Design and Govern Advanced Multi-Agent AI Systems is an intermediate-level course for AI engineers, data scientists, and technical leaders who need to architect collaborative AI systems that work reliably at scale. As the agentic AI market explodes with 56.1% growth, organizations are moving beyond single-agent implementations toward sophisticated multi-agent orchestration.
Advanced Multi-Agent AI System
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Gain insight into a topic and learn the fundamentals.
Intermediate level
Some related experience required
2 hours to complete
Flexible schedule
Learn at your own pace
Skills you'll gain
- Agentic Workflows
- Agentic systems
- Enterprise Application Management
- Site Reliability Engineering
- Generative Model Architectures
- Application Deployment
- AI Enablement
- Middleware
- AI Security
- System Monitoring
- Systems Architecture
- CrewAI
- Generative AI Agents
- Continuous Monitoring
- Artificial Intelligence and Machine Learning (AI/ML)
- Event Monitoring
- AI Orchestration
- Model Deployment
- LangGraph
- Software Architecture
Details to know
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Recently updated!
December 2025
Taught in English
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There are 3 modules in this course
In this foundational lesson, learners will explore the core architectural patterns that enable multiple AI agents to work together effectively. They'll examine different multi-agent system topologies, understand how agent specialization drives system performance, and analyze real-world implementations from leading organizations. Through hands-on activities, learners will practice designing agent roles and defining system boundaries for collaborative AI applications.
What's included
4 videos2 readings1 assignment
This lesson focuses on the critical infrastructure that enables reliable multi-agent collaboration. Learners will explore advanced communication protocols, design governance mechanisms for autonomous systems, and implement safety constraints and monitoring systems. Through real-world examples from industry leaders, they'll learn to balance agent autonomy with system reliability and ethical alignment.
What's included
3 videos1 reading1 assignment
In this final lesson, learners will apply their knowledge to build and deploy a functional multi-agent system prototype. They'll explore practical implementation frameworks, learn deployment strategies for production environments, and develop skills for monitoring and maintaining multi-agent systems at scale. The lesson culminates in a comprehensive capstone project where learners create their own multi-agent system addressing a real-world challenge.
What's included
4 videos1 reading3 assignments
Instructor
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