Slides and demos (in Jupyter Notebook form) for all the courses I currently teach on an ongoing basis at the University of Illinois are now available in open source form on Github:
- Numerical Analysis (for CS450)
- Numerical Methods for Partial Differential Equations (for CS555)
- Fast Algorithms and Integral Equations
- Languages and Abstractions for High-Performance Scientific Computing
The license on all these is the MIT/X-Consortium one, permitting any use at all as long as copyright notices/attributions are preservend and while disclaiming any warranty.
The slides are written in Org Mode which I have found to offer a quick and convenient way of content creation. The Org source code is used to generate fairly readable TeX/Beamer code. (If Org is not your speed, you can easily just use the export TeX.)
I have two-and-a-half specific hopes with this release:
- First, I hope that my students will find creative ways to remix this content into things that are useful to them (flash cards? an LLM bot?).
- First-and-a-half, I am hoping for issue reports/pull requests if issues are spotted.
- Second, I am hoping to offer something of value to my colleagues in the teaching profession (particularly perhaps those just starting out) who may be able to remix this content into something that helps with their course preparation.
But as it always is with open source: The best use cases show up out of the woodwork unexpectedly.