AI Mini-Courses¶
AI Engineering made simple, short, and useful.
A series of mini-courses from beginner to advanced to help you learn practical topics in modern AI engineering. Each course is short, easy to understand, and includes real-world examples, clear visuals, and extra reading materials.
Learning Path¶
| Category | Modules | Status | Description |
|---|---|---|---|
| Fundamentals | 1–7 | ✅ Ready | LLMs, training, RAG, tools, memory, agents, multi-agent systems. Start here. |
| Intermediate | 8–14 | 🚧 Draft | Prompt engineering, context engineering, coding agents, harness engineering, security, loop engineering, personal agents. |
| Expert | 15–23 | 🚧 Draft | Advanced UI, architectures, tools, memory, multi-agent, prompting, context engineering, harness engineering, deployment. |
| Ecosystem | 24–28 | 🚧 Draft | Agent frameworks, inference providers, inference engines, UI design, observability. |
| Protocols & Specs | 29 | 🚧 Draft | A single reference of every protocol and spec mentioned across the series. |
| Optional | 30–31 | 🚧 Draft | Human-in-the-loop and runtime topics that round out the series. |
How to Use¶
- Start with Fundamentals to learn must-know concepts in AI engineering.
- Move on to Intermediate and Ecosystem as they become ready.
- Take the Expert track to master advanced topics.
🚧 Draft categories are work in progress — content may be incomplete or change significantly.
Contributing¶
This is an open source project. Found a typo or want to improve a module? Open an issue or PR on GitHub.