This course takes you from the fundamentals of AI agents all the way to building, evaluating, securing, and deploying complete agentic applications. You do not need previous AI or machine-learning experience. If you are comfortable with Python, you can follow the course from the beginning. We start by understanding what AI agents actually are, how the agent loop works, when to use agents instead of traditional workflows, and how tools allow language models to interact with external systems.
You will then learn the essential building blocks of LangChain, including models, messages, prompts, streaming, structured outputs, and tool calling. From there, you will create your first real agent and learn why naive agent implementations often fail in production. The course then moves into LangGraph, where you will build more reliable and controllable agent architectures using state, nodes, edges, routing, parallel execution, subgraphs, persistence, memory, and human-in-the-loop approval.
