Microsoft AI-300 Value Pack (Frequently Bought Together)

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

You manage an Azure Machine Learning workspace named Workspace1 and an Azure Blob Storage accessed by using the URL https://storage1.blob.core.wmdows.net/data1.
You plan to create an Azure Blob datastore in Workspace1. The datastore must target the Blob Storage by using Azure Machine Learning Python SDK v2. Access authorization to the datastore must be limited to a specific amount of time.
You need to select the parameters of the Azure Blob Datastore class that will point to the target datastore and authorize access to it.
Which parameters should you use? To answer, select the appropriate options in the answer area NOTE: Each correct selection is worth one point.

You manage an Azure Machine Learning workspace named workspace1 by using the Python SDK v2.
The default datastore of workspace1 contains a folder named sample_data.
The folder structure contains the following content:

You write Python SDK v2 code to materialize the data from the files in the sample_data folder into a Pandas data frame.
You need to complete the Python SDK v2 code to use the MLTable folder as the materialization blueprint.
How should you complete the code? To answer, select the appropriate options in the answer area. NOTE:
Each correct selection is worth one point

When comparing prompt variants, the team plans to assess whether the generated responses are grammatically correct.
You need to evaluate the quality of the language from the generated responses.
Which evaluator should you use?

• A. Fluency
• B. Textual similarity
• C. Coherence
• D. Grounded ness

You have an Azure Machine Learning workspace that includes an AmICompute cluster and a batch endpoint.
You clone a repository that contains an MLflow model to your local computer. You need to ensure that you can deploy the model to the batch endpoint.
Solution: Add a compute resource to the workspace.
Does the solution meet the goal?

• A. Yes
• B. No