Stanford CME 295 Lecture 4 public video and lecture notes
Stanford course CME 295 Transformers & Large Language Models has been updated to Lecture 4, with both the video and lecture notes now publicly available. The topic of this lecture is Reinforcement learning with LLMs, covering everything from reinforcement learning and reward design to PPO, GRPO, RLVR, and DAPO, explaining each of the notations one by one. The course is taught by Afshine and Shervine Amidi, with 9 lectures in total, covering the Transformer architecture, attention variants, RoPE, LoRA fine-tuning, RLHF/GRPO training, Flash Attention inference optimization, MCP and AI Agents, and diffusion language models. Currently, Lecture 4 is public, and no evidence of updates for subsequent lectures has been seen yet.
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