The Path
Where to start, and what depends on what
Lessons are grouped into tracks and ordered by prerequisite. You don't have to go in order — every lesson is standalone — but if you want a route, here's the map.
Where to start
- Zero prior AI experience
- Read straight through Stage 0 → 6. Skip nothing on the first pass. If a maths or Python reference loses you, hop to /foundations for a pointer, then come back — the roadmap assumes only the shape of the reference, not fluency in it.
- Working software engineer
- Skim Stage 0 (mostly familiar) and Stage 1 (mostly familiar API mechanics with LLM quirks). Start reading in earnest at Stage 2. Stage 5 (Production Reality) is likely where the roadmap adds the most new material.
- Data scientist / ML practitioner
- You know the models. The gap is shipping. Skip to Stage 2 (tools) and Stage 5 (production) — evals, guardrails, observability, cost — then loop back to Stage 3 (RAG) if retrieval is new to you.
Missing the fundamentals a lesson assumes? Start with Foundations →