Microsoft AI-300 - Operationalizing Machine Learning and Generative AI Solutions Exam
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Total 170 questions
Question #11 (Topic: Topic 1, Design and implement an MLOps infrastructure
)
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?
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.
Answer: D
Question #12 (Topic: Topic 1, Design and implement an MLOps infrastructure
)
An Azure Machine Learning workspace processes sensitive training data.
The workspace must NOT be accessible from the public internet.
You need to restrict network access.
Which configuration should you implement?
The workspace must NOT be accessible from the public internet.
You need to restrict network access.
Which configuration should you implement?
A. Azure Firewall rules
B. Private endpoints
C. Network security groups
D. Service endpoints
Answer: B
Question #13 (Topic: Topic 1, Design and implement an MLOps infrastructure
)
A team is experimenting with traditional models for a classification workflow in Azure Machine Learning.
The team requires a consistent way to manage assets that are created during experimentation.
You need to ensure that artifacts can be reused and governed across projects.
Which asset should you register?
The team requires a consistent way to manage assets that are created during experimentation.
You need to ensure that artifacts can be reused and governed across projects.
Which asset should you register?
A. Model
B. Component
C. Environment
D. Pipeline
Answer: B
Question #14 (Topic: Topic 1, Design and implement an MLOps infrastructure
)
HOTSPOT
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
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
Answer: 
Question #15 (Topic: Topic 1, Design and implement an MLOps infrastructure
)
HOTSPOT
You manage an Azure Machine Learning workspace named workspace1 by using the Python SDK v2. You create a General Purpose v2 Azure storage account named mlstorage1. The storage account includes a publicly accessible container named mlcontainer1. The container stores 10 blobs with files in the CSV format.
You must develop Python SDK v2 code to create a data asset referencing all blobs in the container named mlcontainer1.
You need to complete the Python SDK v2 code.
How should you complete the code? 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. You create a General Purpose v2 Azure storage account named mlstorage1. The storage account includes a publicly accessible container named mlcontainer1. The container stores 10 blobs with files in the CSV format.
You must develop Python SDK v2 code to create a data asset referencing all blobs in the container named mlcontainer1.
You need to complete the Python SDK v2 code.
How should you complete the code? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer: 
