Further Readings

I will update this list from time to time.

A general further readings list on Python (with a focus on Data Science) can be found in the Python Basics course material.

Online tutorials

• Programming for Computations - A Gentle Introduction to Numerical Simulations with Python or MATLAB/Octave ꜛ by S. Linge and Hans Petter Langtangen ꜛ.
• IPython Interactive Computing and Visualization Cookbook ꜛ, Second Edition (2018), by Cyrille Rossant ꜛ - the online version of this book is free and it provides an excellent introduction to data analysis with Python paired with a large amount of very good code examples, that are also shared and freely available on GitHub ꜛ.
• Introduction to Linear Algebra for Applied Machine Learning with Python ꜛ by Pablo Caceres ꜛ.
• Data All The Wayꜛ, a blog by Rohit Farmer ()/) with very good tutorials and examples on data analysis with Python, Julia and R.