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ai-engineering-from-scratch

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Learn it. Build it. Ship it for others.

MCP Servers54.3k stars9.5k forksPythonMITUpdated 4d ago
Editor's note

AI Engineering from Scratch is a structured, self-paced curriculum covering 503 lessons across 20 phases, spanning roughly 320 hours of study and hands-on work in Python, TypeScript, Rust, and Julia. The curriculum runs from linear algebra and backpropagation through transformers, generative AI, and LLM engineering, culminating in agent engineering, multi-agent swarms, and production infrastructure. Each lesson follows a fixed six-step loop: motto, problem statement, conceptual explanation, from-scratch implementation in raw math, reproduction using a production library such as PyTorch or scikit-learn, and a shipped artifact such as a prompt, skill, agent, or MCP server. The MCP server outputs connect directly to Claude and other assistants via the Model Context Protocol, and the curriculum dedicates a full phase (Phase 13) to tools and protocols including MCP. A standout structural detail is that every lesson folder ships a reusable output under an outputs directory alongside runnable code and narrative docs. The course targets developers and students who already use AI tools but lack the foundational understanding to work with them professionally.

ClaudeWave Trust Score
100/100
Verified
Passed
  • Open-source license (MIT)
  • Actively maintained (<30d)
  • Healthy fork ratio
  • Clear description
  • Topics declared
  • Documented (README)
Last scanned: 9/12/2026
Install in Claude Code / Claude Desktop
Method: NPX · --version
Claude Code CLI
claude mcp add ai-engineering-from-scratch -- npx -y --version
claude_desktop_config.json (Claude Desktop)
{
  "mcpServers": {
    "ai-engineering-from-scratch": {
      "command": "npx",
      "args": ["-y", "--version"]
    }
  }
}
1. Run the command above in your terminal (Claude Code), or paste the JSON config into claude_desktop_config.json (Claude Desktop).
2. Replace any <placeholder> values with your API keys or paths.
3. Restart Claude. The MCP server and its tools appear automatically.
Use cases

MCP Servers overview

<p align="center">
  <img src="assets/banner.svg" alt="AI Engineering from Scratch — reference manual banner" width="100%">
</p>

<p align="center">
  <b>Read in your language:</b>
  <a href="i18n/es/README.md">Español</a> ·
  <a href="i18n/fr/README.md">Français</a> ·
  <a href="i18n/pt/README.md">Português</a> ·
  <a href="i18n/de/README.md">Deutsch</a> ·
  <a href="i18n/it/README.md">Italiano</a> ·
  <a href="i18n/zh/README.md">简体中文</a> ·
  <a href="i18n/ja/README.md">日本語</a> ·
  <a href="i18n/ko/README.md">한국어</a> ·
  <a href="i18n/hi/README.md">हिन्दी</a> ·
  <a href="i18n/ar/README.md">العربية</a> ·
  <a href="i18n/ru/README.md">Русский</a> ·
  <a href="i18n/tr/README.md">Türkçe</a>
  <br><sub>Translated landing pages, committed to the repo. English is canonical; lesson pages are machine-translated on the <code>translations</code> branch. See <a href="docs/i18n.md">docs/i18n.md</a>.</sub>
</p>

<p align="center">
  <a href="LICENSE"><img src="https://img.shields.io/badge/license-MIT-1a1a1a?style=flat-square&labelColor=fafaf5" alt="MIT License"></a>
  <a href="ROADMAP.md"><img src="https://img.shields.io/badge/lessons-523-3553ff?style=flat-square&labelColor=fafaf5" alt="523 lessons"></a>
  <a href="#contents"><img src="https://img.shields.io/badge/phases-20-3553ff?style=flat-square&labelColor=fafaf5" alt="20 phases"></a>
  <a href="https://github.com/rohitg00/ai-engineering-from-scratch/stargazers"><img src="https://img.shields.io/github/stars/rohitg00/ai-engineering-from-scratch?style=flat-square&labelColor=fafaf5&color=3553ff" alt="GitHub stars"></a>
  <a href="https://aiengineeringfromscratch.com"><img src="https://img.shields.io/badge/web-aiengineeringfromscratch.com-3553ff?style=flat-square&labelColor=fafaf5" alt="Website"></a>
</p>

## From the creator of [Agent Memory - #1 Persistent memory ⭐](https://github.com/rohitg00/agentmemory) <a href="https://github.com/rohitg00/agentmemory/stargazers"><img src="https://img.shields.io/github/stars/rohitg00/agentmemory?style=flat-square&labelColor=fafaf5&color=3553ff" alt="GitHub stars"></a> which naturally works with any agents or chat assistants.

```text
░░░▒▒▒░░░▒▒▒░░░▒▒▒░░░▒▒▒░░░▒▒▒░░░▒▒▒░░░▒▒▒░░░▒▒▒░░░▒▒▒░░░▒▒▒░░░▒▒▒░░░▒▒▒░░░▒▒▒░░░▒▒▒░░░▒▒▒
```

> **84% of students already use AI tools. Only 18% feel prepared to use them
> professionally.** This curriculum closes that gap.
>
> 523 lessons. 20 phases. ~342 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.

<!-- STATS:START (generated from site/stats.json by build.js — do not edit by hand) -->
<p align="center"><sub><b>114,584</b> readers &nbsp;·&nbsp; <b>181,995</b> page views in the last 30 days &nbsp;·&nbsp; as of 2026-08-29</sub></p>
<!-- STATS:END -->

## Start here: choose what you want to build

You do not need to scan 523 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](phases/00-setup-and-tooling/) | [Dev Environment](https://aiengineeringfromscratch.com/lesson?path=phases/00-setup-and-tooling/01-dev-environment) |
| I know Python and want math plus ML foundations | [Phase 1: Math Foundations](phases/01-math-foundations/) | [Linear Algebra Intuition](https://aiengineeringfromscratch.com/lesson?path=phases/01-math-foundations/01-linear-algebra-intuition) |
| I want to build production LLM applications | [Phase 11: LLM Engineering](phases/11-llm-engineering/) | [Prompt Engineering](https://aiengineeringfromscratch.com/lesson?path=phases/11-llm-engineering/01-prompt-engineering) |
| I want to build agents | [Phase 14: Agent Engineering](phases/14-agent-engineering/) | [The Agent Loop](https://aiengineeringfromscratch.com/lesson?path=phases/14-agent-engineering/01-the-agent-loop) |
| I want to use coding agents on real repositories | [Agent-Assisted Engineering path](learning-paths/using-coding-agents.json) | [Agent-Assisted Engineering](https://aiengineeringfromscratch.com/lesson?path=phases/14-agent-engineering/31-agent-workbench-why-models-fail&learningPath=using-coding-agents) |
| I want to shape the right build before implementation | [Product Judgment and Delivery path](learning-paths/shaping-the-build.json) | [Product Judgment and Delivery](https://aiengineeringfromscratch.com/lesson?path=phases/14-agent-engineering/47-outcomes-before-output&learningPath=shaping-the-build) |
| I want to build with Model Context Protocol (MCP) | [Model Context Protocol (MCP) route](phases/13-tools-and-protocols/README.md#model-context-protocol-mcp-path) | [Model Context Protocol (MCP) path](https://aiengineeringfromscratch.com/lesson?path=phases/13-tools-and-protocols/06-mcp-fundamentals&learningPath=model-context-protocol) |
| I want to write and ship Agent Skills | [Focused Agent Skills route](phases/13-tools-and-protocols/README.md#agent-skills-fast-path) | [Agent Skills path](https://aiengineeringfromscratch.com/lesson?path=phases/13-tools-and-protocols/22-skills-and-agent-sdks&learningPath=agent-skills) |
| I want to prepare for a Claude certification | [Certification onboarding](certifications/claude/GETTING_STARTED.md) | [Certification Academy](https://aiengineeringfromscratch.com/certifications.html) |

Not sure where you fit? Use the [`start-learning` placement tutor](skills/start-learning/SKILL.md)
or the [website prerequisites guide](https://aiengineeringfromscratch.com/prereqs.html).

Compare four core domains and six career routes in the [AI Engineering Learning Paths](https://aiengineeringfromscratch.com/learning-paths.html).

### Sponsors

<a href="https://serpapi.com/ai-engineering-from-scratch">
  <img align="left" src="assets/sponsors/serpapi-banner.png" alt="SerpApi. Web Search API for your AI apps. Available in Markdown and JSON for any integration." width="600">
</a>

<p><br><b>Thank you to our sponsors.</b></p>
<p>Your support keeps every lesson free and open source.</p>
<p>
  <a href="#supporters">See all supporters</a><br>
  <a href="SPONSORS.md">Become a sponsor</a>
  <br clear="all">
</p>

### 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

```bash
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:

```bash
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:

```bash
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 already know to a starting phase and
saves a personalized study plan to `LEARNING.md`. From there, the `learn` skill
teaches one lesson per session: concept, math, code, quiz. It streams lessons
straight from this repo, and the `course-guide` skill jumps you to the exact
lesson that covers anything you are stuck on. In Codex, invoke these skills with
`learn` and `course-guide`; in Claude Code, use `/learn` and `/course-guide`;
in other compatible hosts, ask to use the skill by name.

Only want Model Context Protocol (MCP)? Use the MCP invocation for your host. It creates
`MCP-LEARNING.md` and follows one 17-lesson route through stateless
requests, transports, bidirectional work, security, reliability, registry
governance, and conformance evidence. The exact order and checkpoints l
agentsaiai-agentsai-engineeringcomputer-visioncoursedeep-learningfrom-scratchgenerative-aillmmachine-learningmcpnlppythonreinforcement-learningrustswarm-intelligencetransformerstutorialtypescript

What people ask about ai-engineering-from-scratch

What is rohitg00/ai-engineering-from-scratch?

+

rohitg00/ai-engineering-from-scratch is mcp servers for the Claude AI ecosystem. Learn it. Build it. Ship it for others. It has 54.3k GitHub stars and its last recorded update is dated 2026-09-07.

How do I install ai-engineering-from-scratch?

+

You can install ai-engineering-from-scratch by cloning the repository (https://github.com/rohitg00/ai-engineering-from-scratch) or following the README instructions on GitHub. ClaudeWave also provides quick install blocks on this page.

Is rohitg00/ai-engineering-from-scratch safe to use?

+

Our security agent has analyzed rohitg00/ai-engineering-from-scratch and assigned a Trust Score of 100/100 (tier: Verified). See the full breakdown of passed checks and flags on this page.

Who maintains rohitg00/ai-engineering-from-scratch?

+

rohitg00/ai-engineering-from-scratch is maintained by rohitg00. The last recorded GitHub activity is dated 2026-09-07, with 113 open issues.

Are there alternatives to ai-engineering-from-scratch?

+

Yes. On ClaudeWave you can browse similar mcp servers at /categories/mcp, sorted by popularity or recent activity.

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