Parlance Labs (Hamel Husain and collaborators) · on Parlance Labs
A free library of practitioner talks and workshops from Hamel Husain's network, covering LLM evaluation, RAG fundamentals and systematic RAG improvement, building and deploying LLM apps, and a deep track on when and how to fine-tune. It suits engineers who already ship LLM features and want battle-tested advice on evals and reliability from people widely followed on X.
Developers and technically curious learners. This is an intermediate course in Generative AI & LLMs, running about 27 talks and workshops.
Free. All talks and workshops on the page are free to watch; Parlance Labs links separately to a paid Maven course. Price seen 2026-11-01.
A large catalogue of runnable notebooks, each isolating one retrieval-augmented generation technique, from basic chunking and query transformations to reranking, hierarchical and graph-based retrieval, and evaluation. It suits developers who have built a basic RAG app and want to systematically try the techniques that improve retrieval quality.
Covers the full LLM lifecycle from transformer architecture and pre-training through instruction fine-tuning, RLHF, and deployment, taught by DeepLearning.AI and AWS engineers. The right course for Python developers with basic ML who want to understand how LLMs are actually built and adapted.
Hugging Face's hands-on course on LLMs and NLP using the Transformers, Datasets, Tokenizers, and Accelerate libraries, from fundamentals through fine-tuning, demos, and reasoning models. Best for Python developers who want to work with open models directly rather than only via APIs.