Free Download LangChain Framework for Beginners - Build AI Systems + RAG
Published 12/2025
Created by Rahul Shetty Academy
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All | Genre: eLearning | Language: English | Duration: 46 Lectures ( 6h 38m ) | Size: 5.13 GB
Learn LangChain 1.0 Typescript with AI Agents, Tools, RAG Pipelines, Agentic RAG,, MCP Integration& LangGraph Deployment
What you'll learn
Build AI Agents with LangChain using tools, memory, prompts, and multi-model configurations.
Create custom tools with Zod validation and enable LLMs to choose and execute tools intelligently.
Implement dynamic system prompts, middleware, and context injection for accurate agent responses.
Design complete RAG pipelines using embeddings, vector stores, similarity search, and document loaders.
Integrate LangChain Agents with external APIs, databases, and MCP servers for real-world automation.
Deploy production-ready LangGraph agent servers with environment setup, tracing, and safety guardrails.
Requirements
Basic knowledge on Typescript will be helpful
Description
Are you excited about building real AI applications, not just chatting with an LLM?This beginner-friendly LangChain course is designed to take you from zero to confidently building AI Agents, RAG systems, custom tools, middleware, MCP integrations, and deployable LangGraph servers - all with hands-on clarity.LangChain has quickly become the most powerful framework for building AI-powered applications. But with v1.0+ changes, breaking updates, new middleware patterns, and deeper concepts like RAG, MCP, embeddings, and vector stores, students often feel lost.This course removes that confusion by teaching you every concept step-by-step with simple explanations and practical demos.You will start by understanding AI Agents, how they think, how they invoke tools, and how they manage memory. Then you'll build your own tools using Zod validation, pass dynamic context, and learn prompt-engineering tricks using system prompts and middleware.Next, you'll master RAG (Retrieval-Augmented Generation) - loading documents, splitting text, generating embeddings, creating vector stores, and performing similarity search & MMR retrieval to eliminate hallucinations.You'll also learn how to integrate external systems using MCP (Model Context Protocol), and finally deploy everything using LangGraph to build production-ready AI servers.By the end of this course, you'll be fully capable of building your own AI Agent systems - for automation, business workflows, customer support, data retrieval, internal tooling, and more.No prior knowledge of LangChain required.If you want to build practical, real AI systems, this is the perfect place to start.
Who this course is for
Backend Developers and Full-Stack Engineers
QA Engineers, Test Automation Developers, and SDETs
AI Enthusiasts and Prompt Engineers
Anyone curious about the next evolution of AI tooling
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