https://stanford-cs324.github.io/winter2022/
https://harvard-ml-courses.github.io/cs287-web/
https://stanford-cs336.github.io/spring2025/
https://www.youtube.com/watch?v=seEv0xrt56c&list=PLzIZxnJJT7ORSBnYrXJMYBVnYeLryJtl7
https://www.youtube.com/playlist?list=PLzIZxnJJT7ORSBnYrXJMYBVnYeLryJtl7
ETH Zürich: Course catalog
Large language models have become one of the most commonly deployed NLP inventions. In the past half-decade, their integration into core natural language processing tools has dramatically increased the performance of such tools, and they have entered the public discourse surrounding artificial intelligence. In this course, we offer a self-contained introduction to language modeling and its applications. We start with the probabilistic foundations of language models, i.e., covering what constitutes a language model from a formal, theoretical perspective. We then discuss how to construct and curate training corpora, and introduce many of the neural-network architectures often used to instantiate language models at scale. The course covers aspects of systems programming, discussion of privacy and harms, as well as applications of language models in NLP and beyond.