AI Agents in Practice: Build Real End-to-End AI Agents

About this course

AI Agents in Practice is a practical, beginner-friendly course that shows you how to design and build working agentic systems using today’s most relevant tools and frameworks, including ReAct, ReWOO, LangGraph, and LangSmith. It’s the natural next step for anyone who understands the basics of large language models and simple chatbots and now wants to build agents that can plan, use tools, and follow multi-step workflows.

Along the way, we’ll tackle the questions most people have when they first encounter AI agents, such as:

• What drives an AI system browsing the web, reading files, or calling APIs to decide what to do next?
• In what way does it break a task into steps?
• How does it determine which tool to use?
• When does it know to ask a human for help?
• If you want clear, practical answers to these questions without getting lost in theory, this course is for you.

We begin with a concise introductory section that provides a solid understanding of what an AI agent is, how it differs from a standard LLM application, and how agents are used in real projects.

Grasp the core building blocks of an agent.

See how agentic systems fit into real-world AI applications.

Apply best practices for creating prompts and prompt frameworks.

Understand how system and user messages shape agent behavior.

Explore prompt patterns that guide an agent’s reasoning.

Look behind the scenes of a real helper chatbot to connect each concept to a concrete example.

In Project 1, you’ll build a Job-Helper agent using the ReAct pattern, turning theory into a working system step by step.

Explore the structure of a LangGraph project.

Create tools like a file reader and a web-search helper.

Add memory so the agent can use

Prices, discounts and availability are set by Udemy. We may earn a commission when you purchase through links on this site.