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Microsoft AI-200 Exam Syllabus Topics:

SectionWeightObjectives
Integrate backend services and build event-driven architectures25%- Build serverless APIs and workflows
  • 1. Azure Functions for AI integration and processing
  • 2. Orchestrate AI pipelines and workflows
- Implement messaging and event systems
  • 1. Azure Service Bus for reliable messaging
  • 2. Azure Event Grid for event-driven processing
  • 3. Connect services and expose APIs securely
Secure, monitor, and optimize AI solutions20%- Manage security and configuration
  • 1. Azure Key Vault for secrets, keys, and certificates
  • 2. Managed identities and access control
  • 3. App Configuration for dynamic settings
- Implement observability and reliability
  • 1. Optimize performance, cost, and scalability
  • 2. Logging, metrics, and distributed tracing
  • 3. OpenTelemetry and Azure Monitor integration
Develop AI solutions using Azure data services30%- Implement vector-enabled databases
  • 1. Azure Managed Redis for caching, streaming, and vector storage
  • 2. Azure Database for PostgreSQL with pgvector extension
  • 3. Azure Cosmos DB for NoSQL with vector search
- Design and optimize data access and retrieval
  • 1. Implement hybrid search and retrieval patterns
  • 2. Indexing strategies, query optimization, and consistency models
Develop containerized AI solutions on Azure25%- Implement container hosting environments
  • 1. Deploy to Azure Container Apps and Azure Kubernetes Service (AKS)
  • 2. Azure Container Registry: store, version, manage images
  • 3. Configure scaling, networking, and security for containers
- Monitor and troubleshoot containerized workloads
  • 1. Manage configurations and secrets for containers
  • 2. Log analysis, health checks, and performance monitoring

Microsoft Developing AI Cloud Solutions on Azure Sample Questions:

1. A container in an AKS cluster repeatedly restarts.
Pod events show probe failures, although node-level CPU and memory metrics are normal.
You need to diagnose the cause of the repeating restarts.
What should you do first?

A) Decrease the initialDelaySeconds for the container liveness probe.
B) Inspect the pod events and container logs.
C) Scale the deployment to more replicas.
D) Drain and reboot the node hosting the pod.


2. You store embeddings in a property named embedding in an Azure Cosmos DB for NoSQL container.
You must retrieve the five most similar documents to an input embedding.
You need to construct the similarity query.
What should you do?

A) Group by embedding value.
B) Enforce strong consistency.
C) Limit the number of results.
D) Use offset pagination.


3. You are deploying a model in Azure AI Foundry and must ensure the endpoint can handle unpredictable bursts of traffic while keeping cost low during idle periods. Which deployment type should you choose?

A) Standard (pay-as-you-go) deployment
B) Batch deployment
C) Provisioned Throughput Units (PTU)
D) Dedicated managed compute with fixed capacity


4. Drag and Drop Question
A Python API running in ACA must send distributed traces to Azure Monitor.
The API creates spans. However, no traces appear in Azure Monitor.
You need to configure the OpenTelemetry SDK pipeline to export traces to Azure Monitor.
What should you do? To answer, move the appropriate actions to the correct requirements. You may use each action once, more than once, or not at all. You may need to move the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.


5. You need to detect whether an uploaded image contains adult or violent content before allowing it to be posted to a public forum. What should you use?

A) Azure AI Document Intelligence
B) Azure AI Face API
C) Azure AI Custom Vision object detection
D) Azure AI Content Safety image moderation


Solutions:

Question # 1
Answer: B
Question # 2
Answer: C
Question # 3
Answer: A
Question # 4
Answer: Only visible for members
Question # 5
Answer: D

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