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Designing and Implementing a Data Science Solution on Azure Exam (DP-100) - Microsoft Exam Questions

Last updated on June 22, 2026

97% Exam Compliance
506 Total Questions
1
Question
You deploy a real-time inference service for a trained model. The deployed model supports a business-critical application, and it is important to be able to monitor the data submitted to the web service and the predictions the data generates. You need to implement a monitoring solution for the deployed model using minimal administrative effort.

What should you do?
Options
A View the log files generated by the experiment used to train the model.
B Enable Azure Application Insights for the service endpoint and view logged data in the Azure portal.
C View the explanations for the registered model in Azure ML studio.
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2
Question
Exhibit

You must use the Azure Machine Learning SDK to interact with data and experiments in the workspace. You need to configure the config.json file to connect to the workspace from the Python environment. Which two additional parameters must you add to the config.json file in order to connect to the workspace? Each correct answer presents part of the solution.

NOTE: Each correct selection is worth one point.
Options
A Login
B resource_group
C Key
D region
E subscription_Id
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3
Question
You have an Azure Machine Learning workspace that includes an AmICompute cluster and a batch endpoint. You clone a repository that contains an MLflow model to your local computer. You need to ensure that you can deploy the model to the batch endpoint. Solution: Add a compute resource to the workspace. Does the solution meet the goal?
Options
A No
B Yes
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4
Question
HOTSPOT You create an Azure Machine Learning workspace. You need to detect data drift between a baseline dataset and a subsequent target dataset by using the DataDriftDetector class.

How should you complete the code segment? To answer, select the appropriate options in the
HOTSPOT
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5
Question
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 plan to use a Python script to run an Azure Machine Learning experiment. The script creates a

Exhibit
Reveal Only
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