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Microsoft AI-200 Exam Syllabus Topics:

Microsoft Developing AI Cloud Solutions on Azure Sample Questions:

1. You deploy an AI application across multiple Azure regions.
The application must be able to view writes across all regions within a predictable time window.
You need to determine the appropriate consistency level.
What are two consistency levels you can use to achieve the goal? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.

A) Session
B) Bounded staleness
C) Eventual
D) Strong

2. You are developing an application that must extract structured field data (invoice number, total, vendor name) from scanned invoices in multiple layouts. You need a solution that requires no custom model training. What should you use?

A) Azure AI Language custom named entity recognition
B) Azure AI Document Intelligence custom neural model
C) Azure AI Vision Read API
D) Azure AI Document Intelligence prebuilt invoice model

3. You are building a multi-agent solution in Azure AI Foundry where one agent handles scheduling and another handles billing questions, and a request may need both. What should you implement?

A) A single monolithic prompt covering both domains
B) An orchestrator agent that routes sub-tasks to specialized agents and combines results
C) Two separate applications with no coordination
D) A single fine-tuned model trained on both domains only

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

5. You need to give an Azure OpenAI-based agent the ability to call a company's internal REST API to check order status during a conversation. What should you implement?

A) Azure AI Search vector index over order records
B) Prompt flow variant testing
C) Function calling (tools) with a defined JSON schema
D) Fine-tuning the model on order data

Solutions: