This course bridges the gap between AI that thinks and AI that acts. You'll learn to build AI agents—LLMs equipped with tools, memory, and reasoning capabilities—that can execute workflows autonomously.

The course covers the core components of agents (the model, system prompt, tools, and memory) and explores practical architectural patterns such as prompt chaining, routing, parallelization, orchestrator–worker designs, and reflection loops. You'll also explore how agents communicate with one another through protocols and handoffs, and learn the Model Context Protocol (MCP), which enables you to build and consume standardized tool interfaces.

Through progressive projects, you'll develop everything from focused AI workflows to more autonomous agents capable of tackling open-ended objectives.

 

How It Works

Course Length
2 weeks

Effort
8 to 10 hours of study per week

Format
100% online, instructor-led
  • Software engineers and developers
  • Data scientists and analysts
  • Machine learning engineers
  • AI and NLP Practitioners
  • Technical product managers
  • CTO and tech executives
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