DP-100 Practice Questions
Designing and Implementing a Data Science Solution on Azure
Last Update 2 days ago
Total Questions : 525
Dive into our fully updated and stable DP-100 practice test platform, featuring all the latest Microsoft Azure exam questions added this week. Our preparation tool is more than just a Microsoft study aid; it's a strategic advantage.
Our free Microsoft Azure practice questions crafted to reflect the domains and difficulty of the actual exam. The detailed rationales explain the 'why' behind each answer, reinforcing key concepts about DP-100. Use this test to pinpoint which areas you need to focus your study on.
You manage an Azure Machine Learning workspace. You build a model for which you must configure a Responsible Al dashboard. Based on what you learn from the dashboard, you must perform the following activities:
• Determine what must be done to get a desirable outcome from the model.
• Identify the features that have the most direct effect on your outcome of interest.
You need to select the components to use for the Responsible Al dashboard configuration. Which two components should you add? Each correct answer presents part of the solution. NOTE: Each correct selection is worth one point.
You manage an Azure Machine Learning workspace.
You schedule a pipeline job by using Azure Machine Learning Python SDK v2.
You need to decide whether the time-based schedule with cron expression is implemented correctly.

For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.

You manage an Azure Machine Learning workspace. You develop a regression model training pipeline by using Notebooks. You need to determine the appropriate evaluation metric for the experiment.
Which two metrics should you choose? Each correct answer presents a complete solution. Choose two. NOTE: Each correct selection is worth one point.
You are using an Azure Machine Learning workspace. You set up an environment for model testing and an environment for production.
The compute target for testing must minimize cost and deployment efforts. The compute target for production must provide fast response time, autoscaling of the deployed service, and support real-time inferencing.
You need to configure compute targets for model testing and production.
Which compute targets should you use? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
You manage an Azure Al Foundry project. You build a multi-turn chatbot application.
You plan to filter your traces to identity issues while observing how the application is responding. The solution must not use an external knowledge base. You need to select an evaluation metric. Which built-in evaluator should you use?
You manage an Azure OpenAI deployment of the gpt-4o base model.
You plan to fine-tune the deployed model.
You need to prepare a file that contains training data.
Which keys should you include in each line of the training data file? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

You are performing sentiment analysis using a CSV file that includes 12,000 customer reviews written in a short sentence format. You add the CSV file to Azure Machine Learning Studio and configure it as the starting point dataset of an experiment. You add the Extract N-Gram Features from Text module to the experiment to extract key phrases from the customer review column in the dataset.
You must create a new n-gram dictionary from the customer review text and set the maximum n-gram size to trigrams.
What should you select? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
You plan to create a speech recognition deep learning model.
The model must support the latest version of Python.
You need to recommend a deep learning framework for speech recognition to include in the Data Science Virtual Machine (DSVM).
What should you recommend?
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?
You manage an Azure Machine Learning workspace. The titanic.csv file is available in an Azure Blob Storage account named storage1. The container name is container " !. The folder name is data.
You perform interactive data wrangling by using a serverless Spark compute.
You need to load the data from Blob Storage into a Pandas dataframe.
How should you complete the code segment? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.





