How This Course Is Organized
Ten modules, taken in a deliberate order. The general skills come first — so you can plan and direct the work — and then the six application sub-skills go deep. Here is the shape of the whole journey.
General Skills First
Before building AI features, you need to be able to plan, direct, and shape the work. Three modules give you that footing.
- M2 — Software Engineering Fundamentals: enough software literacy to plan well.
- M3 — Using Coding Agents: fluency directing an AI that writes the code.
- M4 — Shaping the Build: the skill of deciding and speccing what to build.
Then the Six Sub-Skills
The heart of the course — six modules, one per application sub-skill of building and deploying AI.
- LLM Foundations · Grounding Models with Data
- Building Agentic Systems · Evaluation-Driven Development
- Operating in Production · Machine Learning Foundations
What Done Looks Like
By the end you can spec, build, ground, evaluate, and operate a small AI tool of your own — end to end.
The Two Capstones
You choose one project to build across the modules. Both exercise the same skills from different angles.
Build It
How to implement: pick which capstone you will build and write one sentence describing the finished tool. Keep it — you will turn it into a real spec in Module 4.
- Weekly AI Tasks tracker — assemble it from M2 (a small web app), M3/M4 (build it with an agent), M5–M7 (LLM + RAG + an agent that reads messages), M8/M9 (evals + operations).
- Personal brand site — M2 (a static site), M3/M4 (spec + build), M5/M6 (ground copy in real material), M8 (fact-check every claim).
What you learned
General skills come first (Modules 2–4), then the six application sub-skills (Modules 5–10). Every lesson feeds one of two capstones — a Weekly AI Tasks tracker or a Personal brand site — and by the end you can spec, build, ground, evaluate, and operate a small AI tool.