January 2026
114/180 creditsastronomy+6 credits
March 2026
120/180 creditsdata-management-1+12 credits
June 2026
132/180 creditsfoundations of computer science+6 credits
July 2026
138/180 creditsprobability+6 credits
phys+6 credits
September 2026
150/180 creditsai&ml+12 credits
- https://www.youtube.com/watch?v=GfwFNKCys9c? :: RL
- Learn basic NNs at a simple level, build from scratch (no frameworks) a feed forward neural network with back propagation to train against MNIST or something as simple. Understand every part of it. Just use your favorite programming language._Karpathy YT
- implement word2vec from scratch (in C?)
- https://karpathy.medium.com/yes-you-should-understand-backprop-e2f06eab496b? yes, you should understand backprop - karpathy
- see DL with Python from Chollet
- Alice's Adventures in a differentiable wonderland
- Learn how the NN architectures work and why they work. What is an encoder-decoder? Why the first part produces an embedding? How a transformer works?
- Distributed Training :: multicore programming + distributed systems :: notes/chats/ChatGPT-⌨️.md
October 2026
162/180 credits🎓