AI Engineering
Roadmap
The structured path from zero to production-ready AI
Curated free resources · hands-on projects · milestones at every phase
Not just links
Topics, projects & milestones — not a bookmark list.
Built for developers
No math papers. Ship AI products from day one.
Track progress
Check off topics. Saved in your browser forever.
Also inside this tool
Prep Plan
Already know some AI basics?
A focused 6-week sprint to go from zero to building your first AI app — faster than the full roadmap.
Prompt Eng
Starting Phase 3?
Master techniques, templates, and a 6-week plan to become genuinely good at prompting — the skill every AI app depends on.
GenAI Guide
Curious how AI actually works?
A deep dive into text, code, image, and audio AI — how each domain works under the hood, with tools to explore.
Readiness Check
About to move phases?
Before moving on, check the green flags and move-on rules to make sure you're actually ready — not just rushed.
Books & Courses
Want to go deeper?
The best books and paid/free courses mapped to each phase — for when the free resources aren't enough.
Assessment
Planning your journey?
See exactly where you'll stand as an AI engineer after completing the roadmap — what roles you'll be ready for.
Beyond Roadmap
Finished the roadmap?
What to learn next, what gaps remain, and what projects will take you from competent to expert.
Check off topics
Click any topic in the Learn tab to track your progress. It's saved in your browser.
Explore tabs per phase
Each phase has Learn, Resources, and Project tabs — the project tells you what to build.
More sections above
Use the top navigation to explore Alt Resources, Knowledge Gaps, and Prompt Engineering guides.
Understand how AI/ML works conceptually. No heavy math — just intuition and vocabulary.
- Click any topic to check it off and track your progress
- What is AI, ML, Deep Learning, and GenAI — and how they relate
- Neural networks: inputs, weights, layers, outputs
- How models learn (gradient descent, loss functions)
- What LLMs are and how they generate text
- Key terms: tokens, embeddings, parameters, inference
You have a local LLM running and can call multiple LLM APIs from code.
You have a working AI-powered app you built yourself using an LLM API.
You can build a RAG pipeline from scratch and evaluate its quality.
You understand agentic design patterns and have built a working multi-step agent.
You can fine-tune an open-source model, understand what happened under the hood, and evaluate the result.
You have shipped 2–3 real AI projects and can discuss AI topics with genuine depth.
Essential Free Tools
Principles for the Journey
Help make this better
This roadmap is community-driven. If you spot something outdated, missing, or wrong — please say so.
Click each phase to expand · Use tabs to navigate sections