynb b/tutorials/W2D1_AnEnsembleofFutures/instructor/W2D1_Tutorial3.ipynb
index 218cc4200..e890e8106 100644
--- a/tutorials/W2D1_AnEnsembleofFutures/instructor/W2D1_Tutorial3.ipynb
+++ b/tutorials/W2D1_AnEnsembleofFutures/instructor/W2D1_Tutorial3.ipynb
@@ -599,7 +599,7 @@
     "1. Under both of these scenarios (SSP1-2.6 and SSP5-8.5), the projected warming of the climate is greater than the multi-model uncertainty.\n",
     "2. The warming is greater for SSP5-8.5, but so is the multi-model uncertainty, so the relative size of physical changes and multi-model uncertainty is comparable across both scenarios.\n",
     "3. The likely range includes the middle 66% of model results at a given time. For 5 models this means the ranges encompass the middle 3 models (i.e., they exclude the highest and lowest valued model at each time).\n",
-    "\"\"\";"
+    "\"\"\""
    ]
   },
   {
diff --git a/tutorials/W2D1_AnEnsembleofFutures/instructor/W2D1_Tutorial4.ipynb b/tutorials/W2D1_AnEnsembleofFutures/instructor/W2D1_Tutorial4.ipynb
index 2ef252bf9..44f330cf4 100644
--- a/tutorials/W2D1_AnEnsembleofFutures/instructor/W2D1_Tutorial4.ipynb
+++ b/tutorials/W2D1_AnEnsembleofFutures/instructor/W2D1_Tutorial4.ipynb
@@ -629,7 +629,7 @@
     "\n",
     "\"\"\"\n",
     "1. I will let you decide what you take away from synthesizing these figures and data!\n",
-    "\"\"\";"
+    "\"\"\""
    ]
   },
   {
diff --git a/tutorials/W2D1_AnEnsembleofFutures/solutions/W2D1_Tutorial2_Solution_2f1aae82.py b/tutorials/W2D1_AnEnsembleofFutures/solutions/W2D1_Tutorial2_Solution_0970e7cc.py
similarity index 99%
rename from tutorials/W2D1_AnEnsembleofFutures/solutions/W2D1_Tutorial2_Solution_2f1aae82.py
rename to tutorials/W2D1_AnEnsembleofFutures/solutions/W2D1_Tutorial2_Solution_0970e7cc.py
index 6682395cf..311fb707d 100644
--- a/tutorials/W2D1_AnEnsembleofFutures/solutions/W2D1_Tutorial2_Solution_2f1aae82.py
+++ b/tutorials/W2D1_AnEnsembleofFutures/solutions/W2D1_Tutorial2_Solution_0970e7cc.py
@@ -2,4 +2,4 @@
 """
 1. The models agree much better across this time period, particularly in the reference period and during the rapid warming phase projected in the near future.
 2. There is variability at both ends of the scale, but the future (2080) period has more inter-model variability than the past (1850) period. This is likely because each of these models has to simulate a unique climate system, as we found in the last question, which leads to different responses to the rapid changes in effective radiative forcing that are projected in the near future.
-""";
\ No newline at end of file
+"""
\ No newline at end of file
diff --git a/tutorials/W2D1_AnEnsembleofFutures/solutions/W2D1_Tutorial2_Solution_4d683b54.py b/tutorials/W2D1_AnEnsembleofFutures/solutions/W2D1_Tutorial2_Solution_bfde86f5.py
similarity index 99%
rename from tutorials/W2D1_AnEnsembleofFutures/solutions/W2D1_Tutorial2_Solution_4d683b54.py
rename to tutorials/W2D1_AnEnsembleofFutures/solutions/W2D1_Tutorial2_Solution_bfde86f5.py
index 40bab08ab..06b999308 100644
--- a/tutorials/W2D1_AnEnsembleofFutures/solutions/W2D1_Tutorial2_Solution_4d683b54.py
+++ b/tutorials/W2D1_AnEnsembleofFutures/solutions/W2D1_Tutorial2_Solution_bfde86f5.py
@@ -1,4 +1,4 @@
 
 """
 1. Each of these models has slightly different physics, numerics, and discretization. During the Introduction to Climate Modeling day you showed that Earth's theoretical equilibrium temperature under fixed insolation changes as more details/complexity of the real Earth system are included. Similarly, the small differences between models result in each model having a slightly different equilibrium temperature for a given insolation, which also manifests in these long-term simulations.
-""";
\ No newline at end of file
+"""
\ No newline at end of file
diff --git a/tutorials/W2D1_AnEnsembleofFutures/solutions/W2D1_Tutorial3_Solution_bc0a1a18.py b/tutorials/W2D1_AnEnsembleofFutures/solutions/W2D1_Tutorial3_Solution_d9195b4a.py
similarity index 99%
rename from tutorials/W2D1_AnEnsembleofFutures/solutions/W2D1_Tutorial3_Solution_bc0a1a18.py
rename to tutorials/W2D1_AnEnsembleofFutures/solutions/W2D1_Tutorial3_Solution_d9195b4a.py
index 73365093c..9fceff50f 100644
--- a/tutorials/W2D1_AnEnsembleofFutures/solutions/W2D1_Tutorial3_Solution_bc0a1a18.py
+++ b/tutorials/W2D1_AnEnsembleofFutures/solutions/W2D1_Tutorial3_Solution_d9195b4a.py
@@ -3,4 +3,4 @@
 1. Under both of these scenarios (SSP1-2.6 and SSP5-8.5), the projected warming of the climate is greater than the multi-model uncertainty.
 2. The warming is greater for SSP5-8.5, but so is the multi-model uncertainty, so the relative size of physical changes and multi-model uncertainty is comparable across both scenarios.
 3. The likely range includes the middle 66% of model results at a given time. For 5 models this means the ranges encompass the middle 3 models (i.e., they exclude the highest and lowest valued model at each time).
-""";
\ No newline at end of file
+"""
\ No newline at end of file
diff --git a/tutorials/W2D1_AnEnsembleofFutures/solutions/W2D1_Tutorial4_Solution_7818edff.py b/tutorials/W2D1_AnEnsembleofFutures/solutions/W2D1_Tutorial4_Solution_713a7840.py
similarity index 95%
rename from tutorials/W2D1_AnEnsembleofFutures/solutions/W2D1_Tutorial4_Solution_7818edff.py
rename to tutorials/W2D1_AnEnsembleofFutures/solutions/W2D1_Tutorial4_Solution_713a7840.py
index e28ed3869..c25ccd16a 100644
--- a/tutorials/W2D1_AnEnsembleofFutures/solutions/W2D1_Tutorial4_Solution_7818edff.py
+++ b/tutorials/W2D1_AnEnsembleofFutures/solutions/W2D1_Tutorial4_Solution_713a7840.py
@@ -1,4 +1,4 @@
 
 """
 1. I will let you decide what you take away from synthesizing these figures and data!
-""";
\ No newline at end of file
+"""
\ No newline at end of file
diff --git a/tutorials/W2D1_AnEnsembleofFutures/static/W2D1_Tutorial1_Solution_e885fd98_1.png b/tutorials/W2D1_AnEnsembleofFutures/static/W2D1_Tutorial1_Solution_e885fd98_1.png
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diff --git a/tutorials/W2D1_AnEnsembleofFutures/student/W2D1_Tutorial1.ipynb b/tutorials/W2D1_AnEnsembleofFutures/student/W2D1_Tutorial1.ipynb
index 8591b4296..cd8e4775c 100644
--- a/tutorials/W2D1_AnEnsembleofFutures/student/W2D1_Tutorial1.ipynb
+++ b/tutorials/W2D1_AnEnsembleofFutures/student/W2D1_Tutorial1.ipynb
@@ -409,14 +409,8 @@
     "\n",
     "link_id = \"dsm6a\"\n",
     "\n",
-    "download_link = f\"https://osf.io/download/{link_id}/\"\n",
-    "render_link = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\"\n",
-    "# @markdown\n",
-    "out = widgets.Output()\n",
-    "with out:\n",
-    "    print(f\"If you want to download the slides: {download_link}\")\n",
-    "    display(IFrame(src=f\"{render_link}\", width=730, height=410))\n",
-    "display(out)"
+    "print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
+    "IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=854, height=480)"
    ]
   },
   {
diff --git a/tutorials/W2D1_AnEnsembleofFutures/student/W2D1_Tutorial2.ipynb b/tutorials/W2D1_AnEnsembleofFutures/student/W2D1_Tutorial2.ipynb
index 1b1cf0c5b..9f27e8035 100644
--- a/tutorials/W2D1_AnEnsembleofFutures/student/W2D1_Tutorial2.ipynb
+++ b/tutorials/W2D1_AnEnsembleofFutures/student/W2D1_Tutorial2.ipynb
@@ -556,7 +556,7 @@
     "tags": []
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W2D1_AnEnsembleofFutures/solutions/W2D1_Tutorial2_Solution_4d683b54.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W2D1_AnEnsembleofFutures/solutions/W2D1_Tutorial2_Solution_bfde86f5.py)\n",
     "\n"
    ]
   },
@@ -700,7 +700,7 @@
     "tags": []
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W2D1_AnEnsembleofFutures/solutions/W2D1_Tutorial2_Solution_2f1aae82.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W2D1_AnEnsembleofFutures/solutions/W2D1_Tutorial2_Solution_0970e7cc.py)\n",
     "\n"
    ]
   },
diff --git a/tutorials/W2D1_AnEnsembleofFutures/student/W2D1_Tutorial3.ipynb b/tutorials/W2D1_AnEnsembleofFutures/student/W2D1_Tutorial3.ipynb
index bedd21f9c..b908cbba3 100644
--- a/tutorials/W2D1_AnEnsembleofFutures/student/W2D1_Tutorial3.ipynb
+++ b/tutorials/W2D1_AnEnsembleofFutures/student/W2D1_Tutorial3.ipynb
@@ -560,7 +560,7 @@
     "execution": {}
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W2D1_AnEnsembleofFutures/solutions/W2D1_Tutorial3_Solution_bc0a1a18.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W2D1_AnEnsembleofFutures/solutions/W2D1_Tutorial3_Solution_d9195b4a.py)\n",
     "\n"
    ]
   },
diff --git a/tutorials/W2D1_AnEnsembleofFutures/student/W2D1_Tutorial4.ipynb b/tutorials/W2D1_AnEnsembleofFutures/student/W2D1_Tutorial4.ipynb
index 6a045f1d1..74ffaaaf8 100644
--- a/tutorials/W2D1_AnEnsembleofFutures/student/W2D1_Tutorial4.ipynb
+++ b/tutorials/W2D1_AnEnsembleofFutures/student/W2D1_Tutorial4.ipynb
@@ -576,7 +576,7 @@
     "execution": {}
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W2D1_AnEnsembleofFutures/solutions/W2D1_Tutorial4_Solution_7818edff.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W2D1_AnEnsembleofFutures/solutions/W2D1_Tutorial4_Solution_713a7840.py)\n",
     "\n"
    ]
   },
diff --git a/tutorials/W2D3_ExtremesandVariability/W2D3_Tutorial1.ipynb b/tutorials/W2D3_ExtremesandVariability/W2D3_Tutorial1.ipynb
index 928d228fa..7d7f1c54b 100644
--- a/tutorials/W2D3_ExtremesandVariability/W2D3_Tutorial1.ipynb
+++ b/tutorials/W2D3_ExtremesandVariability/W2D3_Tutorial1.ipynb
@@ -852,7 +852,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.18"
+   "version": "3.9.19"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/W2D3_ExtremesandVariability/W2D3_Tutorial2.ipynb b/tutorials/W2D3_ExtremesandVariability/W2D3_Tutorial2.ipynb
index ac3760adc..8d937a576 100644
--- a/tutorials/W2D3_ExtremesandVariability/W2D3_Tutorial2.ipynb
+++ b/tutorials/W2D3_ExtremesandVariability/W2D3_Tutorial2.ipynb
@@ -908,7 +908,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.18"
+   "version": "3.9.19"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/W2D3_ExtremesandVariability/W2D3_Tutorial3.ipynb b/tutorials/W2D3_ExtremesandVariability/W2D3_Tutorial3.ipynb
index 685817496..f0382ba25 100644
--- a/tutorials/W2D3_ExtremesandVariability/W2D3_Tutorial3.ipynb
+++ b/tutorials/W2D3_ExtremesandVariability/W2D3_Tutorial3.ipynb
@@ -1030,7 +1030,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.18"
+   "version": "3.9.19"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/W2D3_ExtremesandVariability/W2D3_Tutorial4.ipynb b/tutorials/W2D3_ExtremesandVariability/W2D3_Tutorial4.ipynb
index 32fb5c738..21bd2ea25 100644
--- a/tutorials/W2D3_ExtremesandVariability/W2D3_Tutorial4.ipynb
+++ b/tutorials/W2D3_ExtremesandVariability/W2D3_Tutorial4.ipynb
@@ -931,7 +931,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.18"
+   "version": "3.9.19"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/W2D3_ExtremesandVariability/W2D3_Tutorial6.ipynb b/tutorials/W2D3_ExtremesandVariability/W2D3_Tutorial6.ipynb
index 99e698758..cdfac4926 100644
--- a/tutorials/W2D3_ExtremesandVariability/W2D3_Tutorial6.ipynb
+++ b/tutorials/W2D3_ExtremesandVariability/W2D3_Tutorial6.ipynb
@@ -1507,7 +1507,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.18"
+   "version": "3.9.19"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/W2D3_ExtremesandVariability/W2D3_Tutorial7.ipynb b/tutorials/W2D3_ExtremesandVariability/W2D3_Tutorial7.ipynb
index 8f76dfccd..fc62a7ebb 100644
--- a/tutorials/W2D3_ExtremesandVariability/W2D3_Tutorial7.ipynb
+++ b/tutorials/W2D3_ExtremesandVariability/W2D3_Tutorial7.ipynb
@@ -1117,7 +1117,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.18"
+   "version": "3.9.19"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/W2D3_ExtremesandVariability/W2D3_Tutorial8.ipynb b/tutorials/W2D3_ExtremesandVariability/W2D3_Tutorial8.ipynb
index 693253913..37c8a4053 100644
--- a/tutorials/W2D3_ExtremesandVariability/W2D3_Tutorial8.ipynb
+++ b/tutorials/W2D3_ExtremesandVariability/W2D3_Tutorial8.ipynb
@@ -1895,7 +1895,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.18"
+   "version": "3.9.19"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/W2D3_ExtremesandVariability/instructor/W2D3_Tutorial1.ipynb b/tutorials/W2D3_ExtremesandVariability/instructor/W2D3_Tutorial1.ipynb
index 797f4dec2..d042cc944 100644
--- a/tutorials/W2D3_ExtremesandVariability/instructor/W2D3_Tutorial1.ipynb
+++ b/tutorials/W2D3_ExtremesandVariability/instructor/W2D3_Tutorial1.ipynb
@@ -788,7 +788,7 @@
     "# to_remove explanation\n",
     "\"\"\"\n",
     "1. As presented in the figure above, the data falls largely outside of the percentiles you calculated. That, paired with the skewness calculated earlier suggests a different distribution may fit the data better. For example, log-normal distributions tend to be better suited for describing skewed datasets such as this.\n",
-    "\"\"\";"
+    "\"\"\""
    ]
   },
   {
diff --git a/tutorials/W2D3_ExtremesandVariability/instructor/W2D3_Tutorial2.ipynb b/tutorials/W2D3_ExtremesandVariability/instructor/W2D3_Tutorial2.ipynb
index 3e4ffa272..32aea948f 100644
--- a/tutorials/W2D3_ExtremesandVariability/instructor/W2D3_Tutorial2.ipynb
+++ b/tutorials/W2D3_ExtremesandVariability/instructor/W2D3_Tutorial2.ipynb
@@ -712,7 +712,7 @@
     "\"\"\"\n",
     "1. 10, 40 and 70 mm/day.\n",
     "2. Our data only spans from 1920 to 2022. If we are truly interested in 100-year events we need to work with a longer dataset perhaps using paleo proxies or other instrumentation. The longer the dataset, the more frequently we would expect to observe the long return period events and increase our confidence in them. Other ideas would be estimating probability/cumulative density functions (next few tutorials) or to use resampling methods (coding exercise below).\n",
-    "\"\"\";"
+    "\"\"\""
    ]
   },
   {
diff --git a/tutorials/W2D3_ExtremesandVariability/instructor/W2D3_Tutorial3.ipynb b/tutorials/W2D3_ExtremesandVariability/instructor/W2D3_Tutorial3.ipynb
index 1030a397f..7399ce38a 100644
--- a/tutorials/W2D3_ExtremesandVariability/instructor/W2D3_Tutorial3.ipynb
+++ b/tutorials/W2D3_ExtremesandVariability/instructor/W2D3_Tutorial3.ipynb
@@ -964,7 +964,7 @@
     "Scale parameter: The scale parameter influences the spread or width of the distribution. A higher scale parameter will widen the distribution, implying greater variability in the data and thicker tails, while a lower scale parameter will narrow the distribution, implying less probability of extreme events.\n",
     "\n",
     "Shape parameter: This parameter is unique to the GEV distribution and impacts the tails of the distribution. It can make the tails of the distribution thinner or thicker, which in turn affects the skewness and kurtosis of the distribution. In the context of extreme events, a positive shape parameter results in a heavy-tailed distribution, implying a higher probability of very extreme events (far from the median), while a negative shape parameter results in a light-tailed distribution, implying a lower probability of such events.\n",
-    "\"\"\";"
+    "\"\"\""
    ]
   },
   {
diff --git a/tutorials/W2D3_ExtremesandVariability/instructor/W2D3_Tutorial4.ipynb b/tutorials/W2D3_ExtremesandVariability/instructor/W2D3_Tutorial4.ipynb
index bccce0c5f..9069a07d1 100644
--- a/tutorials/W2D3_ExtremesandVariability/instructor/W2D3_Tutorial4.ipynb
+++ b/tutorials/W2D3_ExtremesandVariability/instructor/W2D3_Tutorial4.ipynb
@@ -717,7 +717,7 @@
     "# to_remove explanation\n",
     "\"\"\"\n",
     "Put your observations here. GEV distribution describes the data better than the normal distribution. However, they are similar for shorter return periods. This suggests that for common, less extreme events (short return periods), both the Normal and GEV distributions provide a similar representation of the data. This similarity is likely due to the fact that for less extreme events, the tail of the distribution (which captures extreme events) is less relevant. When we move toards longer return periods (which correspond to more extreme events), the two curves start to diverge.\n",
-    "\"\"\";"
+    "\"\"\""
    ]
   },
   {
diff --git a/tutorials/W2D3_ExtremesandVariability/instructor/W2D3_Tutorial8.ipynb b/tutorials/W2D3_ExtremesandVariability/instructor/W2D3_Tutorial8.ipynb
index f48e25a05..2cb62330b 100644
--- a/tutorials/W2D3_ExtremesandVariability/instructor/W2D3_Tutorial8.ipynb
+++ b/tutorials/W2D3_ExtremesandVariability/instructor/W2D3_Tutorial8.ipynb
@@ -83,9 +83,9 @@
     "# condacolab.install()\n",
     "# !mamba install numpy matplotlib seaborn pandas cartopy scipy texttable xarrayutils cf_xarray cmocean\n",
     "\n",
-    "!wget https://raw.githubusercontent.com/neuromatch/climate-course-content/release-v0.2.1/tutorials/W2D3_ExtremesandVariability/extremes_functions.py\n",
-    "!wget https://raw.githubusercontent.com/neuromatch/climate-course-content/release-v0.2.1/tutorials/W2D3_ExtremesandVariability/gev_functions.py\n",
-    "!wget https://raw.githubusercontent.com/neuromatch/climate-course-content/release-v0.2.1/tutorials/W2D3_ExtremesandVariability/sdfc_classes.py"
+    "!wget https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W2D3_ExtremesandVariability/extremes_functions.py\n",
+    "!wget https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W2D3_ExtremesandVariability/gev_functions.py\n",
+    "!wget https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W2D3_ExtremesandVariability/sdfc_classes.py"
    ]
   },
   {
@@ -1036,7 +1036,7 @@
     "1. Return level for a 3-year event under SSP5-8.5 is 34.5 degrees C (SSP2-4.5: 32.5, SSP1-2.6: 32). This is more than a very rare event (return period >> 100 years) in all other scenarios\n",
     "2. Return level for a 100-year event during the historical period: 32 degrees (SSP1-2.6: 32.5, SSP2-4.5: 33, SSP5-8.5:35.5). In the other scenarios this is the new 'normal', or more specific common events in all scenarios. Under SSP1-2.6 it is a 4-year event, and an annual event in all other scenarios.\n",
     "\n",
-    "\"\"\";"
+    "\"\"\""
    ]
   },
   {
@@ -1821,7 +1821,7 @@
     "1. There is a larger fraction of land area exposed to extreme temperature conditions the higher the emission scenario.\n",
     "\n",
     "2. The choice of threshold here could certainly impact the results! The best way to know for sure is to try it out! While the threshold used here is physically grounded in studies, it is important to understand the sensitivity of this choice, especially when using models which are imperfect. One possible route to understanding the uncertainty more would be to use an ensemble of climate models, similar to those from the IPCC Physical Basis day.\n",
-    "\"\"\";"
+    "\"\"\""
    ]
   },
   {
diff --git a/tutorials/W2D3_ExtremesandVariability/solutions/W2D3_Tutorial1_Solution_a3bcafac.py b/tutorials/W2D3_ExtremesandVariability/solutions/W2D3_Tutorial1_Solution_be51f3cc.py
similarity index 98%
rename from tutorials/W2D3_ExtremesandVariability/solutions/W2D3_Tutorial1_Solution_a3bcafac.py
rename to tutorials/W2D3_ExtremesandVariability/solutions/W2D3_Tutorial1_Solution_be51f3cc.py
index ee185e4a6..e915a503a 100644
--- a/tutorials/W2D3_ExtremesandVariability/solutions/W2D3_Tutorial1_Solution_a3bcafac.py
+++ b/tutorials/W2D3_ExtremesandVariability/solutions/W2D3_Tutorial1_Solution_be51f3cc.py
@@ -1,3 +1,3 @@
 """
 1. As presented in the figure above, the data falls largely outside of the percentiles you calculated. That, paired with the skewness calculated earlier suggests a different distribution may fit the data better. For example, log-normal distributions tend to be better suited for describing skewed datasets such as this.
-""";
\ No newline at end of file
+"""
\ No newline at end of file
diff --git a/tutorials/W2D3_ExtremesandVariability/solutions/W2D3_Tutorial2_Solution_ff3a3b57.py b/tutorials/W2D3_ExtremesandVariability/solutions/W2D3_Tutorial2_Solution_99c3b035.py
similarity index 99%
rename from tutorials/W2D3_ExtremesandVariability/solutions/W2D3_Tutorial2_Solution_ff3a3b57.py
rename to tutorials/W2D3_ExtremesandVariability/solutions/W2D3_Tutorial2_Solution_99c3b035.py
index 67f833f95..c83cb3e40 100644
--- a/tutorials/W2D3_ExtremesandVariability/solutions/W2D3_Tutorial2_Solution_ff3a3b57.py
+++ b/tutorials/W2D3_ExtremesandVariability/solutions/W2D3_Tutorial2_Solution_99c3b035.py
@@ -1,4 +1,4 @@
 """
 1. 10, 40 and 70 mm/day.
 2. Our data only spans from 1920 to 2022. If we are truly interested in 100-year events we need to work with a longer dataset perhaps using paleo proxies or other instrumentation. The longer the dataset, the more frequently we would expect to observe the long return period events and increase our confidence in them. Other ideas would be estimating probability/cumulative density functions (next few tutorials) or to use resampling methods (coding exercise below).
-""";
\ No newline at end of file
+"""
\ No newline at end of file
diff --git a/tutorials/W2D3_ExtremesandVariability/solutions/W2D3_Tutorial3_Solution_974e66e8.py b/tutorials/W2D3_ExtremesandVariability/solutions/W2D3_Tutorial3_Solution_7a0210e5.py
similarity index 99%
rename from tutorials/W2D3_ExtremesandVariability/solutions/W2D3_Tutorial3_Solution_974e66e8.py
rename to tutorials/W2D3_ExtremesandVariability/solutions/W2D3_Tutorial3_Solution_7a0210e5.py
index 89e6aa02f..91099094a 100644
--- a/tutorials/W2D3_ExtremesandVariability/solutions/W2D3_Tutorial3_Solution_974e66e8.py
+++ b/tutorials/W2D3_ExtremesandVariability/solutions/W2D3_Tutorial3_Solution_7a0210e5.py
@@ -6,4 +6,4 @@
 Scale parameter: The scale parameter influences the spread or width of the distribution. A higher scale parameter will widen the distribution, implying greater variability in the data and thicker tails, while a lower scale parameter will narrow the distribution, implying less probability of extreme events.
 
 Shape parameter: This parameter is unique to the GEV distribution and impacts the tails of the distribution. It can make the tails of the distribution thinner or thicker, which in turn affects the skewness and kurtosis of the distribution. In the context of extreme events, a positive shape parameter results in a heavy-tailed distribution, implying a higher probability of very extreme events (far from the median), while a negative shape parameter results in a light-tailed distribution, implying a lower probability of such events.
-""";
\ No newline at end of file
+"""
\ No newline at end of file
diff --git a/tutorials/W2D3_ExtremesandVariability/solutions/W2D3_Tutorial4_Solution_9573c306.py b/tutorials/W2D3_ExtremesandVariability/solutions/W2D3_Tutorial4_Solution_33475dec.py
similarity index 99%
rename from tutorials/W2D3_ExtremesandVariability/solutions/W2D3_Tutorial4_Solution_9573c306.py
rename to tutorials/W2D3_ExtremesandVariability/solutions/W2D3_Tutorial4_Solution_33475dec.py
index d35c74311..4888c07f7 100644
--- a/tutorials/W2D3_ExtremesandVariability/solutions/W2D3_Tutorial4_Solution_9573c306.py
+++ b/tutorials/W2D3_ExtremesandVariability/solutions/W2D3_Tutorial4_Solution_33475dec.py
@@ -1,3 +1,3 @@
 """
 Put your observations here. GEV distribution describes the data better than the normal distribution. However, they are similar for shorter return periods. This suggests that for common, less extreme events (short return periods), both the Normal and GEV distributions provide a similar representation of the data. This similarity is likely due to the fact that for less extreme events, the tail of the distribution (which captures extreme events) is less relevant. When we move toards longer return periods (which correspond to more extreme events), the two curves start to diverge.
-""";
\ No newline at end of file
+"""
\ No newline at end of file
diff --git a/tutorials/W2D3_ExtremesandVariability/solutions/W2D3_Tutorial8_Solution_a557abd9.py b/tutorials/W2D3_ExtremesandVariability/solutions/W2D3_Tutorial8_Solution_027e5fa8.py
similarity index 99%
rename from tutorials/W2D3_ExtremesandVariability/solutions/W2D3_Tutorial8_Solution_a557abd9.py
rename to tutorials/W2D3_ExtremesandVariability/solutions/W2D3_Tutorial8_Solution_027e5fa8.py
index 00c990ca0..e10e21657 100644
--- a/tutorials/W2D3_ExtremesandVariability/solutions/W2D3_Tutorial8_Solution_a557abd9.py
+++ b/tutorials/W2D3_ExtremesandVariability/solutions/W2D3_Tutorial8_Solution_027e5fa8.py
@@ -2,4 +2,4 @@
 1. Return level for a 3-year event under SSP5-8.5 is 34.5 degrees C (SSP2-4.5: 32.5, SSP1-2.6: 32). This is more than a very rare event (return period >> 100 years) in all other scenarios
 2. Return level for a 100-year event during the historical period: 32 degrees (SSP1-2.6: 32.5, SSP2-4.5: 33, SSP5-8.5:35.5). In the other scenarios this is the new 'normal', or more specific common events in all scenarios. Under SSP1-2.6 it is a 4-year event, and an annual event in all other scenarios.
 
-""";
\ No newline at end of file
+"""
\ No newline at end of file
diff --git a/tutorials/W2D3_ExtremesandVariability/solutions/W2D3_Tutorial8_Solution_43e64815.py b/tutorials/W2D3_ExtremesandVariability/solutions/W2D3_Tutorial8_Solution_51796267.py
similarity index 99%
rename from tutorials/W2D3_ExtremesandVariability/solutions/W2D3_Tutorial8_Solution_43e64815.py
rename to tutorials/W2D3_ExtremesandVariability/solutions/W2D3_Tutorial8_Solution_51796267.py
index 63023ff85..97080a8eb 100644
--- a/tutorials/W2D3_ExtremesandVariability/solutions/W2D3_Tutorial8_Solution_43e64815.py
+++ b/tutorials/W2D3_ExtremesandVariability/solutions/W2D3_Tutorial8_Solution_51796267.py
@@ -2,4 +2,4 @@
 1. There is a larger fraction of land area exposed to extreme temperature conditions the higher the emission scenario.
 
 2. The choice of threshold here could certainly impact the results! The best way to know for sure is to try it out! While the threshold used here is physically grounded in studies, it is important to understand the sensitivity of this choice, especially when using models which are imperfect. One possible route to understanding the uncertainty more would be to use an ensemble of climate models, similar to those from the IPCC Physical Basis day.
-""";
\ No newline at end of file
+"""
\ No newline at end of file
diff --git a/tutorials/W2D3_ExtremesandVariability/static/W2D3_Tutorial1_Solution_e35d1bc8_1.png b/tutorials/W2D3_ExtremesandVariability/static/W2D3_Tutorial1_Solution_e35d1bc8_1.png
deleted file mode 100644
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GIT binary patch
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diff --git a/tutorials/W2D3_ExtremesandVariability/static/W2D3_Tutorial6_Solution_f0cfaef4_1.png b/tutorials/W2D3_ExtremesandVariability/static/W2D3_Tutorial6_Solution_f0cfaef4_2.png
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diff --git a/tutorials/W2D3_ExtremesandVariability/static/W2D3_Tutorial7_Solution_59610b73_1.png b/tutorials/W2D3_ExtremesandVariability/static/W2D3_Tutorial7_Solution_59610b73_1.png
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diff --git a/tutorials/W2D3_ExtremesandVariability/static/W2D3_Tutorial7_Solution_eb1ac56e_1.png b/tutorials/W2D3_ExtremesandVariability/static/W2D3_Tutorial7_Solution_eb1ac56e_1.png
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diff --git a/tutorials/W2D3_ExtremesandVariability/student/W2D3_Tutorial1.ipynb b/tutorials/W2D3_ExtremesandVariability/student/W2D3_Tutorial1.ipynb
index 4a95b6533..11fd81ea9 100644
--- a/tutorials/W2D3_ExtremesandVariability/student/W2D3_Tutorial1.ipynb
+++ b/tutorials/W2D3_ExtremesandVariability/student/W2D3_Tutorial1.ipynb
@@ -696,7 +696,7 @@
     "\n",
     "*Example output:*\n",
     "\n",
-    "<img alt='Solution hint' align='left' width=775.0 height=575.0 src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W2D3_ExtremesandVariability/static/W2D3_Tutorial1_Solution_e35d1bc8_1.png>\n",
+    "<img alt='Solution hint' align='left' width=775.0 height=575.0 src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W2D3_ExtremesandVariability/static/W2D3_Tutorial1_Solution_e35d1bc8_2.png>\n",
     "\n"
    ]
   },
@@ -742,7 +742,7 @@
     "execution": {}
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W2D3_ExtremesandVariability/solutions/W2D3_Tutorial1_Solution_a3bcafac.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W2D3_ExtremesandVariability/solutions/W2D3_Tutorial1_Solution_be51f3cc.py)\n",
     "\n"
    ]
   },
diff --git a/tutorials/W2D3_ExtremesandVariability/student/W2D3_Tutorial2.ipynb b/tutorials/W2D3_ExtremesandVariability/student/W2D3_Tutorial2.ipynb
index bab71bd35..7db956ed1 100644
--- a/tutorials/W2D3_ExtremesandVariability/student/W2D3_Tutorial2.ipynb
+++ b/tutorials/W2D3_ExtremesandVariability/student/W2D3_Tutorial2.ipynb
@@ -707,7 +707,7 @@
     "tags": []
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W2D3_ExtremesandVariability/solutions/W2D3_Tutorial2_Solution_ff3a3b57.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W2D3_ExtremesandVariability/solutions/W2D3_Tutorial2_Solution_99c3b035.py)\n",
     "\n"
    ]
   },
diff --git a/tutorials/W2D3_ExtremesandVariability/student/W2D3_Tutorial3.ipynb b/tutorials/W2D3_ExtremesandVariability/student/W2D3_Tutorial3.ipynb
index 0f3574db6..304d0c40d 100644
--- a/tutorials/W2D3_ExtremesandVariability/student/W2D3_Tutorial3.ipynb
+++ b/tutorials/W2D3_ExtremesandVariability/student/W2D3_Tutorial3.ipynb
@@ -924,7 +924,7 @@
     "execution": {}
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W2D3_ExtremesandVariability/solutions/W2D3_Tutorial3_Solution_974e66e8.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W2D3_ExtremesandVariability/solutions/W2D3_Tutorial3_Solution_7a0210e5.py)\n",
     "\n"
    ]
   },
diff --git a/tutorials/W2D3_ExtremesandVariability/student/W2D3_Tutorial4.ipynb b/tutorials/W2D3_ExtremesandVariability/student/W2D3_Tutorial4.ipynb
index eb1af07f8..1139a8382 100644
--- a/tutorials/W2D3_ExtremesandVariability/student/W2D3_Tutorial4.ipynb
+++ b/tutorials/W2D3_ExtremesandVariability/student/W2D3_Tutorial4.ipynb
@@ -692,7 +692,7 @@
     "execution": {}
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W2D3_ExtremesandVariability/solutions/W2D3_Tutorial4_Solution_9573c306.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W2D3_ExtremesandVariability/solutions/W2D3_Tutorial4_Solution_33475dec.py)\n",
     "\n"
    ]
   },
diff --git a/tutorials/W2D3_ExtremesandVariability/student/W2D3_Tutorial6.ipynb b/tutorials/W2D3_ExtremesandVariability/student/W2D3_Tutorial6.ipynb
index 96bdd78c6..63ea50a4f 100644
--- a/tutorials/W2D3_ExtremesandVariability/student/W2D3_Tutorial6.ipynb
+++ b/tutorials/W2D3_ExtremesandVariability/student/W2D3_Tutorial6.ipynb
@@ -1175,7 +1175,7 @@
     "\n",
     "*Example output:*\n",
     "\n",
-    "<img alt='Solution hint' align='left' width=775.0 height=575.0 src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W2D3_ExtremesandVariability/static/W2D3_Tutorial6_Solution_f0cfaef4_1.png>\n",
+    "<img alt='Solution hint' align='left' width=775.0 height=575.0 src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W2D3_ExtremesandVariability/static/W2D3_Tutorial6_Solution_f0cfaef4_2.png>\n",
     "\n"
    ]
   },
diff --git a/tutorials/W2D3_ExtremesandVariability/student/W2D3_Tutorial8.ipynb b/tutorials/W2D3_ExtremesandVariability/student/W2D3_Tutorial8.ipynb
index 20cd69a9d..3779d3b4b 100644
--- a/tutorials/W2D3_ExtremesandVariability/student/W2D3_Tutorial8.ipynb
+++ b/tutorials/W2D3_ExtremesandVariability/student/W2D3_Tutorial8.ipynb
@@ -83,9 +83,9 @@
     "# condacolab.install()\n",
     "# !mamba install numpy matplotlib seaborn pandas cartopy scipy texttable xarrayutils cf_xarray cmocean\n",
     "\n",
-    "!wget https://raw.githubusercontent.com/neuromatch/climate-course-content/release-v0.2.1/tutorials/W2D3_ExtremesandVariability/extremes_functions.py\n",
-    "!wget https://raw.githubusercontent.com/neuromatch/climate-course-content/release-v0.2.1/tutorials/W2D3_ExtremesandVariability/gev_functions.py\n",
-    "!wget https://raw.githubusercontent.com/neuromatch/climate-course-content/release-v0.2.1/tutorials/W2D3_ExtremesandVariability/sdfc_classes.py"
+    "!wget https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W2D3_ExtremesandVariability/extremes_functions.py\n",
+    "!wget https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W2D3_ExtremesandVariability/gev_functions.py\n",
+    "!wget https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/W2D3_ExtremesandVariability/sdfc_classes.py"
    ]
   },
   {
@@ -1030,7 +1030,7 @@
     "execution": {}
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W2D3_ExtremesandVariability/solutions/W2D3_Tutorial8_Solution_a557abd9.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W2D3_ExtremesandVariability/solutions/W2D3_Tutorial8_Solution_027e5fa8.py)\n",
     "\n"
    ]
   },
@@ -1810,7 +1810,7 @@
     "execution": {}
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W2D3_ExtremesandVariability/solutions/W2D3_Tutorial8_Solution_43e64815.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/climate-course-content/tree/main/tutorials/W2D3_ExtremesandVariability/solutions/W2D3_Tutorial8_Solution_51796267.py)\n",
     "\n"
    ]
   },
diff --git a/tutorials/instructor/intro.ipynb b/tutorials/instructor/intro.ipynb
new file mode 100644
index 000000000..be1bde326
--- /dev/null
+++ b/tutorials/instructor/intro.ipynb
@@ -0,0 +1,190 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "colab_type": "text",
+    "execution": {},
+    "id": "view-in-github"
+   },
+   "source": [
+    "<a href=\"https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/intro.ipynb\" target=\"_blank\"><img alt=\"Open In Colab\" src=\"https://colab.research.google.com/assets/colab-badge.svg\"/></a>   <a href=\"https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/intro.ipynb\" target=\"_blank\"><img alt=\"Open in Kaggle\" src=\"https://kaggle.com/static/images/open-in-kaggle.svg\"/></a>\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "execution": {},
+    "pycharm": {
+     "name": "#%% md\n"
+    }
+   },
+   "source": [
+    "# Introduction\n",
+    "\n",
+    "## Welcome to Computational Tools in Climate Science!\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "execution": {}
+   },
+   "source": [
+    "![Sponsors](./static/CMA_Logo_Block_2024.png)\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "execution": {},
+    "pycharm": {
+     "name": "#%% md\n"
+    }
+   },
+   "source": [
+    "## Concepts map\n",
+    "\n",
+    "<img src=\"Art/CMA_Concept_Map.png\" alt=\"Concept map overview of curriculum\" class=\"bg-primary\" width=\"100%\">\n",
+    "\n",
+    "\\*Image made by Sloane Garelick\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "execution": {}
+   },
+   "source": [
+    "We have curated an integrated program of tutorials, research projects, and professional development activities. The curriculum spans most areas of climate science and will cover cutting-edge methods to analyze climate data and models. This section will overview the curriculum.\n",
+    "\n",
+    "## Prerequisite refreshers\n",
+    "\n",
+    "We curated a number of [refresher resources](https://github.com/neuromatch/precourse/blob/main/prereqs/ClimateScience.md) for you that will help you prepare for Climatematch Academy. You are not required to study this material before the course. It is rather meant to help you detect and fill any gaps you may have in your knowledge.\n",
+    "The **Introduction to Python** pre-course is an asynchronous course that you can complete on your own time. You will learn how to code in Python from scratch using straightforward examples curated by Project Pythia. If you have questions about the pre-course material, we offer support via Discord chat.\n",
+    "You will also find other open-source resources to catch up on algebra, statistics, calculus, physics, chemistry, and climate science. The topics covered on these days were carefully chosen based on what you need for the course.\n",
+    "\n",
+    "## The Academy begins!\n",
+    "\n",
+    "You will start out your two weeks at Climatematch Academy covering the **fundamentals** for understanding climate science data and research. This will include an overview of the climate system and xarray, as well as an introduction to good, equitable research practices.\n",
+    "\n",
+    "You will then switch your focus to different types of **climate data**. You will use reanalysis products, remote sensing data, and paleoclimate proxy data to understand multi-scale climate interactions, climate monitoring, and variations in past marine, terrestrial, and atmospheric climates.\n",
+    "\n",
+    "This will be followed by an introduction to the **future of the climate system** as predicted through climate modeling. You will learn about climate models, how to interpret their projections of future climate, and the standard framework for assessing socio-economic climate risks. You will also explore pathways to mitigate those risks. During this time, you will also have a full day to work on your research projects, which will give you a chance to incorporate these new insights into your data analyses and interpretation.\n",
+    "\n",
+    "Finally, the course will cover the **responses to climate change**, including identification of extreme climate events, like heatwaves, droughts, or wildfires, and the use of climate data for tracking the impacts of climate change to inform adaptation measures.\n",
+    "\n",
+    "You can find more details on the daily schedule and topics taught on different days in the [General Schedule](https://comptools.climatematch.io/tutorials/Schedule/daily_schedules.html).\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "execution": {}
+   },
+   "source": [
+    "# Video: Student Orientation"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @markdown\n",
+    "\n",
+    "from ipywidgets import widgets\n",
+    "from IPython.display import YouTubeVideo\n",
+    "from IPython.display import IFrame\n",
+    "from IPython.display import display\n",
+    "\n",
+    "\n",
+    "class PlayVideo(IFrame):\n",
+    "    def __init__(self, id, source, page=1, width=400, height=300, **kwargs):\n",
+    "        self.id = id\n",
+    "        if source == \"Bilibili\":\n",
+    "            src = f\"https://player.bilibili.com/player.html?bvid={id}&page={page}\"\n",
+    "        elif source == \"Osf\":\n",
+    "            src = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/download/{id}/?direct%26mode=render\"\n",
+    "        super(PlayVideo, self).__init__(src, width, height, **kwargs)\n",
+    "\n",
+    "\n",
+    "def display_videos(video_ids, W=400, H=300, fs=1):\n",
+    "    tab_contents = []\n",
+    "    for i, video_id in enumerate(video_ids):\n",
+    "        out = widgets.Output()\n",
+    "        with out:\n",
+    "            if video_ids[i][0] == \"Youtube\":\n",
+    "                video = YouTubeVideo(\n",
+    "                    id=video_ids[i][1], width=W, height=H, fs=fs, rel=0\n",
+    "                )\n",
+    "                print(f\"Video available at https://youtube.com/watch?v={video.id}\")\n",
+    "            else:\n",
+    "                video = PlayVideo(\n",
+    "                    id=video_ids[i][1],\n",
+    "                    source=video_ids[i][0],\n",
+    "                    width=W,\n",
+    "                    height=H,\n",
+    "                    fs=fs,\n",
+    "                    autoplay=False,\n",
+    "                )\n",
+    "                if video_ids[i][0] == \"Bilibili\":\n",
+    "                    print(\n",
+    "                        f\"Video available at https://www.bilibili.com/video/{video.id}\"\n",
+    "                    )\n",
+    "                elif video_ids[i][0] == \"Osf\":\n",
+    "                    print(f\"Video available at https://osf.io/{video.id}\")\n",
+    "            display(video)\n",
+    "        tab_contents.append(out)\n",
+    "    return tab_contents\n",
+    "\n",
+    "\n",
+    "video_ids = [(\"Youtube\", \"FwjyhCLeqx0\"), (\"Bilibili\", \"BV1QE421P7EJ\")\n",
+    "            ]\n",
+    "tab_contents = display_videos(video_ids, W=730, H=410)\n",
+    "tabs = widgets.Tab()\n",
+    "tabs.children = tab_contents\n",
+    "for i in range(len(tab_contents)):\n",
+    "    tabs.set_title(i, video_ids[i][0])\n",
+    "display(tabs)"
+   ]
+  }
+ ],
+ "metadata": {
+  "colab": {
+   "collapsed_sections": [],
+   "include_colab_link": true,
+   "name": "intro",
+   "provenance": [],
+   "toc_visible": true
+  },
+  "kernel": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.19"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/tutorials/intro.ipynb b/tutorials/intro.ipynb
index 082249131..be1bde326 100644
--- a/tutorials/intro.ipynb
+++ b/tutorials/intro.ipynb
@@ -79,7 +79,9 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "execution": {}
+   },
    "source": [
     "# Video: Student Orientation"
    ]
@@ -87,7 +89,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
    "outputs": [],
    "source": [
     "# @markdown\n",
@@ -177,7 +182,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.18"
+   "version": "3.9.19"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/student/intro.ipynb b/tutorials/student/intro.ipynb
new file mode 100644
index 000000000..be1bde326
--- /dev/null
+++ b/tutorials/student/intro.ipynb
@@ -0,0 +1,190 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "colab_type": "text",
+    "execution": {},
+    "id": "view-in-github"
+   },
+   "source": [
+    "<a href=\"https://colab.research.google.com/github/neuromatch/climate-course-content/blob/main/tutorials/intro.ipynb\" target=\"_blank\"><img alt=\"Open In Colab\" src=\"https://colab.research.google.com/assets/colab-badge.svg\"/></a>   <a href=\"https://kaggle.com/kernels/welcome?src=https://raw.githubusercontent.com/neuromatch/climate-course-content/main/tutorials/intro.ipynb\" target=\"_blank\"><img alt=\"Open in Kaggle\" src=\"https://kaggle.com/static/images/open-in-kaggle.svg\"/></a>\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "execution": {},
+    "pycharm": {
+     "name": "#%% md\n"
+    }
+   },
+   "source": [
+    "# Introduction\n",
+    "\n",
+    "## Welcome to Computational Tools in Climate Science!\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "execution": {}
+   },
+   "source": [
+    "![Sponsors](./static/CMA_Logo_Block_2024.png)\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "execution": {},
+    "pycharm": {
+     "name": "#%% md\n"
+    }
+   },
+   "source": [
+    "## Concepts map\n",
+    "\n",
+    "<img src=\"Art/CMA_Concept_Map.png\" alt=\"Concept map overview of curriculum\" class=\"bg-primary\" width=\"100%\">\n",
+    "\n",
+    "\\*Image made by Sloane Garelick\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "execution": {}
+   },
+   "source": [
+    "We have curated an integrated program of tutorials, research projects, and professional development activities. The curriculum spans most areas of climate science and will cover cutting-edge methods to analyze climate data and models. This section will overview the curriculum.\n",
+    "\n",
+    "## Prerequisite refreshers\n",
+    "\n",
+    "We curated a number of [refresher resources](https://github.com/neuromatch/precourse/blob/main/prereqs/ClimateScience.md) for you that will help you prepare for Climatematch Academy. You are not required to study this material before the course. It is rather meant to help you detect and fill any gaps you may have in your knowledge.\n",
+    "The **Introduction to Python** pre-course is an asynchronous course that you can complete on your own time. You will learn how to code in Python from scratch using straightforward examples curated by Project Pythia. If you have questions about the pre-course material, we offer support via Discord chat.\n",
+    "You will also find other open-source resources to catch up on algebra, statistics, calculus, physics, chemistry, and climate science. The topics covered on these days were carefully chosen based on what you need for the course.\n",
+    "\n",
+    "## The Academy begins!\n",
+    "\n",
+    "You will start out your two weeks at Climatematch Academy covering the **fundamentals** for understanding climate science data and research. This will include an overview of the climate system and xarray, as well as an introduction to good, equitable research practices.\n",
+    "\n",
+    "You will then switch your focus to different types of **climate data**. You will use reanalysis products, remote sensing data, and paleoclimate proxy data to understand multi-scale climate interactions, climate monitoring, and variations in past marine, terrestrial, and atmospheric climates.\n",
+    "\n",
+    "This will be followed by an introduction to the **future of the climate system** as predicted through climate modeling. You will learn about climate models, how to interpret their projections of future climate, and the standard framework for assessing socio-economic climate risks. You will also explore pathways to mitigate those risks. During this time, you will also have a full day to work on your research projects, which will give you a chance to incorporate these new insights into your data analyses and interpretation.\n",
+    "\n",
+    "Finally, the course will cover the **responses to climate change**, including identification of extreme climate events, like heatwaves, droughts, or wildfires, and the use of climate data for tracking the impacts of climate change to inform adaptation measures.\n",
+    "\n",
+    "You can find more details on the daily schedule and topics taught on different days in the [General Schedule](https://comptools.climatematch.io/tutorials/Schedule/daily_schedules.html).\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "execution": {}
+   },
+   "source": [
+    "# Video: Student Orientation"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "execution": {}
+   },
+   "outputs": [],
+   "source": [
+    "# @markdown\n",
+    "\n",
+    "from ipywidgets import widgets\n",
+    "from IPython.display import YouTubeVideo\n",
+    "from IPython.display import IFrame\n",
+    "from IPython.display import display\n",
+    "\n",
+    "\n",
+    "class PlayVideo(IFrame):\n",
+    "    def __init__(self, id, source, page=1, width=400, height=300, **kwargs):\n",
+    "        self.id = id\n",
+    "        if source == \"Bilibili\":\n",
+    "            src = f\"https://player.bilibili.com/player.html?bvid={id}&page={page}\"\n",
+    "        elif source == \"Osf\":\n",
+    "            src = f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/download/{id}/?direct%26mode=render\"\n",
+    "        super(PlayVideo, self).__init__(src, width, height, **kwargs)\n",
+    "\n",
+    "\n",
+    "def display_videos(video_ids, W=400, H=300, fs=1):\n",
+    "    tab_contents = []\n",
+    "    for i, video_id in enumerate(video_ids):\n",
+    "        out = widgets.Output()\n",
+    "        with out:\n",
+    "            if video_ids[i][0] == \"Youtube\":\n",
+    "                video = YouTubeVideo(\n",
+    "                    id=video_ids[i][1], width=W, height=H, fs=fs, rel=0\n",
+    "                )\n",
+    "                print(f\"Video available at https://youtube.com/watch?v={video.id}\")\n",
+    "            else:\n",
+    "                video = PlayVideo(\n",
+    "                    id=video_ids[i][1],\n",
+    "                    source=video_ids[i][0],\n",
+    "                    width=W,\n",
+    "                    height=H,\n",
+    "                    fs=fs,\n",
+    "                    autoplay=False,\n",
+    "                )\n",
+    "                if video_ids[i][0] == \"Bilibili\":\n",
+    "                    print(\n",
+    "                        f\"Video available at https://www.bilibili.com/video/{video.id}\"\n",
+    "                    )\n",
+    "                elif video_ids[i][0] == \"Osf\":\n",
+    "                    print(f\"Video available at https://osf.io/{video.id}\")\n",
+    "            display(video)\n",
+    "        tab_contents.append(out)\n",
+    "    return tab_contents\n",
+    "\n",
+    "\n",
+    "video_ids = [(\"Youtube\", \"FwjyhCLeqx0\"), (\"Bilibili\", \"BV1QE421P7EJ\")\n",
+    "            ]\n",
+    "tab_contents = display_videos(video_ids, W=730, H=410)\n",
+    "tabs = widgets.Tab()\n",
+    "tabs.children = tab_contents\n",
+    "for i in range(len(tab_contents)):\n",
+    "    tabs.set_title(i, video_ids[i][0])\n",
+    "display(tabs)"
+   ]
+  }
+ ],
+ "metadata": {
+  "colab": {
+   "collapsed_sections": [],
+   "include_colab_link": true,
+   "name": "intro",
+   "provenance": [],
+   "toc_visible": true
+  },
+  "kernel": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.19"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}