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Architecting Multi-agent LLM Systems

New

4 Weeks

Cohort-based Course

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

Architecting Multi-agent LLM Systems

New

4 Weeks

Cohort-based Course

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

Hosted by

Amir Feizpour

9+ years in AI and Product Development, PhD

Amir Feizpour

9+ years in AI and Product Development, PhD

Previous and current affiliations

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...

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

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

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

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

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

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

Week 1
May 27—Jun 2
Week dates are set to instructor's time zone
Events
May
30
Session 1 - LLM Products - Guest Lecture / Group Discussion
Session 1 - LLM Products - Guest Lecture / Group Discussion
Thu, May 30, 4:00 PM - 5:00 PM UTC
Jun
2
Session 2 - LLM Products - Project Office Hour
Session 2 - LLM Products - Project Office Hour
Sun, Jun 2, 4:00 PM - 5:00 PM UTC
Modules
Introduction to Large Language Model Products
Introduction to Large Language Model Products
3 Lessons • 1 Project
Week 2
Jun 3—Jun 9
Week dates are set to instructor's time zone
Events
Jun
6
Session 3 - Multi-agent Systems - Guest Lecture / Group Discussion
Session 3 - Multi-agent Systems - Guest Lecture / Group Discussion
Thu, Jun 6, 4:00 PM - 5:00 PM UTC
Jun
9
Session 4 - Multi-agent Systems - Project Office Hour
Session 4 - Multi-agent Systems - Project Office Hour
Sun, Jun 9, 4:00 PM - 5:00 PM UTC
Modules
Introduction to Multi-agent LLM Systems
Introduction to Multi-agent LLM Systems
3 Lessons • 1 Project
Week 3
Jun 10—Jun 16
Week dates are set to instructor's time zone
Events
Jun
13
Session 5 - Use Cases - Guest Lecture / Group Discussion ft. Chris Butler, Staff Product Operations Manager at GitHub
Session 5 - Use Cases - Guest Lecture / Group Discussion ft. Chris Butler, Staff Product Operations Manager at GitHub
Thu, Jun 13, 4:00 PM - 5:00 PM UTC
Jun
16
Session 6 - Use Cases - Project Office Hour
Session 6 - Use Cases - Project Office Hour
Sun, Jun 16, 4:00 PM - 5:00 PM UTC
Modules
Business Use Cases for Multi-agent System
Business Use Cases for Multi-agent System
3 Lessons • 1 Project
Week 4
Jun 17—Jun 23
Week dates are set to instructor's time zone
Events
Jun
20
Session 7 - System Reliability - Guest Lecture / Group Discussion
Session 7 - System Reliability - Guest Lecture / Group Discussion
Thu, Jun 20, 4:00 PM - 5:00 PM UTC
Jun
23
Session 8 - System Reliability - Project Office Hour
Session 8 - System Reliability - Project Office Hour
Sun, Jun 23, 4:00 PM - 5:00 PM UTC
Modules
Security, Robustness, and Reliability of Multi-agent Systems
Security, Robustness, and Reliability of Multi-agent Systems
2 Lessons • 1 Project

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.

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.

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.

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.

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.

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.

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.

Data Scientist

Meet your instructor

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.

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