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This is a collection of different assigments completed as part of the Programming for Everybody (Getting Started with Python) Coursera course: https://www.coursera.org/learn/python?

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This is a collection of different assignments completed as part of the Programming for Everybody (Getting Started with Python) Coursera course: https://www.coursera.org/learn/python?

Textbook: http://do1.dr-chuck.com/pythonlearn/EN_us/pythonlearn.pdf

Per Course rights: "The code for this site [PY4E, not Coursera] including the auto graders, slides, and course content is all available on GitHub. That means you could make your own copy of the course site, publish it and remix it any way you like."

NOTE: This is meant to showcase the skills I learned as part of the course. PLEASE DO NOT USE IF IN THE COURSE AS IT IS VALUABLE TO TRY TO WORK THROUGH THE PROBLEMS ON YOUR OWN! First few chapters are basic coding/python tutorial and not included.

Table of contents:

Chapter Three: Conditional Code
	In this section we move from sequential code that simply runs one line of code after another to conditional code where some steps are skipped. It is a very simple concept - but it is how computer software makes "choices".
	3.1 Conditional Statements
	3.2 More Conditional Statements


Chapter Four: Functions
	This is a relatively short chapter. We will learn about what functions are and how we can use them. The programs in the first chapters of the book are not large enough to require us to develop functions, but as the book moves into more and more complex programs, functions will be an essential way for us to make sense of our code.
	4.1 - Using Functions
	4.2 - Building Functions


Chapter Five: Loops and Iteration
	Loops and iteration complete our four basic programming patterns. Loops are the way we tell Python to do something over and over. Loops are the way we build programs that stay with a problem until the problem is solved.
	5.1 - Loops and Iteration
	5.2 - Definite Loops
	5.3 - Finding the Largest Value
	5.4 - Loop Idioms


Chapter Six: Strings
	In this class, we pick up where we left off in the previous class, starting in Chapter 6 of the textbook and covering Strings and moving into data structures. The second week of this class is dedicated to getting Python installed if you want to actually run the applications on your desktop or laptop. If you choose not to install Python, you can just skip to the third week and get a head start.
	6.1 - Strings
	6.2 - Manipulating Strings


Chapter Seven: Files
	Up to now, we have been working with data that is read from the user or data in constants. But real programs process much larger amounts of data by reading and writing files on the secondary storage on your computer. In this chapter we start to write our first programs that read, scan, and process real data.
	7.1 - Files
	7.2 - Processing Files


Chapter Eight: Lists
	As we want to solve more complex problems in Python, we need more powerful variables. Up to now we have been using simple variables to store numbers or strings where we have a single value in a variable. Starting with lists we will store many values in a single variable using an indexing scheme to store, organize, and retrieve different values from within a single variable. We call these multi-valued variables "collections" or "data structures".
	8.1 - Lists
	8.2 - Manipulating Lists
	8.3 - Lists and Strings


Chapter Nine: Dictionaries
	The Python dictionary is one of its most powerful data structures. Instead of representing values in a linear list, dictionaries store data as key / value pairs. Using key / value pairs gives us a simple in-memory "database" in a single Python variable.
	9.1 - Dictionaries
	9.2 - Counting with Dictionaries
	9.3 - Dictionaries and Files


Chapter Ten: Tuples
	Tuples are our third and final basic Python data structure. Tuples are a simple version of lists. We often use tuples in conjunction with dictionaries to accomplish multi-step tasks like sorting or looping through all of the data in a dictionary.
	10 - Tuples

Chapter Eleven: Regular Expressions
	Regular expressions are a very specialized language that allow us to succinctly search strings and extract data from strings. Regular expressions are a language unto themselves. It is not essential to know how to use regular expressions, but they can be quite useful and powerful.
	11 - R.E.

Chapter Twelve: Networks and Sockets / Programs that Surf the web
	In this section we learn about the protocols that web browsers use to retrieve documents and web applications use to interact with Application Program Interfaces (APIs) and learn to use Python to retrieve data from web sites and APIs over the Internet.
	12.1 Networked Technology
	12.2 Hypertext Transfer Protocol (HTTP)
	12.3 Unicode Characters and Strings
	12.4 Retrieving Web Pages
	12.5 Parsing Web Pages

Chapter Thirteen: Webservices (XML and JSON)
	In this section, we learn how to retrieve and parse XML (eXtensible Markup Language) data as well as Application Program Interfaces / Web Services using the JavaScript Object Notation (JSON) data format.
	13.1 Data on the Web
	13.2 eXtensible Markup Language (XML)
	13.3 XML Schema
	13.4 Parsing XML
	13.5 JavaScript Object Notation (JSON)
	13.6 Service Oriented Approach
	13.7 Using Application Programming Interfaces
	13.8 Securing API Requests

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This is a collection of different assigments completed as part of the Programming for Everybody (Getting Started with Python) Coursera course: https://www.coursera.org/learn/python?

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