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Microsoft Operationalizing Machine Learning and Generative AI Solutions Sample Questions:

1. You deploy a model to production but do not have labeled data available for evaluating prediction accuracy. However, you must monitor model health continuously. What is the BEST strategy?

A) Use data drift detection
B) Perform manual evaluation only
C) Monitor accuracy metrics
D) Disable monitoring

2. An organization is deploying several generative AI workloads by using Microsoft Foundry. Each workload must meet different requirements related to data governance, task specialization, and operational cost control.
The organization requires models that meet the following requirements:
- Model behavior aligns with the task being performed.
- Data handling aligns with internal governance policies.
- Operational complexity and cost are justified by workload needs.
You need to select the foundation model options that meet the requirements.
Which three models can you select? Each correct answer presents a complete solution. Choose three.
NOTE: Each correct selection is worth one point.

A) The smallest available model to minimize the usage cost
B) The largest available model to simplify operational management
C) A model that offers enterprise governance controls when workloads process regulated business data
D) A model that supports multiple input types when workloads require combined text and image analysis
E) A model that is optimized for conversational reasoning when deploying an interactive assistant

3. A company's platform engineers manage the resource settings and governance of Microsoft Foundry.
Developers must be able to create and update project assets but must not be able to change resource-level configurations.
You need to enforce least privilege access for the engineers and developers.
Which two actions should you perform? Each correct answer presents part of the solution.
Choose two.
NOTE: Each correct selection is worth one point.

A) Disable Microsoft Entra ID authentication for the Microsoft Foundry resource.
B) Assign the Azure AI Developer role to the developers.
C) Share a single API key across all teams.
D) Assign a resource-level Azure AI Administrator role to the platform engineers.

4. A team plans to deploy a large foundation model in Microsoft Foundry as part of a new enterprise AI capability.
Different business units across the team's organization will access the model from various internal applications.
You need to deploy a foundation model by minimizing latency.
Which deployment type should you use?

A) Data Zone Batch
B) Global Batch
C) Developer
D) Data Zone Standard

5. You have a deployment of an Azure OpenAI Service base model.
You plan to fine-tune the model.
You need to prepare a file that contains training data.
Which file format should you use?

A) JSON
B) CSV
C) JSONL
D) TSV

Solutions: