Free Microsoft DP-100 Exam Questions

Become Microsoft Certified with updated DP-100 exam questions and correct answers

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Total 511 Questions | Updated On: Nov 25, 2025

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Question 1

You manage an Azure Machine learning workspace named workspace1. You must develop Python SDK v2 code to add a compute instance to workspace1. The code must import all required modules and call the constructor of the Compute instance class. You need to add the instantiated compute instance to workspace 1. What should you use?

A : constructor of the azure ai.ml. ComputerPowerAction enemy

B : set resources method of an instance of the azureai.ml. Command class

C : begin create or update method of a stance of the azure.ai. imLMLCSentdass

D : contractor of the azure.ai.ml. mLComputeSchedule class

Answer: C

Question 2

You have an Azure Machine Learning workspace.

You plan to tune a model hyperparameter when you train the model.

You need to define a search space that returns a normally distributed value.

Which parameter should you use?

A : QUniform

B : LogUniform

C : Uniform

D : LogNormal

Answer: D

Question 3

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 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 register a model in an Azure Machine Learning workspace by running the following code:

You are creating a scoring script to use in a real-time service for the model.

You need to write code in the scoring script to set the path of the registered model so that it can be loaded by the service. You include the necessary import statements.

Which code segment should you use?

A : th = Model.get_model_path(‘loan_model’)

B : th = ‘model.pkl’

C : th = ws.models(‘loan_model’)

D : th = ‘outputs/model.pkl’

Answer: A

Page: 1 / 103

Total 511 Questions | Updated On: Nov 25, 2025

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