Become Microsoft Certified with updated DP-100 exam questions and correct answers
You create an Azure Machine Learning workspace. You must create a custom role named DataScientist that meets the following requirements: Role members must not be able to delete the workspace. Role members must not be able to create, update, or delete compute resource in the workspace. Role members must not be able to add new users to the workspace. You need to create a JSON file for the DataScientist role in the Azure Machine Learning workspace. The custom role must enforce the restrictions specified by the IT Operations team. Which JSON code segment should you use?
You create an Azure Machine Learning workspace. The workspace contains a dataset named
sample.dataset, a compute instance, and a compute cluster. You must create a two-stage pipeline
that will prepare data in the dataset and then train and register a model based on the prepared data.
The first stage of the pipeline contains the following code:
You need to identify the location containing the output of the first stage of the script that you can use
as input for the second stage. Which storage location should you use?
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 new experiment in Azure Machine Learning Studio. One class has a much smaller number of observations than the other classes in the training set. You need to select an appropriate data sampling strategy to compensate for the class imbalance. Solution: You use the Stratified split for the sampling mode. Does the solution meet the goal?
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.
You train and register a model in your Azure Machine Learning workspace. You must publish a pipeline that enables client applications to use the model for batch inferencing. You must use a pipeline with a single ParallelRunStep step that runs a Python inferencing script to get predictions from the input data. You need to create the inferencing script for the ParallelRunStep pipeline step. Which two functions should you include? Each correct answer presents part of the solution. NOTE: Each correct selection is worth one point.
© Copyrights DumpsCertify 2026. All Rights Reserved
We use cookies to ensure your best experience. So we hope you are happy to receive all cookies on the DumpsCertify.