LangChain Tutorial From Basics to Agents and LangGraph Workflows

Description

In this complete LangChain and LangGraph course, you will learn how modern AI applications are designed and built from scratch using a fully hands on approach. This course is not theory heavy. Every concept is immediately implemented so you can clearly understand how real world AI systems actually work. We start by understanding what LangChain is, why it is needed, and how it simplifies AI application development by making it modular, scalable, and easy to maintain. Next, we move into LCEL chains and learn how to design structured and linear workflows that solve real world problems. After that, we deep dive into agents. You will learn what agents are, when to use them, and how to build a simple yet powerful agent using LangChain. We then explore essential tools from the LangChain ecosystem including LangGraph CLI, LangSmith, and LangChain Chat UI so you can properly build, debug, and monitor AI workflows. Finally, we take a complete deep dive into LangGraph workflows where we design complex workflows and build a real world writing agent to solidify everything you have learned. 👨‍💻 Code: https://github.com/stynamic/langchain-course 🔌 Tavily: https://www.tavily.com/ 🎪 Google AI Studio: https://aistudio.google.com/app/apikey 🧩 Langchain Chat UI: Github (https://github.com/langchain-ai/agent-chat-ui) Vercel (https://agentchat.vercel.app/) ⏱ Sections: 00:00:00 Course Overview 00:01:47 LangChain Introduction 00:11:56 LCEL Chains 00:50:43 Building Agents with create_agent() 01:34:33 LangChain Tooling: CLI, LangSmith & Chat UI 01:54:01 LangGraph Workflow 03:36:20 Wrap-up 🔗 Connect with Me: 🌐 LinkedIn: https://in.linkedin.com/in/sumitmorkhade