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AI Agents in LangGraph

A developer-focused short course on implementing agentic AI applications with the LangGraph framework and understanding graph-based agent workflows.

Provider
DeepLearning.AI
Level
Intermediate

About

AI Agents in LangGraph is a DeepLearning.AI short course for developers who want an implementation-oriented introduction to agentic applications in the LangGraph framework. Its value is narrower than a general agents overview: it places agent construction inside a specific graph-based development context and focuses on building AI agents rather than surveying every agent platform. Learners should arrive ready to work with code and use the course as a focused framework entry point. It is not a substitute for broader production engineering, deployment, or cross-framework comparison.

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Learning Outcomes

  • ✓Explain how a graph-based workflow can organize the steps of an agentic AI application
  • ✓Apply LangGraph concepts when building a focused AI agent workflow in code
  • ✓Identify where framework-level implementation ends and broader production engineering begins

Syllabus

1. Agent workflows in LangGraph

Introduces the LangGraph context and frames agent behavior as an organized graph of steps rather than an undefined autonomous process.

2. Implementing an AI agent

Moves from the conceptual workflow into developer-oriented construction of an agentic application using the named framework.

3. Scope and implementation choices

Clarifies the value of a focused framework example and the additional evaluation, deployment, and reliability work outside a short course.

Skills Covered

🧠 LangGraph🧠 Building AI agents