Ready to build intelligent AI agents that can reason, improve, and collaborate? This hands-on course gives you the skills to build agentic AI systems using LangChain and LangGraph in just 3 weeks. You’ll design stateful workflows that support memory, iteration, and conditional logic. You’ll explore how to build self-improving agents using Reflection, Reflexion, and ReAct architectures, empowering your agents to reason about their outputs and refine them over time. Plus, you’ll work on guided labs where you’ll structure agent feedback, integrate external data, and generate context-aware responses through step-by-step reasoning. You’ll then develop collaborative multi-agent systems that coordinate tasks, retrieve relevant data, and solve complex problems using agentic RAG. Plus, you'll gain experience in agent orchestration, query routing, and governance strategies for building robust, scalable AI applications. By the end of the course, you’ll have built working prototypes of agentic systems and gained hands-on skills to design reliable, adaptable agents. Enroll today and get ready to power up your portfolio!
Good, Make it a little more clear on teaching the code and specific functions for agentic systems
Great course with intro to agent & Muti agent.
Great overview and the insight into the coding aspects was invaluable!
Gain good knowledge of concepts required to build Agentic AI system.
It's well structured, giving all insights of expected training.
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Excellent content - well delivered in multiple forms : videos, readings, labs, exercises , which is very helpful in reinforcing the concepts as well as bringing practical confidence.
Good, Make it a little more clear on teaching the code and specific functions for agentic systems
when someone's write text on a presentation , please do not write sloppy . it does not look "cool", it looks unprofessional
Good intro into the landscape. Labs could benefit from redesign/rethinking. Underkill for intermediate and up folks
This course isnt up to the mark. The videos are just linear and the speakers robotic voice makes it difficults for the understand. Overall its not a good crafted course, though the lab assignments were good. I will give a below average rating for this.
lab in module 3 not working. Videos with people writing on board sub-optimal.
The course content is extremely poor. There’s very little human explanation—almost everything else is AI-generated junk. It feels like they just threw a piece of code into an AI and let it ramble without any real structure or logic. I don’t believe anyone can actually understand the video introducing the reflexion agent. Many parts of the course are also riddled with errors. If the earlier courses were merely shallow and full of repetitive, AI-flavored fluff, this one is an outright disaster—completely incoherent.
Agentic AI with LangChain and LangGraph is a well-structured and insightful course that effectively introduces the transition from traditional LLM applications to advanced agent-based systems. It clearly explains key concepts such as agentic workflows, multi-agent collaboration, and Retrieval-Augmented Generation (RAG), while emphasizing practical implementation using LangGraph. The course stands out for its focus on building scalable, stateful AI systems with strong attention to real-world use cases and responsible AI practices, including guardrails and failsafes. Overall, it is a valuable resource for professionals seeking to develop robust, production-ready agentic AI solutions.
This module is fantastic, and I learned a ton! The structured focus on multi-agent collaboration patterns, like the Hub-and-Spoke model, was incredibly valuable.The course does a great job breaking down complex workflows into practical components. I highly recommend it for anyone wanting to build advanced, production-ready AI systems.Key Takeaways: Design Patterns: Mastered specialized agent boundaries and JSON schema standardization. Agentic RAG: Built dynamic routing pipelines using LLMs as decision-makers. Orchestration: Gained hands-on experience using LangGraph for multi-agent coordination. AI Governance: Learned critical safety steps like PII data sanitation.
Great overview and the insight into the coding aspects was invaluable!
It's well structured, giving all insights of expected training.
Great Learning journey, especially in LangGraph
Great course with intro to agent & Muti agent.
Excellent, concepts are clearly explained.
the best agentic ai course in Coursera
very nice course. highly recommended
LangGraph so clearly thanks
Good course on agentic AI
excellent course
Great, complete