🎓 Stanford has released a new course: “Transformers & Large Language Models”

The authors are the Amidi brothers, and three free lectures are already available on YouTube. This is probably one of the most systematic introductory courses on modern LLMs.

Course content:

• Transformers: tokenization, embeddings, attention, architecture
• #LLM basics: Mixture of Experts, decoding types
• Training and fine-tuning: SFT, RL, LoRA
• Model evaluation: LLM/VLM-as-a-judge, best practices
• Tricks: RoPE, attention approximations, quantization
• Reasoning: scaling during training and inference
• Agentic approaches: #RAG, tool calling

If you are already familiar with this topic — it’s a great opportunity to refresh your knowledge and try implementing some techniques from scratch.

https://cme295.stanford.edu/syllabus/

https://t.iss.one/CodeProgrammer 🌟

🖥 Microsoft has introduced a new lecture series on Python and artificial intelligence.

The course gathers up-to-date information on #Python programming and creating advanced AI assistants based on it.

• Content: The course includes 9 lectures, supplemented with video materials, detailed presentations, and code examples. Learning to develop AI agents is accessible even for coding beginners.
• Topics: The lectures cover topics such as #RAG (Retrieval-Augmented Generation), embeddings, #agents, and the #MCP protocol.

The perfect weekend plan is to dive deep into #AI!

https://github.com/orgs/azure-ai-foundry/discussions/166

https://t.iss.one/CodeProgrammer