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Learner Reviews & Feedback for AI Agents in LangGraph by DeepLearning.AI

4.7
stars
58 ratings

About the Course

LangChain, a popular open source framework for building LLM applications, recently introduced LangGraph. This extension allows developers to create highly controllable agents. In this course you will learn to build an agent from scratch using Python and an LLM, and then you will rebuild it using LangGraph, learning about its components and how to combine them to build flow-based applications. Additionally, you will learn about agentic search, which returns multiple answers in an agent-friendly format, enhancing the agent’s built-in knowledge. This course will show you how to use agentic search in your applications to provide better data for agents to enhance their output. In detail: 1. Build an agent from scratch, and understand the division of tasks between the LLM and the code around the LLM. 2. Implement the agent you built using LangGraph. 3. Learn how agentic search retrieves multiple answers in a predictable format, unlike traditional search engines that return links. 4. Implement persistence in agents, enabling state management across multiple threads, conversation switching, and the ability to reload previous states. 5. Incorporate human-in-the-loop into agent systems. 6. Develop an agent for essay writing, replicating the workflow of a researcher working on this task. Start building more controllable agents using LangGraph!...

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1 - 13 of 13 Reviews for AI Agents in LangGraph

By Marcello B

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Nov 24, 2024

It was a really enlightening course. Well-done, progressive, and with content that will certainly be really useful for deepening the topic of Agents and developing applications. The only downside – not trivial – for which I did not give 5 stars, is that the libraries are outdated and with many incompatibilities. While it's possible to create a virtual environment with the current state of the art, the problem lies in replicating what was learned in a new project with updated libraries. That requires reprogramming a large part of the code. I spent a large part of the time finding solutions to rewrite and update the code. Very heavy and time-consuming ... but overall, I would do it again.

By Evan M

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Jul 1, 2024

As usual pretty fantastic short course on Deep Learning, very grateful! I had errors in the Human in the loop section, no matter how many times I reloaded the page and reran the steps ensuring the kernal was present. Everything else though was great. I was a competitor in NVIDIA's AI Agent Developer Contest and had this been out two weeks ago I would have felt much more confident on employing Graphs vs just Agents. TY very Much, Evan Mendenhall

By Anastasiya N

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Nov 12, 2024

Great project! It provides a good starting point in the world of Agents with LangGraph. Now, I am eager to learn more and to implement my own agentic workflows.

By Elise W

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Sep 19, 2024

very interesting and inspiring work, also solidify my knowledge of llms.

By debobrata p

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Aug 30, 2024

This was really Awesome Learning

By Sanjay U

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Jul 20, 2024

Very Valuable and insightful !!

By Nadeem N

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Sep 17, 2024

just best

By Ahmad S A A

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Jun 29, 2024

Thanks 🌸

By Devi s D

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Dec 19, 2024

Good

By Jaime G

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Jul 3, 2024

Ok

By Svante K

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Nov 7, 2024

Great course! Code needs to be updated to latest version though.

By Eliseo B F

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Oct 16, 2024

a short course that shows the utility of LangGraph

By Jim H

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Nov 12, 2024

PRESENTERS WERE SUBSTANDARD AND WAS UNABLE TO ACCESS THE QUIZS