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

• Cognitive Class
• IBM Cloud
• Joseph Santarcangelo
• Mavis Zhou
• Python for Data Science and AI (Coursera)
• Jupyter Notebook
• Google Colab
• Raph Trajano

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