Architecting Multi-agent LLM Systems

New
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4 Weeks

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Cohort-based Course

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

Previous and current affiliations

University of Toronto
University of Oxford
RBC
aggregate intellect

This course is popular

6 people enrolled last week.

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

8 interactive live sessions

Lifetime access to course materials

11 in-depth lessons

Direct access to instructor

4 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

Expand all modules

    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

    PhD

    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.

    A pattern of wavy dots
    Join an upcoming cohort

    Architecting Multi-agent LLM Systems

    Cohort 1

    $500 USD

    Dates

    May 27—June 23, 2024

    Payment Deadline

    May 26, 2024
    |

    Bulk purchases

    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.

    • May 27, 2024 - June 23, 204

      Course will run for 4 weeks in May and June. You will have access to reading / watching material, instructor, and hands-on teaching assistants.

    • Weekly projects

      2 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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    Are there discounts / scholarships available?
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    What tools or software will be used in this course?
    Is technical support / feedback available during / after the course?
    Do I have to come up with my own project idea?
    What is a multi-agent LLM system?
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    A pattern of wavy dots
    Join an upcoming cohort

    Architecting Multi-agent LLM Systems

    Cohort 1

    $500 USD

    Dates

    May 27—June 23, 2024

    Payment Deadline

    May 26, 2024
    |

    Bulk purchases

    $500 USD

    4 Weeks