Feb 12
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Welcome to the Foundations of LangGraph! 🚀 In this introductory module, you will learn how to use LangGraph, the cutting-edge framework designed for building complex, stateful LLM workflows. If you’ve used LangChain and want to take your AI agents to the next level with better orchestration, branching, and memory, this course is for you. What we cover in this series: 1. The Basics: Understanding LangGraph components (Nodes & Edges) and simple agent workflows. 2. State & Memory: How to manage information persistence across your entire workflow. 3. Multi-Agent Orchestration: Implementing branching, conditional flows, and tool integration. 4. Capstone Project: Building an Autonomous Research Engine using multi-agent systems and Vector Databases. Prerequisites: 1. Basic Proficiency in Python (Functions, Packages, Virtual Environments). 2. Familiarity with Jupyter Notebooks. 3. Foundational knowledge of Prompt Engineering, Tools, and Vector DBs. LangGraph is the "orchestration layer" of the agentic stack. It allows you to move beyond simple chains and create graphical, multi-step workflows that can handle everything from support chatbots to complex office automation. Subscribe to follow along with the full module and build your own autonomous AI research assistant! #LangGraph #LLM #AIAgents #LangChain #Python #GenerativeAI #MachineLearning #MultiAgentSystems