AI Engineering from Scratch
20 phases, 542 lessons, from math to agents to production.
Learn it. Build it. Ship it.
20 phases, 542 lessons, from math to agents to production. Every lesson has a video, code and a quiz.
Each phase builds on the previous. Start at Phase 0 or jump to any topic.
20 phases, 542 lessons, from math to agents to production.
Structured from foundations to advanced AI architectures.
Three simple steps to master AI engineering.
Clear, concise video explanations for every concept.
Real Python code repositories and reproducible scripts.
Auto-graded quizzes to test and solidify your knowledge.
Phase 0, Lesson 1: Introduction to AI Engineering.
In this introductory lesson, we establish our Python runtime, virtual environments, and essential developer tooling for building robust AI systems.
python3 -m venv .venv
source .venv/bin/activate
pip install torch transformers fastapi
Read the full lesson, no login needed
Senior AI Engineer & Open Source Author. Building production-grade AI systems and sharing the journey through open-source curricula.
Everything you need to know about the AI Engineering curriculum.
Yes. Every lesson, video, code repository, and quiz is completely free and public without any paywalls.
No. You can read every lesson and access all materials without logging in. Accounts are optional for tracking progress.
Basic familiarity with programming or Python is helpful, but the curriculum takes you from foundations to advanced deployment.
At 5 to 10 hours per phase, the complete curriculum spans roughly 3 to 6 months of dedicated study.
Yes, all code examples and repositories are fully open-source under the MIT license.
Created by Rohit Ghumare, MIT licensed curriculum for the open-source AI community.
Join engineers learning AI from the ground up. No paywalls, ever.