Build Multi-agent LLM Products

5.0

(4 ratings)

·

7 Weeks

·

Cohort-based Course

Learn to design, implement, and deploy near-term multi-agent systems to solve business problems.

This course is popular

3 people enrolled last week.

Previous and current affiliations

University of Toronto
University of Oxford
RBC
aggregate intellect

Course overview

Become a Multi-agent LLM Systems Architect

Multi-agent LLM systems, while powerful, face hurdles. Optimizing teamwork, managing complex information flow, and ensuring security are just a few.


This course equips you to grasp the core principles of multi-agent LLMs, identify use cases, and explore how to integrate them into current products.


By the end, you'll be well on your way to becoming a multi-agent LLM system architect, able to design and build the future of multi-player human-machine systems.

This course is for you if...

01

You're a product person who has experimented with LLM APIs like OpenAI or open source LLMs locally, OR created custom GPT agents.

02

You're a machine learning person looking to translate LLM potential into practical architectures, strategies and products.

03

You are software person who cares about the reliability & robustness of the LLM systems you pitch to stakeholders (investors, execs).

At the end of this course you will ...

Understand the core principles of multi-agent LLM systems

Grasp how multiple LLMs can collaborate with each other, get feedback from or assign tasks to humans, ad use tools to tackle complex problems

Integrate LLMs with existing product offerings to enhance user and customer experience

Bridge the gap by crafting strategies to seamlessly integrate LLMs with existing products, boosting user experience, productivity, and business metrics.

Understand key considerations for securing, robust, and reliable LLM systems

Learn what it takes to build robust multi-agent LLMs. Understand security best practices and ensure system reliability.

This course includes

Interactive live sessions

Lifetime access to course materials

In-depth lessons

Direct access to instructor

Projects to apply learnings

Guided feedback & reflection

Private community of peers

Course certificate upon completion

Maven Satisfaction Guarantee

This course is backed by Maven’s guarantee. You can receive a full refund within 14 days after the course ends, provided you meet the completion criteria in our refund policy.

Course syllabus

Week 1

Jan 13—Jan 19

    Ingredients of Agentic Systems & Setup

    4 items • Free preview

Week 2

Jan 20—Jan 26

    Design Your Multi-agent System

    3 items • Free preview

Week 3

Jan 27—Feb 2

    Build v0.1 of your Multi-agent LLM Product

    2 items • Free preview

Week 4

Feb 3—Feb 9

    Evaluate and Improve your Multi-agent LLM Product

    2 items • Free preview

Week 5

Feb 10—Feb 16

    Deploy your Multi-agent Product

    2 items • Free preview

Week 6

Feb 17—Feb 23

    Prepare you Product for Demo

    2 items • Free preview

Week 7

Feb 24—Feb 28

    Prepare and Present a Public Demo

    2 items • Free preview

5.0

(4 ratings)

What students are saying

What people are saying

        They say if you can't explain something in simple terms to a non-expert, you don't fully understand it either. That's how I know Amir knows what he's talking about. No unnecessary jargon. No pretence. He knows his audience and I've had no trouble understanding him even though I have little exposure to LLMs.
Nayana T.

Nayana T.

Founder & CTO
        Amir has an interactive presentation style, ushering the audience to find out the details of the most complex concepts by encouraging the right questions and discussions. This makes the retention of the information so much deeper since the learning takes place via a collaborative discovery rather than memorization.
Ehsan A.

Ehsan A.

Head of AI Innovation & Acceleration
        Amir has a knack of presenting ideas with simplicity and asking the right questions. He has a great intuitive sense of ML as a business leader and a researcher allowing him to zoom in and out on demand to effectively communicate complex ideas with any audience.
Nikhil V.

Nikhil V.

Founding ML Engineer
        Amir's combination of rigorous thinking and an ability to get to the heart of the matter is truly amazing.  Every conversation with him challenges me to up my game. He is able to do deep discussions on a wide range of topics, be it LLMs, product development, or heavy ML research. He is great at deconstructing and communicating difficult concepts.
Yerzat M.

Yerzat M.

ML Product Manager
        As a researcher, I jump between topics constantly. Learning from Amir gave me the skills and confidence to tackle anything, even outside my expertise. My biggest project (besides my PhD) is on APIs, thanks in part to Amir's events and insights.
Roxana B.

Roxana B.

Sr. UX Consultant
        Amir's insights are fantastic! He breaks down complex topics into clear ideas and helps you ask the right questions. He is great at facilitating discussions, expertly drawing out everyone's thoughts, fostering a collaborative and open learning environment.
Ian Y.

Ian Y.

ML Engineer
        I have attended many sessions organized by Amir in the past 5 years. I love that he can explain difficult technical concepts with ease from multiple angles: technical, product, and business. This helps to understand the concepts holistically in the context of serving the larger purpose of the product or service.
Gurinder G.

Gurinder G.

Data Scientist

Meet your instructor

Amir Feizpour

Amir Feizpour

10 yrs in NLP, Founder of AISC - Community of 5k AI devs and founders

Amir is the founder of Aggregate Intellect, helping clients leverage LLM systems to augment their business workflows. Prior to this, Amir was an AI Product Lead at Royal Bank of Canada and built a document processing platform used by internal lines of business. Amir held a research position at University of Oxford conducting experiments on quantum computing resulting in high profile publications and patents. Amir holds a PhD in Physics from University of Toronto. Amir has also founded and grown a global community of 5000+ engineers, researchers, and founders gathered around topics in natural language processing.

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Join an upcoming cohort

Build Multi-agent LLM Products

Cohort-2501

$700

Dates

Jan 13—Mar 1, 2025

Payment Deadline

Jan 16, 2025

Course schedule

4-8 hours per week

  • Thursdays & Sundays

    12:00pm - 1:00pm EST

    We will have group discussions and guests lecturers on Thursdays, and project office hours on Sundays.

  • Sep. 9, 2024 - Oct. 25, 204

    Course will run for 6 weeks in September and October. You will have access to reading / watching material, instructor, and hands-on teaching assistants.

  • Weekly projects

    2-4 hours per week

    There will be a project that you will do alongside the course material with weekly milestones.

Learning is better with cohorts

Learning is better with cohorts

Active hands-on learning

This course builds on live workshops and hands-on projects

Interactive and project-based

You’ll be interacting with other learners through breakout rooms and project teams

Learn with a cohort of peers

Join a community of like-minded people who want to learn and grow alongside you

Frequently Asked Questions

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What happens if I start the cohort and then realize that can't continue?

Are there discounts / scholarships available?

Is there a bulk purchase discount?

Do you offer private / corporate cohorts?

Can I access the course materials after completion of the course?

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Do I have to come up with my own project idea?

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What is a multi-agent LLM system?

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A pattern of wavy dots

Join an upcoming cohort

Build Multi-agent LLM Products

Cohort-2501

$700

Dates

Jan 13—Mar 1, 2025

Payment Deadline

Jan 16, 2025

$700

5.0

(4)

·

7 Weeks