LangChain & LangGraph: Building Agentic AI, RAG & Chatbots

About this course

LangChain & LangGraph: Building Agentic AI, RAG & Chatbots

Learn how to build real-world Generative AI applications using LangChain and LangGraph, from the fundamentals of working with Large Language Models to advanced Agentic AI, RAG, tools, memory, parallel workflows, sub-agents, and multi-agent systems.

This is a practical, hands-on course designed to help you understand not just how to use LangChain and LangGraph APIs, but why these concepts exist and how they fit together when building production-style AI applications.

A major focus of this course is running AI locally using Ollama and local LLMs, allowing you to experiment with modern AI development without depending entirely on cloud-based models.

What You’ll Learn:

• Fundamentals of LangChain & LangSmithChat Message History in LangChain for storing conversation data
• Running Parallel & Multiple Chains (Runnable

Parallels, etc.)Building Chatbots with LangChain & Streamlit (with message history)Understanding Tools and Tool chains in LLMBuilding Tools and Custom Tools for LLM Creating AI Agents using LangChainImplementing RAG with vector stores & local LLM embeddings

Using AI Agents and RAG with Tooling while building LLM AppsOptimizing & Debugging AI applications with LangSmithEvaluating & Testing LLM applications with RAGAsReal-world projects & hands-on testing strategies

Assessing RAG & AI Agents with RAGAs

Build

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