School S07 · F02
AI Engineering
The intelligence layer of modern software.
Trains engineers to embed AI deep into products — RAG, tool use, evals, memory, guardrails and cost control. Not model research; production AI.
Learning outcomes
What graduates can do.
- 01Design retrieval, memory and tool-use architectures
- 02Build robust evals and regression suites for AI features
- 03Guardrail LLM systems for safety and cost
- 04Ship AI features that survive real user traffic
Curriculum
10 courses.
Delivered as a portfolio-based sequence. Every course culminates in shipped work reviewed by working practitioners.
- 01The Modern AI Stack
- 02Prompting & Structured Output
- 03Retrieval-Augmented Generation (RAG)
- 04Vector Databases & Hybrid Search
- 05Tool Use, Function Calling & Agents
- 06Long-Term Memory Architectures
- 07Evals, Golden Sets & LLM-as-Judge
- 08Guardrails, Safety & Content Policy
- 09Cost, Latency & Model Routing
- 10Capstone: Ship an AI Feature to Production
Tools & technologies
OpenAIAnthropicGeminiPineconeLangSmithBraintrustVercel AI SDK
Career tracks
- AI Engineer
- Applied AI Lead
- AI Product Engineer
Featured programs
Flagship programs anchored in this school.
Other schools in this faculty