Scientific Python Lectures

One document to learn numerics, science, and data with Python

Tutorials on the scientific Python ecosystem: a quick introduction to central tools and techniques. The different chapters each correspond to a 1 to 2 hours course with increasing level of expertise, from beginner to expert.

Release: 2025.2rc0.dev0

Getting started with Python for Science

• Introduction to getting started
• Python scientific computing ecosystem
• The Python language
• NumPy: creating and manipulating numerical data
• Matplotlib: plotting
• SciPy: high-level scientific computing
• Getting help and finding documentation

Advanced topics

• Introduction to advanced topics
• Advanced Python Constructs
• Advanced NumPy
• Debugging code
• Optimizing code
• Scipy sparse arrays
• Image manipulation and processing using NumPy and SciPy
• Mathematical optimization: finding minima of functions
• Interfacing with C

Packages and applications

• Introduction to packages and applications
• Statistics in Python
• sympy : Symbolic Mathematics in Python
• scikit-image: image processing
• scikit-learn: machine learning in Python

About

• About the Scientific Python Lecture notes
• Authors
• What’s new
• License
• Contributing