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 The first Python program
4. 03 Git Basics
5. 04 Introduction to Python I — Variables and Python data types
6. 04 Introduction to Python II — Flow control
7. 04 Introduction to Python III — Functions
8. 04 Introduction to Python IV — Modules and Objects
9. 05 Debugging Primer
10. 06 Introduction to NumPy
11. 07 Numbers
12. 08 Errors
13. 09 Differentiation
14. 10 Ordinary Differential Equations (ODEs)
15. 11 Molecular Dynamics (MD) Simulations
16. 12 ODEs: Applications
17. 13 Root finding by trial-and-error
18. 14 Linear Algebra
19. 15 Code optimization
20. 16 Partial Differential Equations (PDEs)
21. 17 Solving PDEs with time stepping
22. 18 PDEs: Wave equation
23. Final Poster Symposium
24. 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.