mlabonne/llm-course

LLM Course is a free, self-paced course that teaches how to work with Large Language Models, the kind of AI behind ChatGPT and similar tools. It is not a piece of software you install but a learning resource: the repository is mostly markdown roadmaps, links to articles, and Google Colab notebooks you can open in your browser and run without setting anything up locally. The course is split into three tracks. The first, called LLM Fundamentals, is optional and covers the background, the mathematics, the Python, and the basics of neural networks, that the later tracks assume. The second, The LLM Scientist, focuses on actually building the best possible language models using current techniques. The third, The LLM Engineer, focuses on the practical side: taking an existing model and turning it into an application you can deploy. Each track is laid out as a roadmap with notebooks attached so the theory comes with runnable examples. Alongside the roadmaps, the repository hosts a library of notebooks for specific tasks: fine-tuning models like Llama, Mistral, and CodeLlama using methods such as QLoRA, ORPO, DPO, and Axolotl; quantising models with GPTQ, GGUF and ExLlamaV2 so they run on smaller hardware; merging models with MergeKit; and automating evaluation. There are also notebooks for building a chat interface with Gradio, deduplicating datasets, and other practical chores. Someone would use this course to move from curious about LLMs to actually training, modifying, and shipping one. The author also co-wrote a paid book, the LLM Engineer's Handbook, that covers the same ground end-to-end. The full README is longer than what was provided.