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AI-500 Course | Design and Implementation of Multi-Agent AI Solutions
The official AI-500 course is aimed at professionals who want to design, develop, and implement multi-agent artificial intelligence solutions using Microsoft Foundry and Azure. This advanced training allows you to acquire the skills needed to build modern enterprise architectures based on intelligent agents capable of collaborating, coordinating complex processes, and integrating with corporate services and tools.
Throughout the course, you will learn to design multi-agent ecosystems, implement orchestration strategies, develop production-ready solutions, and apply monitoring, security, and governance mechanisms for enterprise artificial intelligence projects.
The training is especially aimed at AI Engineers, developers, solutions architects, and professionals specializing in Microsoft technologies who are involved in advanced automation, enterprise artificial intelligence, and digital transformation initiatives.
AI-500 is the official training to prepare for the Microsoft Certified: Multi-Agent AI Solutions Expert certification. In addition, this course is official from Microsoft and eligible for FUNDAE subsidies for companies.
Course Overview
Multi-agent artificial intelligence represents one of the most significant advances in the evolution of AI applied to enterprise environments. Organizations need solutions capable of coordinating multiple intelligent agents that collaborate with each other to automate tasks, make decisions, interact with external systems, and respond to increasingly complex needs.
The AI-500 course provides the skills needed to design scalable architectures, integrate enterprise tools, implement advanced agent collaboration patterns, and operate artificial intelligence solutions ready for real-world production scenarios using Microsoft Foundry and Azure.
The training combines knowledge of architecture, governance, integration, observability, and operations so that professionals can develop robust, secure solutions aligned with business requirements.
Virtual course with certification exam included free of charge. Don't miss this opportunity! The exam is valued at €126 + VAT and is included at no additional cost.
Promotion valid until December 31, 2026. One-attempt exam available only in Virtual - Distance Learning format.
What is the Multi-Agent AI Solutions Expert certification used for in a professional environment?
The Microsoft Certified: Multi-Agent AI Solutions Expert certification demonstrates the ability to design and implement enterprise solutions based on multiple intelligent agents using the latest Microsoft technologies.
This accreditation validates skills related to multi-agent system architecture, tool integration, intelligent process orchestration, the application of security controls, and the monitoring of solutions deployed in production environments.
For companies and professionals, having specialized knowledge in multi-agent artificial intelligence provides a competitive advantage in advanced automation, intelligent assistants, business operations, and next-generation generative solutions projects.
Professional Applications of Multi-Agent AI Solutions Expert
The knowledge acquired in AI-500 allows you to participate in projects related to:
- Design of multi-agent enterprise architectures.
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Intelligent automation of complex processes.
- Implementation of solutions based on Microsoft Foundry.
- Integration of agents with Azure services.
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Governance and observability of artificial intelligence solutions.
- Development of AI-powered enterprise applications.
- Orchestration of multiple agents for corporate scenarios.
- Innovation projects based on generative artificial intelligence.
What Microsoft Official Courses and Certifications Include at Nanfor
The training includes Microsoft Learn material, presentations by expert instructors, authorized labs, specialized tutoring, and certification preparation.
Nanfor combines Microsoft's official content with expert guidance, allowing for training focused on practical application in real business environments.
Learn all the components
Advantages of AI-500 Training
- Specialization in one of the fastest-growing areas within enterprise artificial intelligence: multi-agent systems.
- Development of advanced skills to design AI architectures ready for production environments.
- Ability to participate in intelligent automation and collaborative agent projects in organizations across any sector.
- Enhancement of your professional profile for positions related to artificial intelligence, advanced development, solutions architecture, and digital transformation.
- Acquisition of practical knowledge about Microsoft Foundry, Azure, and cutting-edge artificial intelligence technologies.
- Preparation to earn the Microsoft Certified: Multi-Agent AI Solutions Expert certification and demonstrate specialized knowledge to clients and companies.
- Understanding key aspects of security, governance, monitoring, and the operation of enterprise artificial intelligence solutions.
- Ability to design scalable solutions that integrate multiple agents, tools, and services within complex corporate ecosystems.
Prerequisites
Prior experience in application development, artificial intelligence, and cloud platforms is recommended. It is also advisable to have knowledge of Python, Azure, and concepts related to modern enterprise architectures.
Professionals who already work on AI, automation, or enterprise solutions development projects will get the most out of the training.
Preparation for the Microsoft Multi-Agent AI Solutions Expert Certification
AI-500 is designed to prepare professionals to confidently tackle the Microsoft Certified: Multi-Agent AI Solutions Expert certification. During the training, you will develop the knowledge and skills needed to design, develop, integrate, deploy, and govern multi-agent artificial intelligence solutions in enterprise environments.
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Course duration:
100 hours
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Classroom access:
3 months
General Course Information
Who is the Microsoft AI-500 course aimed at?
This training is aimed at solutions architects, developers, AI Engineers, Azure specialists, and professionals responsible for designing and implementing enterprise solutions based on artificial intelligence.
It is also suitable for experts involved in innovation, advanced automation, and generative artificial intelligence projects.
AI-500 Course Objectives and What You Will Learn
- Design multi-agent artificial intelligence architectures.
- Implement solutions using Microsoft Foundry.
- Develop advanced orchestration strategies.
- Integrate enterprise tools and services.
- Apply observability and monitoring models.
- Implement security and governance controls.
- Deploy scalable solutions in Azure.
- Prepare for the associated official certification.
Elements of the Microsoft Learn Multi-Agent AI Solutions Expert Collection
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Unit 1: Designing production-ready multi-agent artificial intelligence solutions in Azure.
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Unit 2: Creating production-ready multi-agent features with Microsoft Foundry.
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Unit 3: Implementing and governing enterprise artificial intelligence solutions in Azure.
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Unit 4: Monitoring, evaluating, and operating multi-agent artificial intelligence solutions in Azure.
AI-500 Course Content
Unit 1. Designing Agentic Loops with Microsoft Foundry Agent Service
Modules:
- Agentic loop architecture for production environments
- Foundry and Agents v2 API Responses
- Agent reflection and planning cycles
- Session state and context management
- Branching and resumption-based sessions
- Migrating from Agents v1 to Agents v2
Lab:
- Design stateful agentic loops using Microsoft Foundry Agent Service
- Migrate an Agents v1 pattern to Agents v2
- Deploy the necessary resources in Microsoft Foundry
- Capture evidence of conversations, reflection, and branching
Unit 2. Implementing Multi-Agent Orchestration with Microsoft Foundry
Modules:
- Differentiate between agentic and multi-agent architectures
- Analyze advanced orchestration architectures
- Implement hub-and-spoke orchestration
- Design parallel execution and agent synchronization
- Compare orchestration frameworks
Lab:
- Implement advanced multi-agent orchestration patterns in Microsoft Foundry
- Create versioned Agents v2 specialists
- Implement a hub-and-spoke orchestrator
- Apply quorum rules
- Send accepted evidence to a supervisor
Unit 3. Applying Task Decomposition and Agent Collaboration Strategies in Microsoft Foundry
Modules:
- Design prompt chaining flows
- Implement dynamic and adaptive task decomposition
- Design message schemas for handoffs between agents
- Ensure handoff reliability and context preservation
- Optimize decomposition granularity
Lab:
- Apply task decomposition and agent collaboration strategies
- Complete a planner meta-agent in Agents v2
- Validate an AI-generated DAG
- Invoke specialists based on dependencies
- Transfer context via handoff
- Enable evidence-based replanning
Unit 4. Designing Enterprise-Scale Agent Communication Using A2A in Azure
Modules:
- Design large-scale A2A agent ecosystems
- Implement distributed shared state management
- Design context isolation and sharing strategies
- Develop conflict detection and resolution mechanisms
- Resolve conflicts and maintain audit traceability
Lab:
- Design enterprise agent communication using A2A in Azure
- Create A2A-compatible endpoints
- Register agents in Azure Cosmos DB
- Implement capability-based routing
- Manage distributed state using ETags
- Record conflict decisions in the audit log
Unit 5. Designing Advanced Prompting Strategies for Production AI Agents
Modules:
- Design multi-turn reasoning architectures
- Implement defenses against prompt injection
- Build system prompt frameworks for agent control
- Design multi-level guardrail architectures
- Implement prompt versioning and optimization
- Automate prompt regression and optimization
- Design fine-tuning and data pipeline strategies
Lab:
- Design advanced prompting strategies for AI agents
- Compare prompt versions
- Apply guardrails in Python
- Protect against prompt injection
- Manage behavior and scaling limits
Unit 6. Building Enterprise Tool Ecosystems with MCP and Microsoft Foundry
Modules:
- Design MCP contracts, hosting, authorization, and observability
- Implement eligible routing and controlled reliability policies
- Govern compatibility, versioning, migration, and deprecation
Lab:
- Build an enterprise MCP ecosystem
- Complete a FastMCP server
- Develop MCP clients with dynamic discovery
- Select compatible tools using a catalog
- Validate results
- Test fallback mechanisms
Unit 7. Implementing Advanced RAG Pipelines with Azure AI Search and Microsoft Foundry
Modules:
- Design hybrid search architectures
- Implement reranking and contextual ranking
- Design dynamic knowledge source routing
- Optimize chunking and embedding strategies
Lab:
- Implement advanced RAG with Azure AI Search
- Compare embedding profiles
- Compare chunking techniques
- Evaluate query modes
- Analyze routing strategies
Unit 8. Designing Multi-Agent Memory Architectures with Azure Cosmos DB
Modules:
- Analyze memory architecture patterns
- Implement semantic memory with vector storage
- Optimize memory retrieval and injection
- Configure context window optimization
- Design memory retention and consolidation
- Apply privacy and audit compliance
Lab:
- Build a Foundry agent with persistent memory in Cosmos DB
- Implement a custom memory layer
- Manage shared preferences
- Ensure patient isolation
- Manage auditable retention and deletion
Unit 9. Implementing CI/CD pipelines for multi-agent systems with GitHub Actions
Modules:
- Design multi-agent deployment pipelines
- Implement progressive deployment strategies
- Configure differentiated deployment environments
- Automate rollback procedures
Lab:
- Implement CI/CD for a multi-agent system
- Provision Foundry and Container Apps with Bicep
- Validate compatibility between agents
- Execute Canary deployments
- Perform a controlled rollback
Unit 10. Protecting multi-agent systems using Zero Trust architecture in Azure
Modules:
- Apply Zero Trust identity to agent networks
- Protect access using JIT and workload identity
- Design authentication flows and secret lifecycles
- Prevent lateral movement in agent networks
- Implement context propagation and multitenant isolation
- Validate tenant boundaries and encryption
- Configure regulatory compliance controls
Lab:
- Apply Zero Trust to a Microsoft Foundry multi-agent flow
- Implement allowlists between agents
- Validate tenant boundaries
- Apply least-privilege identities
- Generate compliance evidence
Unit 11. Scaling Responsible AI governance with Azure AI Content Safety and Microsoft Foundry
Modules:
- Design bias and fairness monitoring
- Implement transparency and explainability
- Configure privacy in multi-agent flows
- Establish audit and accountability frameworks
Lab:
- Govern a multi-agent code review in Foundry
- Deploy models with guardrails
- Implement compliance gates
- Apply fairness and privacy rules
- Manage auditing of the entire process
Unit 12. Governing the enterprise agent lifecycle in Microsoft Foundry
Modules:
- Design agent versioning and approval
- Implement quotas and usage limits
- Design attribution and chargeback models
- Establish retirement and obsolescence processes
Lab:
- Govern the lifecycle of a multi-agent topology
- Inventory Foundry agents
- Implement approval gates
- Manage usage controls
- Execute controlled version retirements
Unit 13. Implementing distributed observability for multi-agent solutions with OpenTelemetry
Modules:
- Design distributed traceability for multi-agent solutions
- Implement structured logging for agent decisions
- Configure telemetry aggregation and dashboards
- Build anomaly detection for agent behavior
Lab:
- Trace multi-agent flows using OpenTelemetry
- Create distributed spans
- Propagate W3C traceparent context
- Configure alerts in Azure Monitor
- Analyze performance and consumption anomalies
Unit 14. Designing evaluation frameworks for multi-agent solutions with Microsoft Foundry
Modules:
- Define multi-agent success metrics
- Implement evaluation using LLM-as-Judge
- Design synthetic test sets
- Build regression pipelines to detect drift
Lab:
- Build a quality gate for multi-agent evaluation
- Create custom evaluators
- Calibrate LLM judges with human evaluations
- Apply deterministic thresholds
- Block regressions before deployment
Unit 15. Optimizing the performance and cost of multi-agent systems in Microsoft Foundry
Modules:
- Design model routing for agent ecosystems
- Implement multi-level caching strategies
- Optimize token and context usage
- Balance quality, cost, and latency
Lab:
- Optimize the performance and cost of multi-agent systems
- Implement intelligent routing
- Apply result caching
- Manage context budgets
- Evaluate configurations based on evidence
Unit 16. Debugging and responding to multi-agent production incidents in Azure
Modules:
- Implement agent replay for debugging
- Design root cause analysis
- Configure automatic incident detection and remediation
- Establish response and postmortem processes
Lab:
- Debug a multi-agent production incident
- Capture distributed traces
- Execute replay without side effects
- Validate root cause hypotheses
- Generate a blameless postmortem
Our differentiator: Official Microsoft Labs
AI-500 includes official Microsoft labs that allow you to apply the knowledge acquired in practical scenarios related to the design, deployment, and operation of multi-agent solutions. Thanks to these environments, participants can reinforce their learning through practical experiences aligned with real-world situations.
Course language
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Course: English / Spanish
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Labs: English / Spanish
Want to take this course? Request information now
If you want to take this training virtually, you can purchase it at the top of the product page. If you have any questions, please contact us.
If you want to take it in person or remotely, please contact us:
Nanfor, Microsoft's official IT training center
Nanfor is a custom IT training center specializing in technology training for professionals and businesses, and it is officially accredited by Microsoft as:
- Microsoft Solutions Partner – Training Services
- Microsoft Cloud Partner
These accreditations certify that Nanfor meets Microsoft's standards for delivering technical courses using Microsoft content and Microsoft Certified Trainers (MCTs), ensuring quality, continuous updates, and alignment with certifications.
Frequently asked questions about the AI-500 course
What is the Microsoft Foundry and Azure AI-500 course?
The AI-500 course is official Microsoft training focused on the design and implementation of multi-agent artificial intelligence solutions using Microsoft Foundry and Azure. It is aimed at professionals who need to develop advanced enterprise architectures based on intelligent agents.
What is the Multi-Agent AI Solutions Expert certification associated with the AI-500 course used for?
The Microsoft Certified: Multi-Agent AI Solutions Expert certification certifies knowledge for designing, implementing, and operating enterprise multi-agent artificial intelligence solutions using Microsoft Foundry and Azure technologies.
Is the AI-500 course an official Microsoft course?
Yes. AI-500 is an official Microsoft course and follows the content and learning objectives defined by Microsoft for preparing for the associated certification.
What is the difference between AI-500 and other Microsoft certifications related to artificial intelligence?
AI-500 specializes in the design and implementation of multi-agent artificial intelligence solutions using Microsoft Foundry and Azure. Its focus is on advanced architectures, orchestration, integration, monitoring, security, and governance of multi-agent systems.
Is the AI-500 course eligible for FUNDAE funding?
Yes. The AI-500 course may be eligible for FUNDAE funding for companies that meet the requirements established by current regulations.
How long is the Microsoft AI-500 course?
The total duration of the AI-500 course is 100 hours, and access to the virtual campus is available for 3 months.
Is the AI-500 course included in Nanfor's LaaS Cert?
Yes. AI-500 is part of the catalog available in LaaS Cert, Nanfor's annual continuous training license that allows access to multiple courses and certifications for one year.
What technical level is recommended for taking the AI-500 course?
Previous experience in application development, Python programming, Azure services, and initiatives related to artificial intelligence and cloud architectures is recommended.
What career opportunities does the Microsoft AI-500 course offer?
The training is especially useful for AI Engineers, Solution Architects, developers, Azure specialists, and professionals involved in enterprise artificial intelligence projects, advanced automation, and multi-agent solutions.
