Free Microsoft DP-100 Exam Questions

Question 1

You use the Azure Machine Learning SDK in a notebook to run an experiment using a script file in an experiment folder. The experiment fails. You need to troubleshoot the failed experiment. What are two possible ways to achieve this goal? Each correct answer presents a complete solution.

A : Use the get_metrics() method of the run object to retrieve the experiment run logs.

B : Use the get_details_with_logs() method of the run object to display the experiment run logs.

C : View the log files for the experiment run in the experiment folder.

D : View the logs for the experiment run in Azure Machine Learning studio.

E : Use the get_output() method of the run object to retrieve the experiment run logs.

Answer: B,D

Question 2

You create an Azure Machine Learning compute resource to train models. The compute resource is configured

as follows:

Minimum nodes: 2

Maximum nodes: 4

You must decrease the minimum number of nodes and increase the maximum number of nodes to the

following values:

Minimum nodes: 0

Maximum nodes: 8

You need to reconfigure the compute resource.

What are three possible ways to achieve this goal? Each correct answer presents a complete solution

NOTE: Each correct selection is worth one point.

A : the Azure Machine Learning studio.

B : n the update method of the AmlCompute class in the Python SDK.

C : the Azure portal.

D : the Azure Machine Learning designer.

E : n the refresh_state() method of the BatchCompute class in the Python SDK

Answer: A,B,C

Question 3

You plan to run a script as an experiment using a Script Run Configuration. The script uses modules from the scipy library as well as several Python packages that are not typically installed in a default conda environment. You plan to run the experiment on your local workstation for small datasets and scale out the experiment by running it on more powerful remote compute clusters for larger datasets. You need to ensure that the experiment runs successfully on local and remote compute with the least administrative effort. What should you do?

A : Create and register an Environment that includes the required packages. Use this Environment for all experiment runs.

B : Always run the experiment with an Estimator by using the default packages.

C : Do not specify an environment in the run configuration for the experiment. Run the experiment by using the default environment.

D : Create a config. yaml file defining the conda packages that are required and save the file in the experiment folder.

E : Create a virtual machine (VM) with the required Python configuration and attach the VM as a compute target. Use this compute target for all experiment runs.

Answer: A

Question 4

You plan to run a script as an experiment using a Script Run Configuration. The script uses modules from the scipy library as well as several Python packages that are not typically installed in a default conda environment. You plan to run the experiment on your local workstation for small datasets and scale out the experiment by running it on more powerful remote compute clusters for larger datasets. You need to ensure that the experiment runs successfully on local and remote compute with the least administrative effort. What should you do?

A : Create and register an Environment that includes the required packages. Use this Environment for all experiment runs.

B : Always run the experiment with an Estimator by using the default packages.

C : Do not specify an environment in the run configuration for the experiment. Run the experiment by using the default environment.

D : Create a config. yaml file defining the conda packages that are required and save the file in the experiment folder.

E : Create a virtual machine (VM) with the required Python configuration and attach the VM as a compute target. Use this compute target for all experiment runs.

Answer: A

Question 5

You manage an Azure Machine Learning workspace. The development environment tor 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 10 use a user-assigned identity. Solution: Configure the IdentityConfiguration class with the appropriate identity type. Does the solution meet the goal?

A : Yes

B : No

Answer: A