The Multi-Agent Systems and Orchestration course teaches learners how to design and coordinate AI agents that work together as collaborative systems. Starting with the OpenAI Agents SDK, participants explore how to structure planner–executor architectures, enabling agents to break down complex tasks into coordinated subtasks.
Multi-Agent Systems and Orchestration
Gain insight into a topic and learn the fundamentals.
Intermediate level
Recommended experience
1 week to complete
at 10 hours a week
Flexible schedule
Learn at your own pace
Skills you'll gain
Details to know
Shareable certificate
Add to your LinkedIn profile
Taught in English
See how employees at top companies are mastering in-demand skills
There are 4 modules in this course
In this module, you'll join LegacyCorp as an AI Consultant, tasked with modernizing their internal logistics and support systems. You will learn to transition from brittle, manual execution loops to resilient architectures using the Agents SDK, mastering key concepts like Orchestration, Handoff Hooks, and Type-Driven Design. Through a series of forensic labs and design challenges, you will build a scalable "Hub-and-Spoke" system capable of managing specialized agents and securing critical tools against misuse
What's included
3 videos4 readings3 assignments3 ungraded labs
In this module, you will step into the role of Lead Architect at Praxis AI to tackle complex orchestration challenges for two distinct clients. First, you will rescue the Urban Hop travel assistant by implementing the Planner-Executor pattern, separating high-level reasoning from deterministic execution to ensure reliability. Next, you will transition to a Site Reliability Engineer (SRE) role for Global Freight, using distributed tracing and observability to diagnose and fix race conditions in a high-concurrency logistics engine. By the end of the module, you will have mastered the architectural patterns necessary to build agentic systems that are not just intelligent, but predictable, scalable, and debuggable.
What's included
2 videos3 readings2 assignments1 ungraded lab
In this module, you tackle the complexity of persistent memory in distributed systems. You will act as a Systems Engineer for Global Freight to solve critical "Lost Update" race conditions using Redis and pessimistic locking. Simultaneously, you will serve as an AI Architect for Urban Hop, implementing Vector Stores (for use with Retrieval Augmented Generation, also known as RAG) and memory optimization strategies to give your agent long-term, semantic recall without blowing up the context window.
What's included
1 video3 readings1 assignment3 ungraded labs
What's included
2 ungraded labs
Instructor
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