Guided learning paths for building, observing, and governing AI systems.

How the learning material is organized and who each path is for.

AI Engineer, Researcher, System Architect, Enterprise Developer, and Contributor paths.

Read the core ideas, run the sample notebook, observe one RAG workflow.

The full mental model — AI Kernel, observability, probes, evaluation, profiling — end to end.

Recorded walkthroughs for platform concepts that read better as video.

Runnable in-browser notebooks (uses the /playground runner).

Small, self-contained AI engineering problems with expected outputs.

Short concept checks between chapters.

AI Engineering platform assessment and issued certificate.

End-to-end multi-agent & RAG projects to reinforce a full learning path.