The Large Language Model Course

The Large Language Model (LLM) course offers a comprehensive framework for those interested in the development and application of LLMs, featuring two primary educational tracks: the LLM Scientist and the LLM Engineer. The LLM Scientist track focuses on building optimal LLMs using advanced techniques, discussing topics such as model architecture, pre-training, post-training datasets, supervised fine-tuning, preference alignment, evaluation, quantization, and emerging trends. Meanwhile, the LLM Engineer track emphasizes creating and deploying LLM-based applications, covering aspects like running LLMs, building vector storage, retrieval augmented generation (RAG), inference optimization, deployment strategies, and securing LLMs. The course is designed to remain freely accessible, supplemented by a detailed LLM Engineer's Handbook co-authored by Maxime Labonne and Paul Iuzstin, offering practical insights for building end-to-end LLM applications. Additionally, interactive learning is facilitated through an LLM assistant available on platforms like HuggingChat and ChatGPT, allowing users to test their knowledge in a personalized manner.