Stanford's free CME295 course: 9 lectures, 16+ hours covering the full modern LLM stack
mdancho84 · x · 2026-11-09
Matt Dancho highlights Stanford's free online course CME 295: Transformers & Large Language Models (9 lectures, 16+ hours, 430K+ views on Stanford Online), arguing that aspiring AI engineers should understand how LLMs actually work before chasing RAG and agent frameworks.
The curriculum covers:
- Transformers: tokenization, embeddings, attention
- Architectures: MHA, GQA, RoPE, BERT
- LLMs: MoE, prompting, context windows, chain-of-thought
- Training: pretraining, distributed training, quantization, LoRA
- Post-training: SFT, RLHF, PPO, DPO
- Reasoning: reasoning models, GRPO, inference-time scaling
- Agents: RAG, advanced retrieval, function calling
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