Microsoft DP-100 Designing and Implementing a Data Science Solution on Azure Exam Practice Test

You manage an Azure Machine Learning workspace. The development environment for managing the workspace is configured to use Python SDK v2 in Azure Machine Learning Notebooks.

A Synapse Spark Compute is currently attached and uses system-assigned identity.

You need to use Python code to update the Synapse Spark Compute to use a user-assigned identity.

Solution: Initialize the DefaultAzureCredential class.

Does the solution meet the goal?

You manage an Azure Machine Learning workspace named projl

You plan to use assets defined in projl to create a pipeline in the Machine Learning studio designer

You need to set the Registry name filter to display only the list of assets defined in projl.

What should you set the Registry name filter to?

You manage an Azure Machine Learning workspace. You design a training job that is configured with a serverless compute. The serverless compute must have a specific instance type and count

You need to configure the serverless compute by using Azure Machine Learning Python SDK v2. What should you do?

You manage an Azure Machine Learning workspace named Workspace1.

You plan to create a pipeline in the Azure Machine Learning Studio designer. The pipeline must include a custom component You need to ensure the custom component can be used in the pipeline. What should you do first.

You use Azure Machine Learning Designer lo load the following datasets into an experiment:

Dataset1:

Dataset2:

You need to create a dataset that has the same columns and header row as the input datasets and contains all rows from both input datasets.

Solution: Use the Add Rows component.

Does the solution meet the goal?

Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.

After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.

You have an Azure Machine Learning workspace. You connect to a terminal session from the Notebooks page in Azure Machine Learning studio.

You plan to add a new Jupyter kernel that will be accessible from the same terminal session.

You need to perform the task that must be completed before you can add the new kernel.

Solution: Create an environment.

Does the solution meet the goal?

You have an Azure Machine Learning workspace.

You plan to run a job to tram a model as an MLflow model output.

You need to specify the output mode of the MLflow model.

Which three modes can you specify? Each correct answer presents a complete solution.

NOTE: Each correct selection is worth one point.