Coursera
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AI Agents in LangGraph (Short Course) | Coursera
Learn AI Agents in LangGraph in this 2-hour, Guided Project. Practice with real-world tasks and build skills you can apply right away.
Coursera
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Agentic AI with LangChain and LangGraph | Coursera
August 22, 2025 - This module focuses on building self-improving AI agents using LangGraph. You’ll explore and implement Reflection, Reflexion, and ReAct agent architectures to design workflows that evaluate and refine their own outputs.
Videos
How is agentic AI development different from traditional coding or prompt engineering?
Traditional development builds static applications, and prompt engineering fine-tunes LLM responses. But agentic AI development focuses on designing autonomous, stateful systems that can evaluate their outputs, manage memory, and interact intelligently over time. You'll learn how to architect systems that think, adapt, and collaborate, using tools such as LangGraph to build workflows with cycles, conditionals, and inter-agent communication.
coursera.org
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Agentic AI with LangChain and LangGraph | Coursera
Do I need machine learning experience to take this course?
No prior machine learning (ML) experience is required. If you're comfortable with Python, you're ready to go. This course focuses on building practical agentic AI systems that reflect, improve, and act. No complex ML understanding is required.
coursera.org
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Agentic AI with LangChain and LangGraph | Coursera
What is the learning experience like with Projects?
In Projects, you'll complete an activity or scenario by following a set of instructions in an interactive hands-on environment. Projects are completed in a real cloud environment and within real instances of various products as opposed to a simulation or demo environment.
coursera.org
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AI Agents in LangGraph (Short Course) | Coursera
DeepLearning.AI
learn.deeplearning.ai › courses › ai-agents-in-langgraph › lesson › qyrpc › introduction
AI Agents in LangGraph - DeepLearning. ...
June 5, 2024 - Welcome to AI Agents and LangGraph. Built in partnership with LangChain and Tivoli. Taught by Harrison Chase, co-founder and CEO of LangChain, as well as Rotem Weiss who is the co-founder and CEO of Tavily.
Coursera
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Building Autonomous AI Agents with LangGraph | Coursera
Build autonomous AI agents with advanced query handling and state management. Integrate LangGraph to design scalable, interactive AI systems.
Coursera
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Building AI Agents and Agentic Workflows | Coursera
You’ll start with LangGraph, creating agents that support memory, iteration, conditional logic, and retrieval-augmented generation (Agentic RAG). Next, you’ll explore self-improving agents that use reflection and reasoning, and design ...
Udemy
udemy.com › it & software
LangGraph- Develop LLM powered AI agents with LangGraph
3 weeks ago - Welcome to first LangGraph Udemy course - Unleashing the Power of LLM Agents! This comprehensive course is designed to teach you how to QUICKLY harness the power the LangGraph library for LLM agentic applications.
GitHub
github.com › ksm26 › AI-Agents-in-LangGraph
GitHub - ksm26/AI-Agents-in-LangGraph: Master the art of building and enhancing AI agents. Learn to develop flow-based applications, implement agentic search, and incorporate human-in-the-loop systems using LangGraph's powerful components. · GitHub
In this course, you'll explore key principles of designing AI agents with LangGraph, learning how to build flow-based applications and enhance agent capabilities.
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Coursera
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Agentic AI with LangGraph, CrewAI, AutoGen and BeeAI | Coursera
October 1, 2025 - This course provides a structured approach to designing AI-powered systems using agentic design principles, orchestration strategies, and proven workflow patterns. You’ll explore popular frameworks such as LangGraph, CrewAI, BeeAI, and AG2 ...
Coursera
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AI Agents with LangGraph, Semantic Kernel, and AutoGen | Coursera
Learn to build autonomous AI agents using LangGraph and Semantic Kernel. Create intelligent, adaptive agents that integrate human feedback for improved decision-making.
Class Central
classcentral.com › subjects › artificial intelligence › natural language processing (nlp) › langchain
Online Course: AI Agents in LangGraph from DeepLearning.AI | Class Central
AI Agents in LangGraph
Learn to build controllable AI agents using LangGraph. Create agents from scratch, implement persistence, incorporate human-in-the-loop, and develop an essay-writing agent. Enhance agent knowledge with agentic search.
Price -$1.00
Coursera
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IBM RAG and Agentic AI Professional Certificate | Coursera
Implement function calling, RAG, and vector stores to build intelligent, context-aware applications · Create autonomous AI agents using LangGraph, CrewAI, and AG2 for real-world impact
Udacity
udacity.com › all programs › school of artificial intelligence
AI Agents with LangChain and LangGraph | Online Course | Udacity
March 31, 2026 - Develop advanced AI agents using LangChain and LangGraph. Connect language models to apps, automate workflows, and solve complex tasks.
Coursera
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Multi-Agent Systems with LangGraph | Coursera
February 26, 2026 - This program is ideal for AI engineers, backend developers, and system architects who want to build agent systems that are not only intelligent, but also predictable, auditable, and production-ready. Prior experience with Python, LLM fundamentals, and basic agent concepts will help maximize your learning experience. Learners need a reliable internet connection, a modern web browser, and access to Python development tools. The course uses LangGraph and modern LLM APIs, which do not require specialized hardware.
Coursera
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Fundamentals of AI Agents Using RAG and LangChain | Coursera
March 30, 2026 - Then, you’ll apply in-context learning and advanced prompt engineering techniques, including prompt templates and example selectors, to generate accurate responses. You’ll also work with LangChain’s tools, components, document loaders, retrievers, chains, and agents to simplify LLM-based application development. Through hands-on labs, you’ll develop AI agents that integrate LLMs, LangChain, and RAG technologies.