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Microsoft Operationalizing Machine Learning and Generative AI Solutions Sample Questions:

1. A team develops and manages a conversational assistant by using Microsoft Foundry.
The team must be able to validate that the assistant does not produce hateful responses before the application is exposed to any users.
You need to evaluate the model output for hateful responses as part of a repeatable validation process.
Which evaluator should you configure first?

A) Protected material
B) Indirect attacks
C) Content safety
D) Groundedness

2. An organization maintains separate Azure Machine Learning workspaces for development and production.
Both environments must use the same validated assets without duplicating them.
Assets must be shared across workspaces while maintaining centralized governance and version control.
You need to enable reuse of assets across workspaces without copying them.
What should you do?

A) Enable workspace-level Git integration and sync assets between repositories.
B) Publish the asset as a pipeline component.
C) Create a shared Azure Machine Learning environment that includes the asset.
D) Publish the asset to an Azure Machine Learning registry.

3. A team manages an Azure Machine Learning workspace and deploys a model to an endpoint.
A deployed online endpoint shows inconsistent response times during periods of high traffic.
You need to identify potential performance degradation.
Which three metrics should you monitor? Each correct answer presents part of the solution.
Choose three.
NOTE: Each correct selection is worth one point.

A) Dataset size
B) Request latency
C) Requests per minute
D) Feature count
E) Connections active

4. Drag and Drop Question
A team runs training jobs by using multiple Azure Machine Learning pipelines.
The team must ensure that all runs use the same Python packages and system libraries. The solution must allow dependency updates to be versioned without modifying training code.
You need to configure the workspace so that runtime dependencies are consistent and reusable.
Which four actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.

5. You manage a Microsoft Foundry project. You build a multi-turn chatbot application.
You plan to filter your traces to identify issues while observing how the application is responding.
The solution must not use an external knowledge base.
You need to select an evaluation metric.
Which built-in evaluator should you use?

A) RelevanceEvaluator
B) QAEvaluator
C) SimilarityEvaluator
D) CoherenceEvaluator

Solutions: