Programming for scientists

Below you can find the text and Jupyter notebooks that are used for this lecture.
Additions to the original lecture design were made by Markus Demleitner and Robert Schmidt.
Modifications were added by Yiannis Tsapras and Markus Hundertmark.

Day 1:

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

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

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

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

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

• The SciPy Lecture Notes at http://www.scipy-lectures.org/
• Matplotlib and Numpy video tutorial
• Integration, Interpolation and Curve Fitting video tutorial