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Microsoft AI-200 Exam Syllabus Topics:

Microsoft Developing AI Cloud Solutions on Azure Sample Questions:

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

2. You need to add a custom voice that matches your company's brand for a text-to-speech feature, distinct from any standard neural voice. What should you use?

A) Azure AI Speech prebuilt neural voices
B) Azure AI Language sentiment analysis
C) Azure AI Translator
D) Azure AI Speech Custom Neural Voice

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. Your solution must answer questions about numeric data in large Excel-based reports (e.g.,
"What was Q3 revenue for the West region?"). Which approach is most appropriate?

A) Convert data to a structured table/SQL source and use a function-calling agent to query it
B) Store the Excel data as unstructured text and embed it for vector search
C) Use Azure AI Vision to read the spreadsheet as an image
D) Rely on the model's parametric knowledge

5. Your application stores conversation history so a multi-turn chatbot can reference earlier turns, but the context window is limited. You need to keep the most relevant history within token limits.
What should you implement?

A) Increase max_tokens for output only
B) Store history only in the client and never send it to the model
C) Truncate all history after 2 turns
D) Summarize older turns and retain recent turns verbatim

Solutions: