About the Instructor
Stanford Faculty & Guest Lecturers
CS25 is Stanford's seminar series on Transformers, featuring lectures from researchers at Stanford, Google, Hugging Face, OpenAI, and DeepMind. Each session is taught by the practitioners who built the systems.
First Principles
Transformers scale. More data, more parameters = smarter models. Scaling laws show the relationship between compute and capability.
AI Ecosystem Fit
Layer 3 (Cloud) ↔ Layer 4 (Models) bridge. Training large transformers requires GPUs, infrastructure, and data.
Prerequisites
What Paid Projects This Unlocks
Build foundation models and agentic systems: understand scaling laws, multi-head attention, fine-tuning transformer-based agents.
3 Client Projects You Can Get Paid For
Real businesses have this problem right now. Build it, pitch it, charge for it.
Stack This With → (Unlocks Higher-Paying Projects)
Optimize models for cost/performance tradeoffs
Deploy on AWS with SageMaker
Train custom models for your domain
Why This Matters
Not essential for building agents with off-the-shelf models, but critical if you want to fine-tune or deploy specialized models at scale.