rohitg00 / ai-engineering-from-scratch

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_{Translated landing pages, committed to the repo. English is canonical; lesson pages are machine-translated on the translations branch. See docs/i18n.md.}

From the creator of Agent Memory - #1 Persistent memory ⭐ which naturally works with any agents or chat assistants.

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84% of students already use AI tools. Only 18% feel prepared to use them professionally. This curriculum closes that gap.

511 lessons. 20 phases. ~329 hours. Python, TypeScript, Rust, Julia. Every lesson ships a reusable artifact: a prompt, a skill, an agent, an MCP server. Free, open source, MIT.

You don't just learn AI. You build it. End-to-end. By hand.

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Start here: choose what you want to build

You do not need to scan 511 lessons before beginning. Pick one goal. Each link opens the same curriculum on GitHub or the website, and both versions use the same lesson code.

Your goal	Learn on GitHub	Learn on the website
I am new and want the complete foundation	Phase 0: Setup and Tooling	Dev Environment
I know Python and want math plus ML foundations	Phase 1: Math Foundations	Linear Algebra Intuition
I want to build production LLM applications	Phase 11: LLM Engineering	Prompt Engineering
I want to build agents	Phase 14: Agent Engineering	The Agent Loop
I want to build with Model Context Protocol (MCP)	Model Context Protocol (MCP) route	Model Context Protocol (MCP) path
I want to write and ship Agent Skills	Focused Agent Skills route	Agent Skills path
I want to prepare for a Claude certification	Certification onboarding	Certification Academy

Not sure where you fit? Use the start-learning placement tutor or the website prerequisites guide.

Use every lesson the same way

1. Read docs/en.md and explain the core idea in your own words.
2. Type and build the important code instead of treating the code block as decoration.
3. Run the lesson command from the repository root, the directory containing README.md and phases/.
4. Keep evidence: the command, working directory, exit code, meaningful output, and the artifact you changed or produced.
5. Continue only when you can explain the output and make one small change without guessing.

Commands in lesson pages are paths from the repository root unless the lesson explicitly says to change directories. If a lesson offers several languages, run the implementation for the language you are learning.

Clone it and produce your first evidence

git clone https://github.com/rohitg00/ai-engineering-from-scratch.git
cd ai-engineering-from-scratch
python3 phases/00-setup-and-tooling/01-dev-environment/code/verify.py --route beginner
python3 phases/01-math-foundations/01-linear-algebra-intuition/code/vectors.py

The preflight separates requirements needed now from tools needed later. Every required failure includes the detected reason and a corrective command. The second command is a dependency-free lesson and ends by showing that a matrix times a vector is the operation inside a neural network layer. Save that terminal output as your first evidence.

Add the AI tutor in 30 seconds

If Node.js, npx, and a skill-capable coding agent are already installed, your coding agent can become your tutor in two commands. A repository clone is not needed to install or read the tutor. Runnable focused-path labs need python3. Agent Skills host labs also need a selected host and a writable user or project skill scope.

Check the local requirements first:

node --version
npx --version
python3 --version

Then install the curriculum skills and choose the host and scope you intend to use when the installer asks:

npx skills add rohitg00/ai-engineering-from-scratch

Invocation syntax belongs to the host, not to the portable SKILL.md format:

Host	Start the course	Start Model Context Protocol (MCP)	Start Agent Skills	Run a phase quiz
Codex	start-learning, or choose it from /skills	learn-mcp, or choose it from /skills	learn-agent-skills, or choose it from /skills	check-understanding 13, or choose it from /skills
Claude Code	/start-learning	/learn-mcp	/learn-agent-skills	/check-understanding 13
Other compatible hosts	Use start-learning to begin the course.	Use learn-mcp to start the Model Context Protocol (MCP) path.	Use learn-agent-skills to start the Agent Skills Engineering path.	Use check-understanding to quiz me on Phase 13.

A ten-question placement quiz maps what you alre