AI-200 dumps materials - exam dumps for AI-200: Developing AI Cloud Solutions on Azure

Microsoft Developing AI Cloud Solutions on Azure - AI-200 certification

Exam Code: AI-200

Exam Name: Developing AI Cloud Solutions on Azure

Updated: Jul 24, 2026

Q & A: 93 Questions and Answers

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Microsoft AI-200 Exam Syllabus Topics:

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

Microsoft Developing AI Cloud Solutions on Azure Sample Questions:

1. Your chat application calls Azure OpenAI Service. You need to prevent the model from returning content that promotes self-harm, even if the prompt is crafted to bypass instructions. What should you configure?

A) Azure AI Content Safety filters on the Azure OpenAI resource
B) A lower max_tokens value
C) Azure AI Search semantic ranking
D) A system message instructing the model to refuse harmful topics


2. You are developing a Java application to be deployed in Azure. The application stores sensitive data in Azure Cosmos DB.
You need to configure Always Encrypted to encrypt the sensitive data inside the application.
What should you do first?

A) Create a new container to include an encryption policy with the JSON properties to be encrypted.
B) Create a data encryption key (DEK) by using the Azure Cosmos DB SDK and store the key in Azure Cosmos DB.
C) Create a Microsoft Entra ID managed identity and assign the identity to a new Azure Key Vault instance.
D) Create a customer-managed key (CMK) and store the key in a new Azure Key Vault instance.


3. You are evaluating a fine-tuned Azure OpenAI model against the base model before promoting it to production. Which Azure AI Foundry capability should you use?

A) Azure AI Search indexer scheduling
B) Azure Monitor Application Insights only
C) Content Safety category configuration
D) Prompt flow bulk testing / evaluation with metrics (groundedness, coherence, relevance)


4. A development team wants to compare multiple prompt variations against the same test dataset and visualize which prompt performs best. What should they use in Azure AI Foundry?

A) Speech Studio custom voice
B) Model deployment quota management
C) Azure AI Search indexers
D) Prompt flow with variants


5. You deploy multiple instances of a change feed processor to handle a high ingestion rate within Azure Cosmos DB for NoSQL.
Each processor instance must process a different subset of partitions.
You need to ensure the workload is load-balanced across all processor instances.
What should you configure?

A) indexing precision
B) lease container
C) autoscale throughput
D) strong consistency


Solutions:

Question # 1
Answer: A
Question # 2
Answer: D
Question # 3
Answer: D
Question # 4
Answer: D
Question # 5
Answer: B

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