Stanford University · on YouTube
Stanford's seminar series where leading researchers present the latest on transformers, LLMs, world models, state-space models, multimodal systems, and production inference. For practitioners and researchers who want to follow frontier work straight from the people doing it.
Developers and technically curious learners. This is an advanced course in Generative AI & LLMs, running about Weekly seminar, Spring quarter (recordings available).
Free. Open to the public via Zoom livestream and recorded lectures; no enrollment or certificate for non-Stanford learners.
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.
Scrimba's interactive career path for building AI-powered apps in JavaScript, covering LLM APIs, embeddings and RAG, and agents, with code you edit directly inside the screencasts. It suits web developers who want a guided, hands-on route into AI engineering at a low monthly cost rather than assembling free resources themselves.
Google Cloud's short beginner path explaining what generative AI and large language models are, how they work, and the principles of responsible AI. A fast, free badge-earning starting point for non-technical professionals before moving to Google's deeper developer paths.