Courses
Lecture series I follow on YouTube. Less rigorous than the books page - I won't pretend to take notes for all of these, so this is a resource gallery with a bit of commentary.
Currently watching
CMU 11-711: Advanced NLP
Graham Neubig's NLP course - solid coverage from classical NLP through modern LLM training and evaluation.
CMU 11-785: Introduction to Deep Learning (Fall 2025)
12 / 28 lectures
Bhiksha Raj's deep learning course at CMU. Math-heavy, end-to-end coverage from MLPs through transformers.
Plan to watch
ETH Zurich: Digital Design and Computer Architecture
From transistors and Boolean logic up to processor microarchitecture - the hardware story under everything else I work on.
Stanford CS336: Language Modeling from Scratch
Builds a language model end to end - data, tokenizer, architecture, training, eval, alignment. Lines up with the Raschka book on the bookshelf.