Python: programming for scientists

My next course in the winter semester 2026/27 will take place October 5th to 9th, 2026.

Registration will be possible in heico, and should open sometime in summer (probably August).

This lecture is to a large part based on the lecture by Thomas Robitaille
The material is published under the Creative Commons BY-NC-SA License.

Below you can find the text and the jupyter notebooks that are used for this lecture.
Additions to the original lecture material were made by Markus Demleitner, Markus Hundertmark and myself.

Day 1:

• 00. About the course [notebook]
• 01. What is Python [notebook]
• 02. Using the jupyter notebook [notebook]
• 03. Numbers, String, and Lists [notebook]
• 04. Booleans, Tuples, and, Dictionaries [notebook]
• 05. Control Flow [notebook]
• Practice Problem - Cryptography [notebook]

• 06. Functions [notebook]
• 07. Reading and writing files [notebook]
• 08. Modules and Variable Scope [notebook]
• Practice Problem - Temperatures [notebook]
• Problem set 1 [notebook]

• 09. Introduction to Numpy [notebook]
• 10. Introduction to Matplotlib [notebook]
• 11. Files and paths [notebook]
• 12. String Formatting [notebook]
• Practice Problem - Monte-Carlo Error Propagation [notebook]
• Problem set 2 [notebook]

• 13. Python variables - behind the scenes [notebook]
• 14. Fitting models to data [notebook]
• 15. Interpolation and Integration [notebook]
• 16. Understanding Python errors [notebook]
• Practice Problem - Radioactive Decay [notebook]
• Problem set 3 [notebook]

• 17. Accessing remote resources [notebook]
• 18. Object-oriented programming [notebook]
• 19. List comprehension [notebook]