Artificial Intelligence and Machine Learning Courses

Microsoft AI-500T00: Design and Implement Multi-Agent AI Solutions

Length 4 days

Course overview

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Why study this course

This course focuses on the practical skills needed to architect and develop multi-agent AI solutions using Microsoft Foundry and Azure. It is intended for expert-level practitioners who have subject matter expertise in designing, building, and optimising scalable, production-ready, multi-agent AI systems, solutions, and workflows, and who work closely with developers, machine learning engineers, platform engineers, data scientists, and business stakeholders.

Students will learn how to design logical architecture for multi-agent solutions, build and integrate tool ecosystems, and implement multi-agent orchestration using Microsoft Foundry and Azure. The course emphasises the integration of monitoring, security, and governance, validating the ability to translate complex requirements into production-ready multi-agent solutions.

Aligns to certification

Microsoft Certified: Multi-Agent AI Solutions Expert

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What you’ll learn

Architect multi-agent solutions
Develop multi-agent solutions in Azure
Evaluate, optimise, and monitor multi-agent solutions
Implement text analysis solutions
Secure, govern, and deploy multi-agent solutions

Microsoft Azure at Lumify Work

As part of Lumify Group, Lumify Work has skilled more people in Microsoft technologies than any other organisation in Australia and New Zealand. We have a campus in the Philippines, too. We offer the broadest range of instructor-led training courses, from end user to architect level. We are proud to be the winner of the Microsoft MCT Superstars Award for FY24, which formally recognises us as having the highest quality Microsoft Certified Trainers in ANZ.

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Who is the course for?

This course is designed for expert-level practitioners who have subject matter expertise in designing, building, and optimising scalable, production‑ready, multi-agent AI systems, solutions and workflows.

Course subjects

Architect production-grade multi-agent AI solutions in Azure

Design stateful agentic loops with Microsoft Foundry agent service
Implement advanced multi-agent orchestration patterns in Microsoft Foundry
Apply task decomposition and agent collaboration strategies in Microsoft Foundry
Design enterprise-scale agent communication with A2A in Azure

Build production-grade multi-agent capabilities with Microsoft Foundry

Design advanced prompting strategies for production AI agents
Build enterprise-grade tool ecosystems with MCP and Microsoft Foundry
Implement advanced RAG pipelines with Azure AI Search and Microsoft Foundry
Design multi-agent memory architectures with Azure Cosmos DB

Deploy and govern enterprise agentic AI solutions on Azure

Implement CI/CD pipelines for multi-agent systems with GitHub Actions
Secure multi-agent systems with Azure zero-trust architecture
Scale responsible AI governance with Azure AI Content Safety and Microsoft Foundry
Govern the enterprise agent lifecycle in Microsoft Foundry

Monitor, evaluate, and operate multi-agent AI solutions in Azure

Implement distributed observability for multi-agent solutions with OpenTelemetry
Design evaluation frameworks for multi-agent solutions with Microsoft Foundry
Optimize multi-agent performance and cost in Microsoft Foundry
Design human-in-the-loop approval workflows with Power Automate and Microsoft Teams
Debug and respond to production multi-agent incidents in Azure

Prerequisites

Completion of AI-103: Develop AI Agents on Azure and AI-300: Operationalise Generative AI Applications (or equivalent experience).
Working experience with Microsoft Foundry Agent Service, including agent development, deployment, tool integration, and custom function/MCP tool consumption.
Familiarity with multi-agent orchestration patterns (sequential, concurrent, group chat, handoff) and basic knowledge of the A2A protocol and remote agent connectivity.
Experience with retrieval and grounding patterns, including classic RAG using Azure AI Search (hybrid search and semantic ranking).
Experience with system prompt design for agent persona and behaviour control.
Familiarity with Microsoft Foundry project deployment, agent evaluation workflows, and related portal capabilities.
Working experience with GitHub Actions for CI/CD pipeline design and implementation.
Knowledge of Azure security and identity services, including Azure Key Vault, Microsoft Entra ID, managed identities, RBAC, responsible AI principles, and Azure AI Content Safety guardrails.
Experience with observability and monitoring, including OpenTelemetry instrumentation and Azure Monitor / Log Analytics workspaces.
Basic familiarity with Power Automate workflow design.
Python programming proficiency, including asynchronous programming, REST API consumption, and use of the Azure AI SDK and Azure OpenAI SDK.

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Terms & Conditions

The supply of this course by Lumify Work is governed by the booking terms and conditions. Please read the terms and conditions carefully before enrolling in this course, as enrolment in the course is conditional on acceptance of these terms and conditions.

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