学习它。构建它。为他人交付它。
📖 README
[代码块]> 84% of students already use AI tools. Only 18% feel prepared to use them
> professionally. This curriculum closes that gap.
>
> 435 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.How this worksMost 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, 435 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 ...
📊 项目信息
- 语言
- Python
- Stars
- ⭐ 10,691
- Forks
- 2,118
- 今日新增
- +1,333
- 排名
- #9
- 收录
- 总榜
- 趋势日期
- 2026年5月21日
- 最后推送
- 2026/5/21
🏷️ 标签
agentsaiai-agentsai-engineeringcomputer-visioncoursedeep-learningfrom-scratchgenerative-aillmmachine-learningmcpnlppythonreinforcement-learningrustswarm-intelligencetransformerstutorialtypescript