Build Multi-agent LLM Products
5.0 (4)
7 Weeks
·Cohort-based Course
Learn to design, implement, and deploy near-term multi-agent systems to solve business problems.
Build Multi-agent LLM Products
5.0 (4)
7 Weeks
·Cohort-based Course
Learn to design, implement, and deploy near-term multi-agent systems to solve business problems.
Previous and current affiliations
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
11 interactive live sessions
Lifetime access to course materials
10 in-depth lessons
Direct access to instructor
7 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.
Build Multi-agent LLM Products
Course syllabus
Week 1
Jan
16
Session 1 - Course Meet & Greet - Intro to Process Mapping
Jan
19
Session 2 - Project Office Hour - Teams Finalized and First Meet
Ingredients of Agentic Systems & Setup
Week 2
Jan
23
Session 3 - Lecture - Converting Workflows to Multi-agent Architecture Designs
Jan
26
Session 4 - Project Office Hour - First Project Update
Design Your Multi-agent System
Week 3
Jan
30
Session 5 - Guest Lecture / Group Discussion ft. Abhimanyu Anand - Agentic Workflow Tips & Tricks
Feb
2
Session 6 - Project Office Hour - Second Project Update
Build v0.1 of your Multi-agent LLM Product
Week 4
Feb
6
Session 7 - Guest Lecture / Group Discussion ft. Abi Aryan, Author of LLMOps: Managing Large Language Models in Production
Feb
9
Session 8 - Project Office Hour - Last Project Update
Evaluate and Improve your Multi-agent LLM Product
Week 5
Feb
13
Session 9 - Guest Lecture / Group Discussion ft. Osh Momoh - Deployment and Ops
Deploy your Multi-agent Product
Week 6
Feb
20
Session 10 - Demo Dry Run
Prepare you Product for Demo
Week 7
Feb
28
Session 11 - Public Demo Day
Prepare and Present a Public Demo
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Meet your instructor
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.
Join an upcoming cohort
Build Multi-agent LLM Products
Cohort-2501
$700
Dates
Payment Deadline
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
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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Join an upcoming cohort
Build Multi-agent LLM Products
Cohort-2501
$700
Dates
Payment Deadline