LangChain with TypeScript: Build AI Apps, RAG & Agents

Course Overview

Learn how to build real-world AI applications using LangChain.js and TypeScript by progressing through core concepts such as prompts, output parsers, embeddings, memory, vector stores, retrievers, RAG, tools, agents, and LangGraph. This course provides a practical, step-by-step approach to developing advanced AI application patterns with modern LLM development techniques.

Key Takeaways

• Build AI applications with LangChain.js and TypeScript using modern LLM development patterns.
• Create Retrieval-Augmented Generation (RAG) applications using embeddings, vector stores, and retrievers.
• Develop AI agents that utilize tools and understand the interaction between tools, agents, and workflows.
• Build advanced agentic workflows with LangGraph and understand its role within the LangChain ecosystem.
• Gain practical experience by building AI application functionality through progressive examples.

Prerequisites

Basic JavaScript or TypeScript programming knowledge is required. Familiarity with Node.js and npm is recommended. No prior experience with LangChain, RAG, or AI agents is necessary. A computer with internet access is needed.

Target Learners

This course is designed for JavaScript and TypeScript developers who want to build AI-powered applications with LangChain.js. It is ideal for Node.js and full-stack developers interested in RAG, AI agents, tools, and LangGraph. Developers looking to move beyond basic LLM API calls and learn to build more capable AI applications with LangChain.js will benefit from this course.