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    Back to Fundamentals of AI Agents Using RAG and LangChain

    Learner Reviews & Feedback for Fundamentals of AI Agents Using RAG and LangChain by IBM

    Filled StarFilled StarFilled StarFilled StarHalf Faded Star
    4.6
    stars
    90 ratings

    About the Course

    Business demand for technical gen AI skills is exploding and AI engineers who can work with large language models (LLMs) are in high demand.
    This Fundamentals of Building AI Agents using RAG and LangChain course builds job-ready skills that will fuel your AI career. During this
    course, you’ll explore retrieval-augmented generation (RAG), prompt engineering, and LangChain concepts. You’ll look at RAG, its applications,
    and its process, along with encoders, their tokenizers, and the FAISS library. Then, you’ll apply in-context learning and prompt engineering to
    design and refine prompts for accurate responses. Plus, you’ll explore LangChain tools, components, and chat models, and w...
    ...

    Top reviews

    LW

    Nov 30, 2024

    Filled StarFilled StarFilled StarFilled StarFilled Star

    It is excellent to learn prompt engineering, RAG and LangChain, so that the application of LLMs can be much more than chatbot.

    MS

    Apr 27, 2025

    Filled StarFilled StarFilled StarFilled StarFilled Star

    An amazing course. A little fast paced but fulfills its purpose of delivering the knowledge in a such a short span of time.

    Filter by:

    1 - 18 of 18 Reviews for Fundamentals of AI Agents Using RAG and LangChain

    Filled StarFilled StarFilled StarStarStar

    By Mohammad D

    •

    Mar 7, 2025

    I didn't like the quality of this course so much. It was not easy to understand the material. The instructor voice sounds very robotic ( sounds like it's a TTS) and speaks too fast with little effort to simplify concepts. Also they were using lots of vague and empty phrases that say nothing concrete (Examples: LangChain provides an environment to build applications, LangChain facilitates tools and ideas for customization). It feels like reading from a marketing brochure of LangChain.

    Filled StarFilled StarFilled StarFilled StarFilled Star

    By LO W

    •

    Nov 30, 2024

    It is excellent to learn prompt engineering, RAG and LangChain, so that the application of LLMs can be much more than chatbot.

    Filled StarFilled StarFilled StarFilled StarFilled Star

    By Mudassir S

    •

    Apr 27, 2025

    An amazing course. A little fast paced but fulfills its purpose of delivering the knowledge in a such a short span of time.

    Filled StarFilled StarFilled StarFilled StarFilled Star

    By Miao

    •

    Feb 9, 2025

    The hands-on is manageable, yet allow learners to experience the actual flow of using the tools.

    Filled StarFilled StarFilled StarFilled StarFilled Star

    By Mifta Y

    •

    Apr 21, 2025

    BEST COARSE FOR BUILDING A FUNDAMENTAL IN GEN AI

    Filled StarFilled StarFilled StarFilled StarFilled Star

    By Diwakara H

    •

    Mar 20, 2025

    Very informative and interesting

    Filled StarFilled StarFilled StarFilled StarFilled Star

    By Iryna L

    •

    Feb 22, 2025

    So helpfully! Thanks a lot....

    Filled StarFilled StarFilled StarFilled StarFilled Star

    By Darmawan J

    •

    Dec 17, 2024

    veri nice and intuitive

    Filled StarFilled StarFilled StarFilled StarFilled Star

    By Enrique A M

    •

    May 3, 2025

    Thanks IBM

    Filled StarFilled StarFilled StarFilled StarFilled Star

    By Ankur U

    •

    Mar 28, 2025

    good

    Filled StarFilled StarFilled StarFilled StarStar

    By filippo b

    •

    Dec 24, 2024

    Great animations and notebooks, but I got some errors during imports and installation, they should be reworked. Also, the last notebook states that if you want to interact with some private documents, RAG is a good choice. For my understanding, pieces of private documents are sent through the internet during RAG, since they're retrieved and added to prompt in-context, that's why I find this notebook a bit misleading.

    Filled StarFilled StarFilled StarFilled StarStar

    By Ala S

    •

    Feb 4, 2025

    Great Course to Learn the AI agent and RAG. I liked the Summary of what you'll learn and recap in each video. The exams where in good level so you had to clearly understand the concept to be able to get a good mark on them. I felt like instructor spoke quite fast though, so I had to reply each video to keep up with the materials.

    Filled StarFilled StarFilled StarFilled StarStar

    By Hamadullah B

    •

    Apr 26, 2025

    Course content was good but there was not much for us to do in labs. A hint based lab completely solved by the learner can be a good addition.

    Filled StarFilled StarFilled StarFilled StarStar

    By Andrej M

    •

    Mar 15, 2025

    The robotic voice of the reader made the experience a little fake, but the content was interesting

    Filled StarFilled StarFilled StarFilled StarStar

    By Tânia F

    •

    May 7, 2025

    I wish there was more coding questions

    Filled StarFilled StarFilled StarFilled StarStar

    By Laxman G

    •

    Aug 28, 2024

    A glossary would be useful.

    Filled StarFilled StarFilled StarStarStar

    By Bevan J

    •

    Nov 30, 2024

    I think there are some issues with the tests - a number of times I feel the answers are either incorrect or the questions are poorly worded so as to be ambiguous. For example: "In agents, a language model is used as a reasoning engine to determine which of the following actions?" - LangChain agents use only Python code for building applications - Language model - Task manager - Data loader From the videos/summary, agents are clearly communicated as Task manager (see below). Additionally, the wording 'In agents' feels like it is referring to a field or domain of specialization which was never introduced; the concept of an agent as an object was taught. Furthermore, the grammar of the question and answers don't align - by asking for 'actions' you are asking for a verb, but all of the answers are nouns. " - Agents in LangChain are dynamic systems where a language model determines and sequences actions, such as predefined chains. - Agents integrate with tools such as search engines, databases, and websites to fulfill user requests. " Furthermore, an LLM by definition cannot be referred to as a reasoning engine as it is probabilistic by its very nature. The ability to reason (or produce reasoned responses) is not the same as a reasoning engine, which is something like a calculator that is deterministic and based on fundamental axioms.

    Filled StarFilled StarStarStarStar

    By lu g

    •

    Apr 11, 2025

    lecture content: dead internet course. This seems like a course about AI where the content is generated by AI and spoken by AI. I would think the value of using AI in education is to make good content more efficiently. notebooks: thorough and clean. I wish they put the same effort into the lectures as they did the notebooks.

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