This is what learning AI should’ve looked like https://t.co/Z9XrOzu55G

AI Engineering from Scratch

Source: https://aiengineeringfromscratch.com/ FIG_000 · curriculum v1.0 · 2026open source · MIT

AI Engineering from Scratch

503 lessons. 20 phases. Every algorithm built from raw math before a single framework gets imported.

Maintained by Rohit Ghumare and contributors. Run on your own machine.

Star on GitHub…Follow @rohitg00

Your agent becomes your tutor: placement quiz, personalized path, lessons taught interactively in your terminal.

Read by engineers and students at

“Obsessed with the AI Engineering from Scratch repo.”— AI engineer at Google

How this works

Most AI material teaches in scattered pieces. A paper here, a fine-tuning post there, a flashy agent demo somewhere else. The pieces rarely line up. You ship a chatbot but can’t explain its loss curve. You hook a function to an agent but can’t say what attention does inside the model that’s calling it.

This curriculum is the spine. 20 phases, 503 lessons, four languages: Python, TypeScript, Rust, Julia. Linear algebra at one end, autonomous swarms at the other. Every algorithm gets built from raw math first. Backprop. Tokenizer. Attention. Agent loop. By the time PyTorch shows up, you already know what it’s doing under the hood.

Each lesson runs the same loop: read the problem, derive the math, write the code, run the test, keep the artifact. No five-minute videos, no copy-paste deploys, no hand-holding. Free, open source, and built to run on your own laptop.

Current Progress

Finished Lessons0 / 0

Phases0 / 0

Languages4

Glossary Terms···

Curriculum · 20 phases · 503 lessons

Tap a phase to expand its lessons. Each one ships when its math, code, and test are all written.

CompleteIn progressPlanned

The book edition · six volumes

The course, compiled. EPUB and PDF built from the same lessons and attached to every GitHub release. The site stays the living edition — every chapter links back here for the animated figures, quizzes, and code.

Independent certification preparation

Prepare by building the real systems

Four Claude certification paths taught the same way as the course: step by step, with interactive labs, practical artifacts, and an AI tutor that works from the GitHub repo.

4tracks33certification lessons295original practice questions

Not affiliated with, endorsed by, sponsored by, or authorized by Anthropic. This curriculum does not issue credentials or guarantee a passing result.

Colophon

The entire curriculum is on GitHub. Clone it, fork it, learn at your own pace. No paywall, no signup. Every lesson has runnable code in Python, TypeScript, Rust, or Julia, depending on what fits the concept best.

git clone https://github\.com/rohitg00/ai\-engineering\-from\-scratch\.git