# Large Language Models

### Guides

* [Generative AI Handbook: A Roadmap for Learning Resources](https://genai-handbook.github.io)

### Foundations

* [Stanford CS224N Natural Language Processing with Deep Learning](https://web.stanford.edu/class/cs224n/)
* [李宏毅 - 生成式人工智能导论](https://speech.ee.ntu.edu.tw/~hylee/genai/2024-spring.php)

### General Courses

* [Princeton CS597 Understanding Large Language Models](https://www.cs.princeton.edu/courses/archive/fall22/cos597G/)
* [Stanford CS324 Advances in Foundation Models](https://stanford-cs324.github.io/winter2023/)
* [CMU 11-711 Advanced Natural Language Processing](https://www.youtube.com/playlist?list=PL8PYTP1V4I8DZprnWryM4nR8IZl1ZXDjg)
* [Samuel Albanie - Foundation Models](https://samuelalbanie.com/teaching/2022-foundation-models)

### Hands-on Courses

* [Stanford CS336 Language Modeling from Scratch](https://stanford-cs336.github.io/spring2024/index.html#schedule)
* [Maxime Labonne - LLM Hands-on Course](https://github.com/mlabonne/llm-course)
* [Umar Jamil's Youtube Channel](https://www.youtube.com/@umarjamilai/videos)
* [LangChain's Youtube Channel](https://www.youtube.com/@LangChain/playlists)
* [Deeplearning.ai Courses](https://www.deeplearning.ai/courses/)

### Fontier Topics

* [Stanford CS25 Transformers United](https://web.stanford.edu/class/cs25/)&#x20;
* [UCB CS294 Large Language Model Agents](https://rdi.berkeley.edu/llm-agents/f24)
* [UCB CS294 Advanced Large Language Model Agents](https://rdi.berkeley.edu/adv-llm-agents/sp25)
* [RLHF Book by Nathan Lambert](https://rlhfbook.com/)
* [Caltech CS159 Large Language Models for Reasoning](https://sites.google.com/view/cs-159-2024/home?authuser=0)
* [UWaterloo CS886 Recent Advances on Foundation Models](https://cs.uwaterloo.ca/~wenhuche/teaching/cs886/)
* [Anthropic LLM Courses: API Fundamentals / Prompt Engineering / Real World Prompting / Prompt Evaluations / Tool Use](https://github.com/anthropics/courses)
* [Reinforcement Learning from Human Feedback Handbook](https://rlhfbook.com/)
* [MIT Introduction to Data-Centric AI](https://dcai.csail.mit.edu/)
* [UW CSE599J Data-centric Machine Learning](https://koh.pw/cse599j/)
* [Alignment Guidebook](https://www.notion.so/Alignment-Guidebook-e5c64df77c0a4b528b7951e87337fa78)

### Collections & Blogs

* [Lilian Weng's Blog](https://lilianweng.github.io/posts/)
* [Andrej Karpathy's Blog](https://karpathy.ai/)
* [Chip Huyen's Blog](https://huyenchip.com/blog/)
* [Interconnects.ai](https://www.interconnects.ai/)
* [Sebastian Raschka's Blog](https://magazine.sebastianraschka.com/)
* [Maxime Labonne's Blog](https://mlabonne.github.io/blog/)
* [Jay Alammar's Blog](https://jalammar.github.io/)
* [The Gradient Substack](https://thegradientpub.substack.com/)
* [Deep (Learning) Focus Substack](https://cameronrwolfe.substack.com/)
* [Artificial Fintelligence Substack](https://www.artfintel.com/)
* [The TWIML AI Podcast with Sam Charrington](https://www.youtube.com/@twimlai/videos)
* [Huggingface's Blog](https://huggingface.co/blog)
* [OpenAI's Research Blog](https://openai.com/research/)
* [Meta AI Blog](https://ai.meta.com/blog/)
* [Google DeepMind's Blog](https://deepmind.google/research/publications/)
* [Awesome-LLM - A Curated List of Large Language Model](https://github.com/Hannibal046/Awesome-LLM)

