This is a great resource for anyone interested in working large language models #llms #machinelearning #deeplearning
If you’re serious about AI, this is worth your attention. Stanford has just released its course CME 295: Transformers & Large Language Models in full on YouTube. What stands out to me is the level of clarity and structure. This isn’t another surface-level overview. It’s the actual curriculum used to teach how modern AI systems work. This will help you move from using AI to understanding it. 📚 𝗧𝗼𝗽𝗶𝗰𝘀 𝗰𝗼𝘃𝗲𝗿𝗲𝗱 𝗶𝗻𝗰𝗹𝘂𝗱𝗲: • How Transformers actually work (tokenization, attention, embeddings) • Decoding strategies & MoEs • LLM finetuning (LoRA, RLHF, supervised) • Evaluation techniques (LLM-as-a-judge) • Optimization tricks (RoPE, quantization, approximations) • Reasoning & scaling • Agentic workflows (RAG, tool calling) 🎥 Watch these now: - Lecture 1: https://zurl.co/F0QR5 - Lecture 2: https://zurl.co/hG5lp - Lecture 3: https://zurl.co/PnKrW - Lecture 4: https://zurl.co/XCZoE - Lecture 5: https://zurl.co/GWlYI - Lecture 6: https://zurl.co/zGqqQ - Lecture 7: https://zurl.co/T06NM - Lecture 8: https://zurl.co/Un42q - Lecture 9: https://zurl.co/rR3YL For 2026, consider setting aside 2–3 hours each week to go through these lectures. If you’re working in AI whether on infrastructure, agents, or applications, this is a foundational resource worth your time. It’s a simple way to build depth where it matters most. #AI #LLMs #Transformers #Stanford #GenAI
