The docs tell you what every endpoint does. They don't tell you which three endpoints you'll actually use, what the failure modes look like in production, or how tool use, RAG, and MCP compose into a working feature. This course is the second half of that story.
The API surface this course teaches (Messages, tool use, streaming, caching, MCP) is stable and versioned. Model names shift, the patterns don't. Lifetime access includes updates when they matter.
Six working programs in your own repo: a multi-turn chat app, an eval pipeline, a reminder-tool assistant, a hybrid RAG retriever, an MCP server and client pair, and a workflow-vs-agent reference design.
No. The course starts from your first API call and builds up. You should be comfortable with Python and REST APIs. No AI or ML background is required.
A multi-turn chat system, a prompt evaluation pipeline, a reminder-tool assistant, a hybrid RAG pipeline, an MCP server and client pair, and a workflow-vs-agent reference design.
56 lessons across 13 modules. Most learners complete it in 6-8 hours of focused study. You can work through it at your own pace.
Yes. The entire course is free and open. Start with Module 1 to get a feel for the voice and pace, then keep going through all 13 modules.
Yes. You'll need an Anthropic API key for the hands-on exercises. The course walks you through obtaining one. Some modules also use VoyageAI for embeddings (free tier available).
The course is free and open, so you can revisit the material anytime. Future updates are included at no extra cost.
Yes. We don't store your personal data. Course access is open and managed via a browser cookie. We don't track you with third-party analytics. See our Privacy Policy for full details.