AI Agents in LangGraph - Syllabus

• Introduction
  • Overview of LangGraph and its role in building controllable agents
  • Course objectives and key components
• Build an Agent from Scratch
  • Introduction to agent building with Python and LLMs
  • Code examples for creating a simple agent
• LangGraph Components
  • Understanding LangGraph components for flow-based applications
  • Re-implementing the agent using LangGraph
• Agentic Search Tools
  • Implementing agentic search for multi-answer retrieval
  • Using search to enhance agent knowledge
• Persistence and Streaming
  • Enabling persistence for state management and conversation switching
  • Using streaming for continuous agent responses
• Human in the Loop
  • Incorporating human feedback into agent workflows
  • Code examples for human-in-the-loop systems
• Essay Writer
  • Developing an agent for essay writing using LangGraph
  • Replicating the workflow of a research assistant
• LangChain Resources
  • Overview of additional LangChain resources and tools
  • Tips for expanding knowledge in LangChain
• Conclusion
  • Summary of LangGraph capabilities and course concepts
  • Future directions for building advanced agents