I'm a passionate Data Scientist and a beginner in Data Engineering, always eager to learn and work on innovative data-driven projects. My journey so far has been focused on applying AI and machine learning techniques to real-world problems, and I'm now diving deeper into cloud infrastructure, big data, and stream processing.
- 🌱 Currently learning: Cloud Infrastructure (AWS, GCP), Data Engineering tools, Big Data, Stream Processing
- 🔭 Working on: Building real-time data pipelines and exploring new ML techniques
- 💬 Ask me about: Data Science, Machine Learning, Data Engineering, Apache Kafka, AI Applications
- ⚡ Fun fact: I’m a huge fan of space exploration, and I love staying updated on the latest developments in AI and its potential in space research!
- Languages: Python, SQL
- Data Engineering: Apache Kafka, Apache Airflow, DBT, Terraform, Databricks
- Cloud: Google Cloud Platform (GCP), AWS, Snowflake
- Databases: PostgreSQL, BigQuery ...
- Databases: PostgreSQL, BigQ
- Data Quality: soda
- Machine Learning: Scikit-learn, TensorFlow, NLP
Developed a predictive model to analyze sentiments from text written in Darija, including a Streamlit interface for user interaction.
In this project, I developed an end-to-end data engineering pipeline for analyzing real-time stock market data using Apache Kafka. The pipeline processes stock market data in real time, stores it in Amazon S3, and catalogs it using AWS Glue. The processed data can then be queried using Amazon Athena for powerful data analysis and insights.
Feel free to check out my repositories and contribute to any ongoing projects! 🚀
