For experienced developers & software engineers moving into AI engineering
AI Engineering
8 weeks
1 live class / week
Don’t just prompt AI. Build with it. Learn to build production-style AI applications—from retrieval and RAG to tool-using agents—then evaluate, debug, and improve them with the judgment of an AI engineer.
Try 2 free classes
What will you learn in the AI Engineering course?
You’ll build the systems behind modern AI applications—not just learn the vocabulary. Starting from LLM APIs and structured outputs, you’ll work through embeddings, chunking, vector search, RAG, evaluation, tool use, agentic workflows, memory/state, observability, and deployment.
Hands-on experimentation is central: build components, intentionally stress or break them, inspect failure modes, and improve the system. You’ll also use AI coding tools as force multipliers—because AI can increasingly generate the code; an AI engineer needs to know whether the resulting system is actually good.
Who it’s for
Software engineers and backend developers comfortable with Python who want to move into LLM-powered systems.
Developers who have built AI prototypes and want to understand retrieval, evaluation, agents, reliability, observability, and engineering tradeoffs.
Experienced builders who want a portfolio project they can defend technically—what they built, why, how it failed, and how they improved it.
Advanced, builder-focused course: comfort with Python and core backend/software engineering concepts is expected.
Core Stack
Python
LLM APIs & Structured Outputs
Embeddings / Vector Databases
Retrieval & RAG
Evaluation / Observability
Tool Calling & Agentic Workflows
Serving / Deployment
Frameworks
OpenAI/Anthropic SDKs
LangChain/LangGraph
LangSmith
ChromaDB/Pinecone
FastAPI
Redis
AI Coding Agents
When you finish
Build and explain an end-to-end LLM application spanning retrieval, generation, tools/agents, evaluation, and serving.
Diagnose failures across model, retrieval, orchestration, state, and infrastructure—and improve the component actually limiting quality.
Evaluate retrieval and agent behavior using test sets, traces, quality checks, latency/cost measurements, and failure testing.
Leave with a production-style capstone and a portfolio/interview story you can defend technically.
Next Cohorts
November 4
Tuesday — 9:00 p. m. to 11:00 p. m. (Eastern Time)
🔥
January 13, 2027
Wednesday — 9:00 p. m. to 11:00 p. m. (Eastern Time)
FAQ
How does the refund through class 2 work?
Is the AI teaching the course?
How much time does it take per week?
Do I need experience to join?
What if I can’t make a live class?
When do cohorts start, and when does enrollment close?
Why learn AI Engineering when ChatGPT / Claude / Codex can write the app?