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AI Agents: Building Teams of LLM Agents that Work For You (Udemy.com)

AutoGen, ChatGPT API, Streamlit, Google Cloud, build and deploy LLM AI Agents based apps (locally or at scale)

4.5
9,487 reviews

Created by: Mohsen Hassan

Last updated September 2025

Our take

Based on the ratings of 9,487 students, a sample of their written reviews and the syllabus, as the course stood in September 2025. No course pays to be reviewed.

Mohsen Hassan and Ilyass Tabiai walk through building teams of LLM agents that talk to each other and get real tasks done, using OpenAI's ChatGPT API and the AutoGen framework. Over 9.3 hours and 49 lectures, the course moves from single-agent basics to a full stock-analysis app, then optional sections add a Streamlit front end, Google Cloud deployment, and a Stripe paywall. It suits people who can read Python but have never touched multi-agent systems, and it expects an OpenAI account funded with a few dollars to follow along.

Reviewers like the clear, real-world explanations, comparisons such as the autocomplete analogy for how LLMs work, and the payment section for anyone who wants to charge for their app. One reviewer says they went in thinking AI was highly complex and came out seeing it as mostly agent communication built on logic and tools. The complaints cluster around pacing: one reviewer says the instructor reads full AI-generated answers aloud, padding lessons that could be half as long. Others hit version mismatches and missing setup steps in the notebooks, plus a few out-of-date scenarios that needed outside research to work around.

At 9.3 hours it's a lean course next to some much longer AI bootcamps on the site, which suits people who want to ship one working agent app rather than survey the whole field. The optional deployment and payment sections are the real differentiator, since most agent courses stop at a notebook demo. Expect some rough edges from a fast-moving topic, but a 4.5 rating across nearly 9,500 reviews suggests most people get what they came for.

Best forAnyone who wants a step-by-step build of a multi-agent AI app, from AutoGen to Google Cloud deployment.
Skip it ifYou want deep AutoGen theory or a course that stays current with fast-moving AI tooling.

Pros

  • Builds one real AI Agent app end-to-end, not just isolated demos
  • Optional sections cover Streamlit front-ends, Google Cloud deployment, and Stripe payments
  • Reviewers praise the plain-language explanations of how agents communicate
  • Covers AutoGen's chat structures in depth, 12 lectures and 175 minutes

Cons

  • Some lessons pad out with the instructor reading full AI answers aloud
  • A few reviewers hit version mismatches and out-of-date scenarios in the notebooks
  • Needs a funded OpenAI account, though one section covers free local LLMs
Exceptionally great lectures. Full of knowledge and learning . Thank you for creating this learning experience.
Anonymized User, a student

Listed as all levels, but reviewers needed basic Python and patience for environment setup quirks.

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What you will learn

  • Build teams of AI Agents that can achieve complex tasks
  • Build LLM Agents based Apps
  • Use ChatGPT's API
  • Use AutoGen to enable AI Agents to communicate with one another
  • Build a front-end to communicate with your team of AI Agents (optional)
  • Run a AI Agent App at scale using Google Cloud (optional)
  • Set up a payment system to charge users to use your AI Agents based App (optional)

Course content

9 sections · 49 lectures · 9.3 hours of video 2 articles

  1. 1Intro to LLM Agents 1 free preview5 lectures · 41 min
  2. 2LLM Agents Implementation (with OpenAI's ChatGPT) 2 free previews9 lectures · 1.4 hours
  3. 3[Optional] Running Open Source LLMs Locally (Free) instead of OpenAI's ChatGPT2 lectures · 33 min
  4. 4LLM Agents Implementation Continued3 lectures · 29 min
  5. 5AutoGen Chat Structures12 lectures · 2.9 hours
  6. 6Application: Using Agents for Stock Analysis4 lectures · 56 min
  7. 7Deploy Your AI Agent App6 lectures · 1.3 hours
  8. 8[Optional] Add Subscription - Payments to your App7 lectures · 1.1 hours
  9. 9Bonus Lecture1 lecture

Who it is for

The instructor says it suits

  • Everyone ready to learn about this brand new way of using LLM Agents

What you need before you start

  • Basic Programming Knowledge (we explain all code provided step by step)
  • No prior knowledge required, everything is shown step by step.

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Course Description

In this course you'll learn about this new way of using LLM Agents: deploying multiple agents to work together as teams to accomplish more complex tasks for you!

Everything is taught step by step and the course is fully practical with multiple examples and one complete AI Agents-based App that we build together.

One of the things we use to accomplish this is ChatGPT's API so we can use ChatGPT through Python.

We also use AutoGen to enable our Agents to work together and communicate with one another (to accomplish tasks with no human intervention).

We also provide a few optional sections. One of these sections teaches to have a front-end, using Streamlit, to more easily interact with your AI Agents.

Another optional section is for those who want to run AI Agents at scale! Here we show you how to deploy your LLM Agents on Google Cloud, so anyone can use your product.

Lastly, one more optional section is available showing how to set up a payment system/subscription model using Stripe for those who want to monetize their AI Agents-based App!

Everything is explained simply and in a step-by-step approach. All code shown in the course is also provided.

Please not that the OpenAI API is not free, you will need to fund your OpenAI developer account with about $5-10 to follow through with the class and build your own app. We clearly show and explain how to do this and minimize your OpenAI costs during this class.
Read More All Levels All Levels product length iconTime: 9.3h

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Instructor Details

Mohsen Hassan

Mohsen has a deep passion for finance and computer science. Having studied and worked in the field, he has developed a deep understanding of the financial industry's many facets: Long-term investing, shorter-term trading, and automation.

Mohsen has started Bloom Trading because of his passion for the financial field and teaching others about the financial markets and programming.

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Reviews

4.5

9,487 ratings on Udemy

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By Xavier SIRVENT on 7/21/2026

Excellent course. Sometimes you scroll the page back and forth too quickly when showing us something.

By Anonymized User on 5/4/2026

This course is interesting and having a value of information that I am achieving. a great learning experience for me from this course. I like it.

By Michal Straszewicz on 3/27/2026

The tutor reads aloud every answer given by the AI model/agent, even if it's an entire blog post! The content of each lesson could have been halved. This makes it harder to follow, as a large part of each lesson is just filler.

By Anonymized User on 3/18/2026

Nice explanation. It would be greatly beneficial if the course can come up with a lab environment to facilitate learning by doing.

By Tibor Mikis on 3/17/2026

The performance exceeded my expectations.

By Anonymized User on 3/16/2026

The clarity of the explanations and the real world examples given, such as the analysis and comparison made to autocomplete features, is very beneficial for an early understanding of what LLMs entail and how they operate on mass scales

By Anonymized User on 2/19/2026

Exceptionally great lectures. Full of knowledge and learning . Thank you for creating this learning experience.

By Juan Carlos Coello on 1/12/2026

Yes, very good course, but if it wasn't for MCP I couldn't have done it until now, there are many inconsistencies and out of date scenarios

By Anonymized User on 11/17/2025

I have gained substantial knowledge about LLM agents, and after completing some practical exercises, I find their implementation to be relatively straightforward. Prior to this course, I believed that artificial intelligence was highly complex; however, I now understand that it primarily revolves around communication between agents, leveraging logic and tools to build effective solutions.

By Anonymized User on 11/11/2025

I like the fact theres a section for a payment processing which is interesting. however, it wasnt clear to me that st-paywall did all the magic of using the secrets in the .txt and working together with streamlit automatically, all in just a few lines of code

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Overall Score : 90 / 100

AI Agents: Building Teams of LLM Agents that Work For You
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  • Video Duration: icon 9.3h
  • Price: $89.99 Track Price 11.99 Track Price
  • Provider: icon Udemy
  • Updated: icon September 2025
  • Level: All Levels All Levels
  • Language: icon English
  • Certificate: icon Yes
  • Lectures:49 in 9 sections
  • Students:28,900
  • Subtitles:11 languages
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