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The course will equip you with the knowledge and skills to build and enhance AI agents using the LangGraph extension of LangChain.\n\n## Course Summary\nIn this course, you'll explore key principles of designing AI agents with LangGraph, learning how to build flow-based applications and enhance agent capabilities. Here's what you can expect to learn and experience:\n\n1. 🛠️ **Building from Scratch**: Learn to build an agent from scratch using Python and an LLM, understanding the division of tasks between the LLM and the code around it.\n\u003cp align=\"center\"\u003e\n\u003cimg src=\"images/l1_1.png\" height=\"300\"\u003e \n\u003c/p\u003e\n\n2. 🔄 **LangGraph Implementation**: Rebuild your agent using LangGraph, learning about its components and how to combine them effectively.\n\u003cp align=\"center\"\u003e\n\u003cimg src=\"images/l2_1.png\" height=\"360\"\u003e \n\u003cimg src=\"images/l2_2.png\" height=\"360\"\u003e \n\u003c/p\u003e\n\n3. 🔍 **Agentic Search**: Explore agentic search, which retrieves multiple answers in a predictable format, enhancing the agent’s built-in knowledge.\n\u003cp align=\"center\"\u003e\n\u003cimg src=\"images/l3_1.png\" height=\"300\"\u003e \n\u003c/p\u003e\n\n4. 💾 **Persistence**: Implement persistence in agents, enabling state management across multiple threads, conversation switching, and the ability to reload previous states.\n5. 👥 **Human-in-the-Loop**: Incorporate human-in-the-loop into agent systems to ensure accuracy and reliability.\n6. ✍️ **Essay Writing Agent**: Develop an agent for essay writing, replicating the workflow of a researcher to enhance productivity and quality.\n\u003cp align=\"center\"\u003e\n\u003cimg src=\"images/l6_1.png\" height=\"450\"\u003e \n\u003c/p\u003e\n\nBy the end of the course, you’ll have hands-on experience with LangGraph’s core components and a solid understanding of how to build and enhance AI agents effectively.\n\n## Key Points\n- 🧩 Learn about LangGraph’s components and how they enable the development, debugging, and maintenance of AI agents.\n- 📈 Integrate agentic search capabilities to enhance agent knowledge and performance.\n- 🌟 Learn directly from LangChain founder Harrison Chase and Tavily founder Rotem Weiss.\n\n## About the Instructors\n🌟 **Harrison Chase** is the Co-Founder and CEO of LangChain, bringing extensive expertise in AI and agent systems to guide you through this course.\n\n🌟 **Rotem Weiss** is the Co-founder and CEO of Tavily, specializing in AI agent design and implementation, to help you master the use of LangGraph.\n\n🔗 To enroll in the course or for further information, visit [deeplearning.ai](https://www.deeplearning.ai/short-courses/).\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fksm26%2Fai-agents-in-langgraph","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fksm26%2Fai-agents-in-langgraph","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fksm26%2Fai-agents-in-langgraph/lists"}