Sabrina Goldfarb
GitHub
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Build Resilient AI-Powered Software
Gain experience building and hardening AI-enabled features in your applications
Total time: 28 hours, 56 minutes
Core Coursework
Take these in order
Prerequisite: The
Beginner Learning Path and
Node.js Learning Path
Up First
Start your journey into AI-assisted engineering with prompting techniques to help you generate high quality results from LLMs.
Up Next
Create a CLI agent with custom tool calling, evals, context window management, and a human-in-the-loop approval flow.
Up Next
The Model Context Protocol (MCP) standardizes how applications provide communicate with large language models (LLMs). Building an MCP server from scratch is a great way to understand the fundamentals, discover ways to integrate AI in common workflows, and future-proof your career.
Up Next
Dive into the discipline of AI Engineering by building a real agentic application from first principles. Gain the fundamental skills to build, measure, and improve AI-powered systems.
Up Next
Go beyond singe-agent demos and learn to engineer the harness that makes any agent reliable, dependable, and production-ready.
Elective Coursework
Optional, take in any order
What They're Saying
Amazing course. I learned a lot about improving agents, and what an AI engineer does. Very motivated to apply this knowledge in real projects!
Daniel Puerta
Excellent course! Really liked the workflows for known repeated paths. Deterministic systems are the key to enterprise production AI!
Emad Ashraf
Hands down best AI course out there!
Aleksa Mitić
AleksaMiti1
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