#3434th of 41 in Learning and cookbooks
nlp_course
University NLP course with lecture and notebook homework, from embeddings to agents
- Stars
- 10.7k
- License
- MIT
- Last commit
- Oct 2026
- Language
- Jupyter Notebook
10,439 on 31 Mar 202610,742 on 20 Oct 2026
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Checked on GitHub.
Overview
Course materials for the YSDA Natural Language Processing course, 2025 edition, organized as 14 weekly folders. Topics run from word embeddings, language models and attention to transfer learning, LLMs, prompting, PEFT/RLHF, efficiency, RAG, agents and interpretability. Each week has lecture notes, seminars and homework, mostly in Jupyter Notebook.
Who it is for: Students and engineers learning NLP and LLMs through notebooks
Strengths
- Covers classic NLP and current LLM topics (RAG, agents, PEFT, quantization) in one syllabus
- Seminar and homework notebooks for most weeks
- Links to interactive lecture materials by Elena Voita for weeks 1 to 4
- MIT license, with an issue thread for installation troubleshooting
Weaknesses
- Weeks 12 to 14 list only titles in the README, no content described
- Materials are added as prepared, so some weeks may be incomplete
- No hardware or RAM requirements stated for the notebooks
- No release or packaged environment; setup is left to the reader
What it needs
- Models: BERT, open-source LLMs
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