The AI Learning Roadmap
I Actually Followed

Not generic Python tutorials — this one is built specifically for AI workflows. APIs, loops, functions, data handling. The most practical beginner resource out there if you want to actually build with AI.

Probably the clearest high-level explanation of how ChatGPT-like systems actually work. Training. Inference. Tool use. Agents. Multimodal. Everything finally started connecting after watching this once.

This one changed how I think about LLMs entirely. Models become much more useful once they can access external knowledge properly. Embeddings. Retrieval. Chunking. Evaluation. A lot of real AI engineering lives here.

AI is moving from "generate text" to "take actions." This crash course covers exactly how MCP works for Python developers — using tools, browsers, IDEs, databases. Actually operating inside systems.

Complete beginner-to-pro course on AI Agents. Covers how agents reason, plan, and use tools to complete multi-step tasks autonomously. The most accessible full walkthrough available right now.

Anyone can make an agent work once. The real challenge is making it reliable consistently. This talk covers evaluation pipelines, why most agent benchmarks are broken, and what real reliability looks like in production.