Overview

The lessons in chronological order so far¹ (the list will be complete at the end of the semester):

1. 00 Installing the environment
2. 01 The Unix Shell
3. 02 Introduction to Python
4. 02' Git Basics
5. 03 Introduction to NumPy
6. 04 Numbers and Errors
7. 05 More errors
8. 06 Differentiation
9. 07 Integration
10. 08 Ordinary Differential Equations (ODEs)
11. 09 Molecular Dynamics (MD) Simulations
12. 10 Git for Collaboration
13. 11 Root finding by trial-and-error
14. 12 Linear Algebra
15. 13 Partial Differential Equations (PDEs)
16. 14 Defensive Programming
17. 15 Solving PDEs with time stepping
18. 16 Performance optimization
19. 17 Final Poster Symposium
20. 18 Summary and Review

Sometimes lessons span more than one lecture but this is not explicitly marked. The dates associated with each lesson indicate the day when the lesson was introduced for the first time.

Most of the teaching material is available as Jupyter notebooks and linked from the lesson pages (typically, near the bottom). For lessons in progress, links initially only point to incomplete materials. Full materials including solutions to in-class problems are always made available after the completion of the lesson.