AI engineering roadmap

Learn by shipping, not collecting tutorials.

A personalized path from software foundations to production AI, with time estimates, prerequisites, practice tasks and proof-of-skill projects.

Progress

0%

Topics

0/23

Remaining

175h

At your pace

25 wk

Personalize your plan

AI application developer: Build useful LLM products, RAG systems and AI features. The full roadmap contains about 175 focused learning hours, excluding projects.

Best next action

Python for product development

Recommended for ai application developer. Spend about 8 hours, then complete the practice task and save the proof.

Your AI engineering path

Select a node to open its lesson plan. Follow the connections from foundations to production.

Completed Recommended To learn23 topics shown
82%
Stage 01

Software foundations

Write, test and connect the code every AI product depends on.

0/4 complete0%
Stage 02

Machine learning essentials

Learn enough ML to evaluate models and make sound product decisions.

0/4 complete0%
Stage 03

LLM application development

Move from impressive demos to controlled, testable AI features.

0/5 complete0%
Stage 04

RAG, tools and agents

Connect models to knowledge and actions without losing control.

0/5 complete0%
Stage 05

Production AI engineering

Ship systems that remain secure, observable and affordable after launch.

0/5 complete0%
Scroll vertically to move through every stage. Drag the horizontal scrollbar on smaller screens.
Skill coverage
Software0%
ML & data0%
LLM systems0%
Agents0%
Production0%

Practice deliberately

Test knowledge, then build something real.

Use quizzes to find weak concepts and the practical AI course for deeper guided exercises.