AI Agents with LangChain and LangGraph

Übersicht

This course explores the use of LangChain and LangGraph for building advanced AI agent systems. It introduces learners to graph theory, state machines, and agentic systems, enabling them to build flexible AI-driven solutions for tasks such as knowledge retrieval using cyclical workflows.

Lehrplan

• Introduction to Agentic Frameworks
Unpack agentic frameworks by exploring key concepts, applications, and roles in shaping perceptions and behaviors within societal structures.
• Build with LLMs in LangChain
Explore the LangChain ecosystem, integrating large language models via APIs and libraries for dynamic app development. Gain practical skills for creating efficient chains.
• Agentic Workflows with LangGraph
Explore agentic workflows with LangGraph, where the agent controls flow dynamically. Learn to set up nodes, manage states, and integrate with LangChain for dynamic, reliable AI applications.
• Create a Knowledge Base Agent
Build a reliable AI Knowledge Base Agent by integrating data sources, ensuring expanded knowledge, and enhancing interaction through RAG pipelines and observability techniques.
• HealthBot: AI-Powered Patient Education System
Develop an AI agent to enhance patient education by delivering personalized, on-demand health information through summaries, comprehension checks, and quizzes about relevant medical topics.

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Unterrichtet von

Henrique Santana

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Fachgebiete

Computer Science