Build Multi-Agent Applications - A Bootcamp

4.8 (12)

·

7 Weeks

·

Cohort-based Course

Design, develop, deploy, and demo an LLM agent application in 7 weeks!

OUR STUDENTS CAME FROM

Meta
Google
TD Bank
Wells Fargo
Accenture

Course overview

Mentorship Program to Help You Build an Agent-based MVP

🟢 WHAT WILL I BE ABLE TO BUILD IN THIS COURSE?

You’ll build a functional application powered by LLM agents to automate a workflow of your choice. Along the way, you'll learn to design agent workflows, and integrate required tools. By the end of the course, you'll have a working MVP ready to showcase in a public demo.


You can see this playlist for examples of what previous students built: https://tinyurl.com/llm-agent-demos


🟢 HOW WILL YOU HELP ME BUILD APPS LIKE THESE IN JUST 7 WEEKS?

This course is all about learning by doing. You do a real project, applying concepts you learn about AI agents with our expert guidance. Specifically:

👨🏽‍🏫 1:1 sessions with the instructors to help you think through bigger picture questions

👨‍🎓 Async and sync sessions with a dedicated TA for constant support, code reviews, and real-time feedback


To help you prepare, we have also curated 70+ hours of content, a "Learning Path" covering everything from product design and coding fundamentals to advanced LLM engineering concepts that you can consume at your own pace, as soon as you sign up. (see the next question for details)


🟢 OK! THAT DOES SOUND FUN, BUT HOW DO I KNOW IF I HAVE THE RRE-REQUISITES AND I'M READY FOR BUILDING?

That's the most common question we get!


The "Learning Path" we have curated should also give you a good sense of what knowledge we assume as pre-reqs. You should get started on that and then sign up for the course as soon as you feel you are ready:

https://maven.com/p/bafd83/llm-agents-learning-path


🟢 I SEE! SO, I'LL DO MY PREP BEFOREHAND, THEN WHAT SHOULD I EXPECT TO HAPPEN DURING?

Think about it like this (since we're developing a product here, eh?): This is a 3-sprint product dev + 1 week of prep for the public demo.

🖌️ SPRINT 1 - DESIGN (weeks 1 & 2)

🔨 SPRINT 2 - DEVELOP (weeks 3 & 4)

🚢 SPRINT 3 - DEPLOY (weeks 5 & 6)

🎭 PUBLIC DEMO (week 7)

In each sprint, you communicate your progress or blockers on Slack, you collaborate on your designs / code on GitHub, you show up to provide weekly project updates and get feedback, and finally you do an end of sprint demo.


🟢 WHAT IF I DON'T HAVE A PROJECT IDEA?

We will have a default project (most probably related to automating data science work) that you can participate in. If your goal is to better internalize the concepts rather than working on a specific idea, you can join that project. We commonly see that people re-take the course in the future to further develop specific ideas they have, and focus on building the foundations the first time they take the course.


🟢 COOL! I'M EXCITED TO GET STARTED, AND A DISCOUNT WOULD REALLY SWEETEN THE DEAL!

Glad to hear that! There are a few options:

🧑🏿‍🤝‍🧑🏼 You can find a buddy or colleague and sign up together. (20% off 2-9 seats | 25% off 10+ seats)

✴️ We often share discount codes with communities (including AISC members - reach out to community@ai.science if you're not part of our slack). So, check in with the communities you are part of.

📆 We regularly hold events and info sessions where we share flash sales discounts valid for a day or two. Join the mailing list on this page to receive notifications about those.

This course is for you if...

01

You want to build an agentic MVP to demonstrate your skills for career progression purposes.

02

You want to build an agentic MVP to test the feasibility of your startup idea.

03

You want to build an agentic MVP to explore the new feature you want to add to your existing product

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.

Course syllabus

Week 1

Jan 13—Jan 19

    Jan

    16

    Session 1 - Course Meet & Greet - Intro to Process Mapping

    Thu 1/164:00 PM—5:00 PM (UTC)

    Jan

    19

    Session 2 - Project Office Hour - Teams Finalized and First Meet

    Sun 1/194:00 PM—5:00 PM (UTC)

    Ingredients of Agentic Systems & Setup

    4 items • Free preview

Week 2

Jan 20—Jan 26

    Jan

    23

    Session 3 - Lecture - Converting Workflows to Multi-agent Architecture Designs

    Thu 1/235:00 PM—6:00 PM (UTC)

    Jan

    26

    Session 4 - Project Office Hour - First Project Update

    Sun 1/265:00 PM—6:00 PM (UTC)

    Design Your Multi-agent System

    3 items • Free preview

Week 3

Jan 27—Feb 2

    Jan

    30

    Session 5 - Guest Lecture / Group Discussion ft. Abhimanyu Anand - Agentic Workflow Tips & Tricks

    Thu 1/304:00 PM—5:00 PM (UTC)

    Feb

    2

    Session 6 - Project Office Hour - Second Project Update

    Sun 2/25:00 PM—6:00 PM (UTC)

    Build v0.1 of your Multi-agent LLM Product

    2 items • Free preview

Week 4

Feb 3—Feb 9

    Feb

    6

    Session 7 - Guest Lecture / Group Discussion ft. Abi Aryan, Author of LLMOps: Managing Large Language Models in Production

    Thu 2/65:00 PM—6:00 PM (UTC)

    Feb

    9

    Session 8 - Project Office Hour - Last Project Update

    Sun 2/95:00 PM—6:00 PM (UTC)

    Evaluate and Improve your Multi-agent LLM Product

    2 items • Free preview

Week 5

Feb 10—Feb 16

    Feb

    13

    Session 9 - Guest Lecture / Group Discussion ft. Osh Momoh - Deployment and Ops

    Thu 2/135:00 PM—6:00 PM (UTC)

    Deploy your Multi-agent Product

    2 items • Free preview

Week 6

Feb 17—Feb 23

    Feb

    20

    Session 10 - Demo Dry Run

    Thu 2/205:00 PM—6:00 PM (UTC)

    Prepare you Product for Demo

    2 items • Free preview

Week 7

Feb 24—Feb 28

    Feb

    28

    Session 11 - Public Demo Day

    Fri 2/285:00 PM—6:00 PM (UTC)

    Prepare and Present a Public Demo

    2 items • Free preview

4.8 (12 ratings)

What students are saying

Free resource

LLM AGENTS - Learning Path

Are you interested in building LLM Agent Products, but unsure where to begin, or if you have the necessary background knowledge? We have curated this learning path using 70+ hours of (mostly) free resources that you can use to:

  1. Get started on your journey of building LLM Agent Products
  2. Prepare to get the most of this course or similar ones, and
  3. Evaluate areas where there's a gap in your knowledge


After entering your email, use this password: 1g3ntspath


Contact maven@ai.science if you have any issues with this resource.

Get this free resource

Frequently Asked Questions

Meet your instructor

Amir Feizpour, PhD

Amir Feizpour, PhD

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.

Abhimanyu Anand

Abhimanyu Anand

Abhimanyu has 7+ years of experience building AI products and applications across diverse industries—from large-scale internet platforms to metals & mining and e-commerce.


Currently, he leads the development of recommender systems and NLP-driven applications at Wattpad, delivering personalized content experiences to millions of users.

In addition, Abhimanyu consults with companies, helping them design and implement Generative AI solutions.


In this course, he'll draw on his practical experience to support you in designing, building, and deploying agentic applications.

A pattern of wavy dots

Join an upcoming cohort

Build Multi-Agent Applications - A Bootcamp

Cohort-2501

$700

Dates

Jan 13—Mar 1, 2025

Payment Deadline

Jan 16, 2025
Get reimbursed

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

Stay in the loop

Sign up to be the first to know about course updates.

A pattern of wavy dots

Join an upcoming cohort

Build Multi-Agent Applications - A Bootcamp

Cohort-2501

$700

Dates

Jan 13—Mar 1, 2025

Payment Deadline

Jan 16, 2025
Get reimbursed

$700

4.8 (12)

·

7 Weeks