Python Resources

Last updated on January 20, 2026.

Introductory Books

• Think Python, Allen B. Downey (Third Ed., O’Reilly, 2024)
• Introduction to Scientific Programming with Python, Joakim Sundnes (Springer, 2020)
• Python for Scientists, John Stewart and Michael Mommert, (Third Edition, CUP, 2023)

Introductory Numerical and Scientific Computing

• Learning Scientific Programming with Python, Christian Hill (Second Ed., CUP, 2020)
• Mathematical Python, Patrick Walls, University of British Columbia
• Python Programming and Numerical Methods: A Guide for Engineers and Scientists, Qingkai Kong, Timmy Siauw, Alexandre M. Bayen (Academic Press, 2021)

Advanced Scientific Computing

• Numerical Methods in Physics with Python, Alex Gezerlis (Second Ed., CUP, 2023)
• Numerical Python: Scientific Computing and Data Science Applications with NumPy, SciPy and Matplotlib,, Robert Johansson (Third Edition, Apress, 2024)
• Computational Statistics Using Python (2017), Cliburn Chan, Janice McCarthy, Duke University
• Computational Statistics and Statistical Computing (2018), Cliburn Chan, Duke University
• Computational Physics: Problem Solving with Python, Rubin H. Landau, Manuel J. Páez, Cristian C. Bordeianu (Fourth Ed.,Wiley-VCH, 2024)
• Computational Physics: Problem Solving with Python, Rubin H. Landau, Manuel J. Páez, Cristian C. Bordeianu (Third Ed.,Wiley-VCH, 2015)

Machine Learning

• Hands-On Machine Learning with Scikit-Learn and PyTorch: Concepts, Tools, and Techniques to Build Intelligent Systems, Aurélien Géron (O’Reilly Media, 2025)

• Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems, Aurélien Géron (O’Reilly Media, 2019)

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