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Microsoft AI-500 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|
| Topic 1: Architect multi-agent solutions | 15-20% | - Design logical architecture for multi-agent solutions
- 1. Decompose goals into workflows, agents, and tools
- 2. Specify observability components including tracing, structured logging, and replay
- 3. Select developer tools and environments for the software development lifecycle
- 4. Specify compute components for scalability, reliability, security, and cost optimization
- 5. Specify monitoring components for coordination, drift detection, and remediation
- 6. Design workflows with agents, subagents, control loops, and human-in-the-loop
|
| Topic 2: Develop multi-agent solutions in Azure | 30-35% | - Build and integrate tool ecosystems
- 1. Design and build MCP servers and clients
- 2. Implement tool validation, error handling, and fallback mechanisms
- 3. Integrate external tools and function calling
- Design and implement advanced prompt engineering strategies
- 1. Implement agent and model fine-tuning strategies
- 2. Implement advanced prompting techniques
- 3. Design context-aware agent behaviors
- Implement multi-agent orchestration
- 1. Implement human-in-the-loop processes
- 2. Implement orchestration patterns
- 3. Integrate agents using Agent2Agent and MCP
- 4. Implement tracing with Microsoft Foundry
- 5. Design reusable middleware
- 6. Implement scalable concurrent execution
- 7. Optimize token usage and cost management
- 8. Design caching strategies
- 9. Use Microsoft Agent Framework, LangChain, LangGraph, and Hugging Face Transformers
- 10. Monitor availability, performance, and SLA compliance
- Design and implement agent memory, context management, and knowledge integration
- 1. Design multi-agent RAG architectures
- 2. Implement memory strategies
- 3. Implement knowledge integration using search, MCP, and semantic search
- 4. Implement context management across agents
|
| Topic 3: Evaluate, optimize, and monitor multi-agent solutions | 20-25% | - Evaluate solution quality
- 1. Evaluate workflows and orchestration
- 2. Measure agent performance and quality
- Optimize operational performance
- 1. Monitor production workloads and operational health
- 2. Optimize latency, throughput, and token consumption
|
| Topic 4: Secure, govern, and deploy multi-agent solutions | 20-25% | - Design and implement security
- 1. Apply shift-left security practices
- 2. Implement authentication and authorization
- 3. Manage secrets with Azure Key Vault
- 4. Implement identity, RBAC, and network security
- Design and implement guardrails
- 1. Implement guardrails for inputs, tools, and outputs
- 2. Validate guardrails with testing and synthetic data
- 3. Design custom guardrails
- Deploy multi-agent solutions to Azure
- 1. Design testing strategies
- 2. Choose deployment and release methodologies
- 3. Implement CI/CD and infrastructure as code
- 4. Implement multi-environment release strategies
|
