Top AI Repos — open-source AI, indexed and scored
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Learn it. Build it. Ship it for others.
| Date | Stars |
|---|---|
| 2026-07-24 | 43116 |
| 2026-07-25 | 43323 |
| 2026-07-28 | 44610 |
| 2026-07-30 | 44610 |
| 2026-08-06 | 44610 |
Today
— stars today
This week
— stars this week
This month
— stars this month
Momentum
35.0
growth rate 0.00%/day
<p align="center">
<img src="assets/banner.svg" alt="AI Engineering from Scratch — reference manual banner" width="100%">
</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-503-3553ff?style=flat-square&labelColor=fafaf5" alt="503 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.
```
░░░▒▒▒░░░▒▒▒░░░▒▒▒░░░▒▒▒░░░▒▒▒░░░▒▒▒░░░▒▒▒░░░▒▒▒░░░▒▒▒░░░▒▒▒░░░▒▒▒░░░▒▒▒░░░▒▒▒░░░▒▒▒░░░▒▒▒
```
> **84% of students already use AI tools. Only 18% feel prepared to use them
> professionally.** This curriculum closes that gap.
>
> 503 lessons. 20 phases. ~320 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>150,639</b> readers · <b>241,669</b> page views in the last 30 days · as of 2026-06-07</sub></p>
<!-- STATS:END -->
## 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.
```
░░░▒▒▒░░░▒▒▒░░░▒▒▒░░░▒▒▒░░░▒▒▒░░░▒▒▒░░░▒▒▒░░░▒▒▒░░░▒▒▒░░░▒▒▒░░░▒▒▒░░░▒▒▒░░░▒▒▒░░░▒▒▒░░░▒▒▒
```
## The shape of the curriculum
Twenty phases stack on top of each other. Math is the floor. Agents and production are the roof.
Skip ahead if you already know the lower layers, but don't skip and then wonder why something at
the top is breaking.
```mermaid
%%{init: {'theme':'base','themeVariables':{'primaryColor':'#fafaf5','primaryTextColor':'#1a1a1a','primaryBorderColor':'#3553ff','lineColor':'#3553ff','fontFamily':'JetBrains Mono','fontSize':'12px'}}}%%
flowchart TB
P0["Phase 0 — Setup & Tooling"] --> P1["Phase 1 — Math Foundations"]
P1 --> P2["Phase 2 — ML Fundamentals"]
P2 --> P3["Phase 3 — Deep Learning Core"]
P3 --> P4["Phase 4 — Vision"]
P3 --> P5["Phase 5 — NLP"]
P3 --> P6["Phase 6 — Speech & Audio"]
P3 --> P9["Phase 9 — RL"]
P5 --> P7["Phase 7 — Transformers"]
P7 --> P8["Phase 8 — GenAI"]
P7 --> P10["Phase 10 — LLMs from Scratch"]
P10 --> P11["Phase 11 — LLM EngineExcerpt of 90,785 characters
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Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:4586d38d266a0fef, topic:tutorial, topic:course, readme:roadmap
matched fp:4586d38d266a0fef, topic:nlp, readme:tokenizer
matched fp:4586d38d266a0fef, topic:ai-agents, topic:agents
matched fp:4586d38d266a0fef, topic:mcp, readme:mcp server