AI-500 Course | Design and Implementation of Multi-Agent AI Solutions
The official AI-500 course is aimed at professionals who wish to design, develop, and implement multi-agent artificial intelligence solutions using Microsoft Foundry and Azure. This advanced training provides the necessary skills 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 specifically designed for AI Engineers, developers, solution architects, and professionals specializing in Microsoft technologies who participate in advanced automation, enterprise artificial intelligence, and digital transformation initiatives.
AI-500 is the official training preparation for the Microsoft Certified: Multi-Agent AI Solutions Expert certification. Additionally, this is an official Microsoft course and is eligible for funding via FUNDAE for companies.
Course Overview
Multi-agent artificial intelligence represents one of the most significant advancements 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 competencies required to design scalable architectures, integrate business tools, implement advanced agent collaboration patterns, and operate artificial intelligence solutions prepared 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 as a gift. 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. Single-attempt exam available only in Virtual - Tele-training mode. Not applicable to the Self-Learning mode.
What is the value of the Multi-Agent AI Solutions Expert certification 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 competencies 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 projects involving advanced automation, intelligent assistants, business operations, and next-generation generative solutions.
Professional Applications of Multi-Agent AI Solutions Expert
The knowledge acquired in AI-500 enables participation 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 official Microsoft courses and certifications include at Nanfor
The training includes Microsoft Learn material, presentations by expert tutors, authorized labs, specialized tutoring, and certification preparation.
Nanfor combines official Microsoft content with expert guidance, enabling training oriented toward practical application in real business environments.
Learn about all 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 projects and collaborative agents in organizations across any sector.
- Enhancement of professional profile for roles related to artificial intelligence, advanced development, solution architecture, and digital transformation.
- Acquisition of practical knowledge about Microsoft Foundry, Azure, and next-generation artificial intelligence technologies.
- Preparation to obtain the Microsoft Certified: Multi-Agent AI Solutions Expert certification and prove specialized knowledge to clients and companies.
- Understanding of key aspects of security, governance, monitoring, and operation of enterprise artificial intelligence solutions.
- Ability to design scalable solutions that integrate multiple agents, tools, and services within complex corporate ecosystems.
Prerequisites
Previous 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 already working on AI, automation, or enterprise solution 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 undertake the Microsoft Certified: Multi-Agent AI Solutions Expert certification. During the training, the knowledge and competencies necessary to design, develop, integrate, deploy, and govern multi-agent artificial intelligence solutions in enterprise environments are covered.
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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 for?
This training is aimed at solution 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-level multi-agent artificial intelligence solutions in Azure.
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Unit 2: Creating production-level multi-agent capabilities 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 API Responses and Agents v2
- Agent reflection and planning cycles
- Session state and context management
- Fork-based sessions and resumption
- Migrating from Agents v1 to Agents v2
Lab:
- Designing stateful agentic loops with Microsoft Foundry Agent Service
- Migrating an Agents v1 pattern to Agents v2
- Deploying necessary resources in Microsoft Foundry
- Capturing evidence of conversations, reflection, and forks
Unit 2. Implementing multi-agent orchestration with Microsoft Foundry
Modules:
- Differentiating agentic and multi-agent architectures
- Analyzing advanced orchestration architectures
- Implementing hub-and-spoke orchestration
- Designing parallel execution and agent synchronization
- Comparing orchestration frameworks
Lab:
- Implementing advanced multi-agent orchestration patterns in Microsoft Foundry
- Creating versioned Agents v2 specialists
- Implementing a hub-and-spoke orchestrator
- Applying quorum rules
- Sending accepted evidence to a supervisor
Unit 3. Applying task decomposition and agent collaboration strategies in Microsoft Foundry
Modules:
- Designing prompt chaining flows
- Implementing dynamic and adaptive task decomposition
- Designing message schemas for agent handoffs
- Ensuring handoff reliability and context preservation
- Optimizing decomposition granularity
Lab:
- Applying task decomposition and agent collaboration strategies
- Completing a planner meta-agent in Agents v2
- Validating an AI-generated DAG
- Invoking specialists based on dependencies
- Transferring context via handoff
- Enabling evidence-based re-planning
Unit 4. Designing enterprise-scale agent communication using A2A in Azure
Modules:
- Designing large-scale A2A agent ecosystems
- Implementing distributed shared state management
- Designing context isolation and sharing strategies
- Developing conflict detection and resolution mechanisms
- Resolving conflicts and maintaining audit traceability
Lab:
- Designing enterprise agent communication with A2A in Azure
- Creating A2A-compatible endpoints
- Registering agents in Azure Cosmos DB
- Implementing capability-based routing
- Managing distributed state using ETags
- Logging conflict decisions in an audit trail
Unit 5. Designing advanced prompting strategies for AI agents in production
Modules:
- Designing multi-turn reasoning architectures
- Implementing defenses against prompt injection
- Building system prompt frameworks for agent control
- Designing multi-level guardrail architectures
- Implementing prompt versioning and optimization
- Automating prompt regression and optimization
- Designing fine-tuning strategies and data pipelines
Lab:
- Designing advanced prompting strategies for AI agents
- Comparing prompt versions
- Applying guardrails in Python
- Protecting against prompt injection
- Managing behavior limits and scaling
Unit 6. Building enterprise tool ecosystems with MCP and Microsoft Foundry
Modules:
- Designing MCP contracts, hosting, authorization, and observability
- Implementing eligible routing and controlled reliability policies
- Governing compatibility, versioning, migration, and retirement
Lab:
- Building an enterprise MCP ecosystem
- Completing a FastMCP server
- Developing MCP clients with dynamic discovery
- Selecting compatible tools using a catalog
- Validating results
- Testing fallback mechanisms
Unit 7. Implementing advanced RAG pipelines with Azure AI Search and Microsoft Foundry
Modules:
- Designing hybrid search architectures
- Implementing reranking and contextual ranking
- Designing dynamic routing of knowledge sources
- Optimizing chunking and embedding strategies
Lab:
- Implementing advanced RAG with Azure AI Search
- Comparing embedding profiles
- Comparing chunking techniques
- Evaluating query modes
- Analyze routing strategies
Module 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 retention and auditable deletion
Module 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 inter-agent compatibility
- Execute Canary deployments
- Perform controlled rollbacks
Module 10. Securing Multi-Agent Systems via Zero Trust Architecture in Azure
Modules:
- Apply Zero Trust identity to agent networks
- Secure access via JIT and workload identity
- Design authentication flows and secret lifecycles
- Prevent lateral movement in agent networks
- Implement context propagation and multi-tenant 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
Module 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 complete process
Module 12. Managing Enterprise Agent Lifecycles in Microsoft Foundry
Modules:
- Design agent versioning and approval
- Implement quotas and rate limiting
- Design imputation 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
Module 13. Implementing Distributed Observability for Multi-Agent Solutions with OpenTelemetry
Modules:
- Design distributed tracing 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
Module 14. Designing Evaluation Frameworks for Multi-Agent Solutions with Microsoft Foundry
Modules:
- Define multi-agent success metrics
- Implement evaluation via 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
Module 15. Optimizing 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 performance and cost of multi-agent systems
- Implement intelligent routing
- Apply result caching
- Manage context budgets
- Evaluate evidence-based configurations
Module 16. Debugging and Incident Response for Multi-Agent Production in Azure
Modules:
- Implement agent replay for debugging
- Design root cause analysis
- Configure automated 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 incorporates official Microsoft labs that allow applying the acquired knowledge 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-life situations.
Course language
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Course: English / Spanish
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Labs: English / Spanish
Do you 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. If you have any questions, please contact us.
If you want to take it in a classroom or telepresence modality, please contact us:
Nanfor, official Microsoft ICT training center
Nanfor is a custom ICT training center, specialized in technological training for professionals and companies, and 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 updating, 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 an 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 for?
The Microsoft Certified: Multi-Agent AI Solutions Expert certification allows you to demonstrate knowledge in 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 funding via FUNDAE?
Yes. The AI-500 course can be eligible for funding through FUNDAE 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 the AI-500 course?
Prior 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.
