DeepLearning.AI's AI Agents in LangGraph teaches you to build AI agents using LangGraph, an extension of LangChain for building stateful multi-agent applications. You build agents that plan, execute, and recover from errors. The course is free on deeplearning.ai. After finishing, you can build agents that loop, branch, and coordinate multiple LLMs. This is more advanced than basic LangChain and assumes familiarity with it. The main limitation: agents are complex systems that often fail in unexpected ways. Real-world deployment requires careful testing and evaluation.
AI agents are one of the fastest-growing areas in applied AI, with thousands of companies shipping agent-based products in 2024 (source: AI industry surveys).
About This Course
DeepLearning.AI's free short course on building agents with LangGraph. Covers ReAct agents, persistence, human-in-the-loop, and search-augmented agents. Taught by LangChain's CEO Harrison Chase alongside Andrew Ng.
Course Details
Frequently Asked Questions
Is this course free?
Yes, free on deeplearning.ai.
Do I need LangChain experience first?
Yes. LangGraph extends LangChain; take the LangChain course first.
What's the difference between chains and agents?
Chains run a fixed sequence of steps. Agents decide their own steps based on what they observe.
What can I build with LangGraph?
Research agents, code generation agents, multi-agent systems where AIs coordinate to complete tasks.
Are AI agents reliable enough for production?
They're improving but still require careful monitoring. Great for prototypes and internal tools now.
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