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A very useful collection of Jupyter Notebooks, which aims to introduce the Python programming language.

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Introduction to Python

This is a collection of Jupyter notebooks that is intended to provide an introduction to the Python programming language. Although this collection is aimed to the beginner data science student, I found it very useful for any beginner in python programming. All notebooks were developed and released by IBM Cognitive Class, with some minors changes, organization and customizations provided by me.

Notebooks

The notebooks are divided by the following topics. I also provided the estimated time required to complete each lesson, a link to the source code, and the Google Colab link where anyone can use to follow the lessons and run the examples.

Python Basics

This section covers the python basics: print, import, types, expressions and strings.

Lesson Estimated time needed Source Code Colab
Your first program 10 min Open Open
Types 10 min Open Open
Expressions and Variables 10 min Open Open
String Operations 15 min Open Open
Total 45 min

Python Data Structures

This section covers the main Python data structures.

Lesson Estimated time needed Source Code Colab
Tuples 15 min Open Open
Lists 15 min Open Open
Dictionaries 20 min Open Open
Sets 20 min Open Open
Total 75 min

Python Programming Fundamentals

This section covers the fundamentals of Python language, logic and control structures, functions, and object-oriented programming in Python.

Lesson Estimated time needed Source Code Colab
Conditions and Branching 20 min Open Open
Loops 20 min Open Open
Functions 40 min Open Open
Classes and Objects 40 min Open Open
Total 120 min

Files

This section covers the basics of File handling in Python.

Lesson Estimated time needed Source Code Colab
Reading files with open 40 min Open Open
Writing files with open 15 min Open Open
Total 55 min

Python Data Analysis Library (Pandas)

This section covers an introduction to pandas, an open source library that provides high-performance, easy-to-use data structures and data analysis tools for the Python programming language.

Lesson Estimated time needed Source Code Colab
Reading files with open 15 min Open Open

NumPy

This section covers an introduction to NumPy, the fundamental package for scientific computing with Python.

NumPy makes it easier to do many operations that are commonly performed in data science. The same operations are usually computationally faster and require less memory in NumPy compared to regular Python.

Lesson Estimated time needed Source Code Colab
1D NumPy in Python 30 min Open Open
2D NumPy in Python 20 min Open Open
Total 50 min

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgments

And a special thanks to Raph Trajano for reviewing and fixing the materials.