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: Dec 07, 2025

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Question 1

You are attaching an Azure Databricks-based compute resource to an Azure Machine Learning development workspace.

You need to configure parameters to attach the resource.

Which three parameters should you use? Each correct answer presents part of the solution.

NOTE: Each correct selection is worth one point.

A : Workspace name

B : Compute name

C : Workspace user credentials

D : Workspace resource ID

E : Access token

Answer: A,B,E

Question 2

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 are creating a model to predict the price of a student’s artwork depending on the following variables: the

student’s length of education, degree type, and art form.

You start by creating a linear regression model.

You need to evaluate the linear regression model.

Solution: Use the following metrics: Mean Absolute Error, Root Mean Absolute Error, Relative Absolute

Error, Accuracy, Precision, Recall, F1 score, and AUC.

Does the solution meet the goal?

A :

B :

Answer: B

Question 3

You plan to provision an Azure Machine Learning Basic edition workspace for a data science project.

You need to identify the tasks you will be able to perform in the workspace.

Which three tasks will you be able to perform? Each correct answer presents a complete solution.

NOTE: Each correct selection is worth one point.

A : eate a Compute Instance and use it to run code in Jupyter notebooks.

B : eate an Azure Kubernetes Service (AKS) inference cluster.

C : the designer to train a model by dragging and dropping pre-defined modules.

D : eate a tabular dataset that supports versioning.

E : the Automated Machine Learning user interface to train a model.

Answer: A,B,D

Question 4

You use the Azure Machine Learning service to create a tabular dataset named training_data. You plan to use this dataset in a training script. You create a variable that references the dataset using the following code: training_ds = workspace.datasets.get("training_data") You define an estimator to run the script. You need to set the correct property of the estimator to ensure that your script can access the training_data dataset. Which property should you set?

A : vironment_definition = {"training_data":training_ds}

B : puts = [training_ds.as_named_input('training_ds')]

C : ript_params = {"--training_ds":training_ds}

D : urce_directory = training_ds

Answer: B

Question 5

You are preparing to train a regression model via automated machine learning. The data available to you has features with missing values, as well as categorical features with little discrete values. You want to make sure that automated machine learning is configured as follows: missing values must be automatically imputed. categorical features must be encoded as part of the training task. Which of the following actions should you take?

A : u should make use of the featurization parameter with the 'auto' value pair.

B : u should make use of the featurization parameter with the 'off' value pair.

C : u should make use of the featurization parameter with the 'on' value pair.

D : u should make use of the featurization parameter with the 'FeaturizationConfig' value pair.

Answer: A

Page: 1 / 103

Total 511 Questions | Updated On: Dec 07, 2025

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