Course

Building Integrated AI Services with LangChain & LangGraph

This course delves into advanced AI app development using LangChain and LangGraph. You'll learn to create complex AI systems, including Retrieval-Augmented Generation (RAG) and AI Agents, while gaining insights into the integration of various AI services and tools.

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EXPERIENCE
Intermediate level
EST TIME TO COMPLETE Completion time may vary based on individual pacing.
4 hrs, 19 mins
CONTENT
2 modules

Learning path outcomes

  • Design and implement RAG systems for domain-specific AI apps. 
  • Develop AI Agents capable of performing complex tasks through system integrations. 
  • Evaluate the effectiveness and limitations of various AI integration techniques in solving real-world problems. 

Prerequisites

While the course is designed to accommodate developers with varying levels of experience, the following prerequisites are recommended: 
  • Basic programming knowledge in any language 
  • Familiarity with web development concepts and RESTful APIs 
  • Understanding of basic AI and machine learning concepts (beneficial but not required) 

Achievements

Earn a badge when you finish this learning path!

Building Integrated AI Services with LangChain & LangGraph

Learning path content

1
Retrieval-Augmented Generation with LangChain Nov 12 2024 · Module (2 hrs, 3 mins)
This module introduces Retrieval-Augmented Generation (RAG) using LangChain. Students will learn about embeddings, vector databases, and how to enhance LLMs with domain-specific knowledge for apps like intelligent search and chatbots.
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2
AI Agents with LangGraph Nov 12 2024 · Module (2 hrs, 22 mins)
Explore the development of AI Agents using LangGraph. You will learn to create agents capable of taking actions through integrations with other systems, moving beyond simple content generation to more complex, interactive AI apps.
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