LangChain with TypeScript: Build AI Apps, RAG & Agents

About this course

Build real-world AI applications with LangChain.js, TypeScript, RAG, Tools, Agents, and LangGraph.

In this course, you'll learn how to use LangChain with TypeScript to build modern AI applications step by step. Instead of jumping directly into complex agents, you'll build a strong foundation and gradually move toward more advanced AI application patterns.

You'll start by understanding the core concepts of LangChain and then progress through prompts, output parsers, embeddings, memory, vector stores, retrievers, and RAG. From there, you'll learn how tools work, how agents use tools, and how LangGraph can be used to build more advanced agentic workflows.

What you'll learn

Build AI applications using LangChain.js and TypeScript

Understand LangChain's core building blocks and how they fit together

Work with prompts and prompt templates

Parse and structure model outputs

Understand embeddings and how they are used in AI applications

Work with vector stores and similarity search

Build retrieval-augmented generation (RAG) applications

Understand retrievers and how they work with RAGGive AI applications access to external tools and functions

Understand the difference between tools, agents, and workflows

Build AI agents using LangChain

Understand how LangGraph fits into modern AI application development

Build practical AI applications instead of only learning isolated conceptsA practical, step-by-step approach

Many AI tutorials jump straight into building an agent without explaining the concepts underneath it. This course takes a different approach.

You'll progressively build your knowledge:

• LangChain fundamentals → Prompts → Output Parsers → Embeddings → Vector Stores → Retrievers → RAG → Tools → Agents → LangGraph
• This

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