Building and Evaluating AI Products

3 credits · Graduate

A project-based course on building AI products and agents end-to-end. Students build a real product over the quarter, justifying AI fit, navigating latency, quality, and cost trade-offs, and rigorously evaluating their own system. The course moves from an individual mechanics phase into a team build, ending in a Demo Day. Enrolled students complete a self-paced pre-course module covering git basics, AI coding tool fluency (Cursor, Claude Code, or Antigravity), eval framework basics, and API setup. Designed primarily for upper-division undergraduates and master's students, with target majors including MS&E, CS, Symbolic Systems, and EE; open to all Stanford students. Enrollment is capped at 12 teams of 4 students (48 students total).