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Microsoft AI-200 Exam Syllabus Topics:

Microsoft Developing AI Cloud Solutions on Azure Sample Questions:

1. You need to ensure that responses from your Azure OpenAI application include citations back to the specific source documents used, to support user trust and verification. What should you implement?

A) Use only the base model with no retrieval
B) Increase top_p to broaden token sampling
C) Configure the RAG pipeline to return retrieved document metadata (source, page) alongside generated answers and instruct the model to cite them
D) Enable higher content filter severity

2. You develop a message-processing service deployed to Azure Container Apps. The service reads messages from an Azure Service Bus queue.
The solution must minimize costs by ensuring NO compute resources are consumed when the queue is empty.
You need to configure scaling for the service.
Which two actions should you perform? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.

A) Configure the scaling rule to allow for the termination of all active replicas.
B) Increase the scaling rule to allow for the maximum running replica count.
C) Enable HTTP ingress concurrency scaling.
D) Configure a Kubernetes Event-driven Autoscaler rule that monitors queue length.

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

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

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

Solutions: