Agentic AI Mastery: Multi-Agent Systems in Practice
Vivian Aranha
Founder & AI Instructor at School of AI
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7 people enrolled last week.
Build Production-Ready Multi-Agent AI Systems in 3 Days
Learn on your schedule with this self-paced course featuring pre-recorded sessions. Enjoy lifetime access, so you can revisit and reinforce your learning whenever needed.
AI is rapidly evolving from simple chatbots to autonomous, multi-agent systems that can plan, reason, and execute complex workflows. Yet most professionals are stuck at the prompt engineering stage—unable to design real AI systems that deliver business value.
This course solves that gap.
If you’ve experimented with ChatGPT or Claude but don’t know how to build scalable AI systems, this bootcamp will show you how. You’ll learn how modern companies are building multi-agent architectures using frameworks like LangGraph, CrewAI, and AutoGen—and how to apply these patterns in real-world use cases.
Instead of theory, you will build end-to-end systems: agents that collaborate, use tools, manage memory, and deliver structured outputs. We’ll also cover production concerns like evaluation, guardrails, and deployment.
By the end, you won’t just understand agentic AI—you’ll be able to design and ship multi-agent systems confidently.
What you’ll learn
Design, build, and deploy real multi-agent AI systems—move beyond prompts to production-ready AI engineering.
Design agent roles and responsibilities
Implement task passing between agents
Create structured outputs and workflows
Apply Planner–Executor frameworks
Use Manager–Worker architectures
Implement multi-step reasoning loops
Integrate APIs and function calling
Add short-term and long-term memory
Use vector databases for context retrieval
Build workflows with LangGraph or CrewAI
Compare orchestration approaches
Design scalable agent pipelines
Define success metrics and KPIs
Use LLM-as-a-judge for evaluation
Implement human-in-the-loop feedback
Build APIs using FastAPI
Add logging, monitoring, and cost tracking
Deploy a working multi-agent application
Learn directly from Vivian
Vivian Aranha
Builds enterprise AI systems and trains global AI leaders
Who this course is for
AI Engineers & Developers: Ready to move from LLM apps to real multi-agent systems and production workflows
Product Managers & Builders: Want to design scalable AI products using agent architectures, not just features
Career Switchers into AI: Looking to build portfolio-ready AI systems and break into high-paying AI roles
What's included
Lifetime access
Go back to course content and recordings whenever you need to.
Community of peers
Stay accountable and share insights with like-minded professionals.
Certificate of completion
Share your new skills with your employer or on LinkedIn.
Hands-On Multi-Agent System Build
Build a complete multi-agent AI system from scratch with planning, execution, and orchestration—no fluff, all real implementation.
Production-Ready Skills (Not Just Prompts)
Learn how to design AI systems with memory, tools, evaluation, and deployment—skills companies actually hire for.
Modern Agent Frameworks
Work with LangGraph, CrewAI, and AutoGen to understand real-world orchestration patterns and when to use each.
Portfolio-Ready Final Project
Leave with a fully functional multi-agent system, architecture diagram, and demo you can showcase to employers or clients.
Designed for Real-World Use Cases
Apply what you learn to business scenarios like research automation, analytics, and AI assistants used in modern companies.
Maven Guarantee
This course is backed by the Maven Guarantee. Students are eligible for a full refund up until the halfway point of the course.
Course syllabus
15 lessons • 3 projects
Week 1
DAY 1 — Foundations + Single-Agent → Multi-Agent Thinking
DAY 2 — Multi-Agent Systems + Orchestration
DAY 3 — Production-Grade Systems
Schedule
Projects
6-8 hrs / week
Async content
5-6 hrs / week
Frequently asked questions
$20
USD
2 cohorts