Building multi-agent systems

Overview

Google, IBM & Meta Certificates — All 10,000+ Courses at 40% Off

One annual plan covers every course and certificate on Coursera. 40% off for a limited time.

This course is designed to elevate skilled developers into multi-agent system architects. You'll learn to design and implement collaborative AI systems. The course focuses on building scalable, production-ready systems, ensuring responsible AI, and applying enterprise security and integration patterns. You'll complete a project where specialized agents work together to solve a complex business problem. By the end of this course, you will be able to: - Design and document sophisticated multi-agent architectures for enterprise applications. - Build and orchestrate multi-agent systems using the AutoGen framework. - Implement enterprise-grade security with Azure Entra ID and integrate with SharePoint. - Deploy and monitor multi-agent systems using Docker and understand Kubernetes requirements. - Apply Microsoft's responsible AI principles.

Syllabus

Multi-agent system concepts and applications

Learn to think beyond single agents by analyzing real-world multi-agent implementations and designing systems where specialized agents collaborate effectively. You'll create professional architecture documentation using industry-standard tools and implement communication protocols that ensure reliable coordination between agents.

AutoGen framework implementation

Build sophisticated multi-agent systems using Microsoft's AutoGen framework to orchestrate conversations and task delegation between specialized agents. You'll implement group chat patterns for business scenarios, create intelligent task distribution systems, and add human oversight for critical decisions.

Enterprise integration and security

Ensure your multi-agent systems are enterprise-ready by applying Microsoft's Responsible AI principles and implementing security fundamentals. You'll build basic authentication with Azure Entra ID, create SharePoint integrations, and navigate the complex decisions required for enterprise AI deployments.

Deployment and monitoring

Take your multi-agent systems to production by implementing containerized deployments and comprehensive monitoring strategies. You'll create Docker containers, explore Kubernetes orchestration, design scaling strategies, and compile a complete portfolio demonstrating your mastery of AI agent development from single agents to distributed systems.