Multi-Agent AI Systems with Microsoft Azure

This course offers a comprehensive exploration of designing and implementing multi-agent architectures. Starting with an introduction to course concepts, students will learn to leverage the Semantic Kernel for effective agent architecture creation. Key lessons focus on agent orchestration, optimizing routing and data flow, and managing state within multi-agent environments. Advanced topics include orchestrating agents collaboratively and employing Retrieval Augmented Generation (RAG) to enhance data retrieval in agentic systems. The course culminates with a practical application of these concepts in the VectraBank project, showcasing agentic RAG tailored for banking applications.

Course

Intermediate
15 hours
Updated: Dec 16, 2025

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Unlimited access to hundreds of top-rated courses
Hands-on projects with expert feedback
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Program Certificates

Skills you'll learn

13 skills

Multi-Agent Implementation
Multi-Agent State Coordination Concepts
Implementing Multi-Agent State Management
Multi-Agent State Management Concepts
Implementing Multi-Agent State Coordination

Prerequisites

4 prerequisites

Prior to enrolling, you should have the following knowledge:

Implementing Database Interaction for AI Agents
Agent Tool Use
Implementing API Integration for Agents
Implementing Agent Memory

You will also need to be able to communicate fluently and professionally in written and spoken English.

Course Outline

16 lessons
1 project

Multi-Agent AI Systems with Microsoft Azure

Introduction to Multi-Agent AI Systems with Microsoft Azure
Get introduced to multi-agent systems, their real-world applications with Azure, course goals, and meet the expert instructors guiding your learning journey.
Designing Multi-Agent Architecture
Explain the core components of multi-agent systems and how to design their high-level architecture.
Creating Multi-Agent Designs
Explain the core components of multi-agent systems and how to design their high-level architecture.
Multi-Agent Architecture with Python
Develop a multi-agent system by coding the designed architecture and connecting agents with well-defined interfaces.
Implementing Multi-Agent Architecture with Semantic Kernel
Learn to build multi-agent AI systems with Semantic Kernel in Python, orchestrating specialized agents in parallel or sequence to solve complex smart city planning problems.
Orchestrating Agent Activities
Apply orchestration techniques to coordinate multiple agent actions and achieve complex workflows.
Implementing Agent Orchestration with Semantic Kernel
Learn to orchestrate specialized AI agents with Semantic Kernel using sequential, parallel, and conditional patterns for flexible, efficient multi-agent solutions.
Routing and Data Flow in Agentic Systems
Configure routing mechanisms to manage data flow among agents in multi-agent systems.
Implementing Routing and Data Flow in Agentic Systems with Semantic Kernel
Learn to build agentic systems with Semantic Kernel, using Azure SQL for persistent data, intelligent routing, and real-time, context-aware multi-agent responses.
State Management in Multi-Agent Systems
Evaluate methods for tracking and updating agent state across multi-turn interactions.
Implementing State Management in Multi-Agent Systems with Semantic Kernel
Learn to build collaborative multi-agent AI systems with Semantic Kernel, using shared state management and plugins for real-time, coordinated agent workflows.
Multi-Agent Orchestration and State Coordination
Develop a coordinated multi-agent system that synchronizes states for coherent task execution.
Implementing Multi-Agent Orchestration and State Coordination with Semantic Kernel
Learn to build multi-agent systems with a coordinator agent, shared state, and Semantic Kernel plugins for dynamic orchestration and workflow optimization, using a pasta factory simulation.
Multi-Agent Retrieval Augmented Generation
Extend RAG to multiple cooperating agents, each specialized in certain retrieval tasks.
Implementing Multi-Agent Retrieval Augmented Generation with Semantic Kernel
Learn to build and extend a multi-agent RAG system using Semantic Kernel, integrating specialized AI agents for robust, in-depth research with error handling and report persistence.

Project: VectraBank: Agentic RAG for Banking
Create a multi-agent system based on agentic RAG to handle customer queries in banking context.

Program Instructors

2 instructors

Unlike typical professors, our instructors come from Fortune 500 and Global 2000 companies and have demonstrated leadership and expertise in their professions:

Tawadros Nemer

Applied Scientist at Microsoft

Christopher Agostino

Founder and Research Scientist at NPC Worldwide

Tawadros Nemer

Applied Scientist at Microsoft

Christopher Agostino

Founder and Research Scientist at NPC Worldwide

About this program

Master Multi-Agent RAG with Microsoft Foundry and Azure OpenAI. Design agents that negotiate, retrieve across silos, and synthesize answers.

Subscription · Monthly

Cancel Anytime
Unlimited access to hundreds of top-rated courses
Hands-on projects with expert feedback
Personalized career coaching and interview prep
Program Certificates

Multi-Agent AI Systems with Microsoft Azure

Skills you'll learn

Prerequisites

Course Outline

Program Instructors

About this program

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