Top 7 Simple Courses to Build AI Agents Using LangGraph
Andrew Ng, the founder of DeepLearning.AI, recently launched a new course on building single and multi-agent LLM applications using LangGraph. LangGraph is a framework within the LangChain ecosystem designed explicitly to build AI agents using a graph-based approach. It allows developers to structure complex interactions and workflows visually, making them easier to manage and understand. The modular design and reusable components can reduce the development time by up to 30%. The tool facilitates stateful interactions, maintains context across sessions, and supports the integration of external APIs and tools, improving the capabilities of the AI agents. It also allows multi-agent collaboration and provides features like user confirmations and conditional interrupts, enabling a more controlled user experience. Here are a few simple and user-friendly tutorials to help you build AI agents. AI Agents in LangGraph DeepLearning AI’s newly launched course ‘AI Agents in LangGraph’ will help you learn how to use LangGraph to create controllable agents and integrate agentic search to enhance an agent’s knowledge with query-focused answers in predictable formats. The course will be taught by Harrison Chase, the CEO of LangChain; and Rotem Weiss, the CEO of Tavily. The participants will gain insights into implementing agentic memory for enhanced reasoning and debugging, and see how human-in-the-loop input can guide agents at key junctures. In this course, one would learn how to build an agent from scratch and then reconstruct it using LangGraph to understand the framework. Finally, they will be able to develop an essay-writing agent that incorporates all the learnings from the session. New AI Agentic course! Learn to use LangGraph to build single and multi-agent LLM applications in AI Agents in LangGraph. This short course, taught by LangChain @LangChainAI founder Harrison Chase @hwchase17 and @tavilyai founder @weiss_rotem, shows how to integrate agentic… pic.twitter.com/NhPT4GAtRq— Andrew Ng (@AndrewYNg) June 5, 2024 LangGraph: Build Your Own AI Financial Agent Application (Beginners) This tutorial on building a financial agent application with LangGraph is ideal for beginners who wish to harness AI for finance. It will walk them through the steps of creating tools, assigning them to an agent, and managing their interactions through a graph. Additionally, they will be able to integrate Gradio to create an interactive user interface. This will help them access real-time stock prices, recent financial news, detailed reports, and historical data on companies, all within one application. https://twitter.com/MervinPraison/status/1770031742625132591 LangGraph 101 This video session provides an in-depth knowledge of LangGraph, from basic introduction to building graphs in the framework to more complex LangGraph agents. You will learn how to build agents with LangGraph and OpenAI. Hands-on with LangGraph Agent Workflows This video provides a comprehensive tutorial on building a LangChain coding agent using LangGraph. It starts by explaining the basics of manually managing a conversation with OpenAI + Tools and then explains how to handle the same workflow with a custom agent built with LangGraph. The tutorial demonstrates how to integrate these tools into an agent workflow, coordinating them through a graph structure. Build Computing Olympiad Agents with LangGraph This video session teaches you how to create Olympiad programming agents using LangGraph. By the end of the tutorial, you will have a solid understanding of how to build agents in LangGraph, leveraging advanced techniques such as reflection, retrieval, and human-in-the-loop interaction. In this tutorial, we create Olympiad programming agents using LangGraph https://twitter.com/LangChainAI/status/1783517933454639492 Creating an AI Agent with LangGraph Llama 3 & Groq This tutorial focuses on integrating custom tools into your LangGraph agent to extend its capabilities. You will learn how to use the Llama 3 model to enhance the performance and intelligence of your agent, and utilise Groq’s powerful hardware for increased computational efficiency. It will help you design and implement workflows for your agent, leveraging LangGraph’s graph-based structure to manage complex interactions. https://twitter.com/LangChainAI/status/1791864166111969523 Build a Customer Support Bot Using LangGraph This session will help you build a travel assistant chatbot using LangGraph. You will be introduced to various reusable techniques applicable to developing any customer support chatbot or AI system that utilises tools, supports multiple user journeys, or requires a high degree of control. View all stories Top Earthquake Prediction Tools To Watch in 2025 QS World University Rankings 2026: Top 10 Indian Universities Meet Dr. M C Mary Kom at The Rising 2025 – Conference | Bengaluru Top 10 Indian Companies with Highest Women Workforce 2025 DeepSeek Vs ChatGPT – Why World is Falling for this Chinese AI Model
Features such as memory and contextual awareness, stateful workflows, multi-agent collaboration, and a more controlled user experience make LangGraph an efficient tool to build AI agents.
LangGraph is a framework within the LangChain ecosystem designed explicitly to build AI agents using a graph-based approach.
["AI (Artificial Intelligence)", "AI Tool"]
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["AI", "ChatGPT", "OpenAI", "LangChain", "LangGraph", "Gradio", "RAG", "R", "API", "GPT"]
Having done her undergrad in engineering and masters in journalism, Sukriti likes combining her technical know-how and storytelling to simplify seemingly complicated tech topics in a way everyone can understand