Microsoft DP-100 Dumps
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DP-100 Exam Info
Exam Name: Designing and Implementing a Data Science Solution on Azure
Exam Duration: 120 mins
Exam Format: Multiple Choice
Exam Type: Cloud Computing
Questions in Exam: 40-60 Questions
Eligibility/Criteria: NIL
Exam Fee: $165 USD*
Language: English, Japanese, Chinese, Korean
Pass Score: 700 (on a scale of 1-1000)
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DP-100 FAQs
The Microsoft DP-100 exam, also known as Designing and Implementing a Data Science Solution on Azure, is a certification test that validates a candidate's ability to apply data science and machine learning techniques using Azure services.
The certification demonstrates your expertise in designing and implementing data science solutions on Azure, which can lead to career growth opportunities, such as promotions, more advanced roles, and specialized positions in data science and AI.
The DP-100 exam is 180 minutes long and consists of multiple-choice, multiple-response, and scenario-based questions.
The registration fee for the DP-100 exam is $165 USD.
The exam includes scenario-based questions on creating and managing Azure ML workspaces, tuning hyperparameters, securing data, deploying models, and monitoring performance in production environments. Questions often simulate real industry challenges — practicing with aligned mock tests on Dumpspedia helps build confidence for these advanced tasks.
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Designing and Implementing a Data Science Solution on Azure Questions and Answers
You use Azure Machine Learning to train a model. You must use Bayesian sampling to tune hyperparameters. You need to select a ieaming_rate parameter distribution.
Which two distributions can you use? Each correct answer presents a complete solution. NOTE: Each correct selection is worth one point.
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: Relative Squared Error, Coefficient of Determination, Accuracy, Precision, Recall, F1 score, and AUC.
Does the solution meet the goal?
You create and register a model in an Azure Machine Learning workspace.
You must use the Azure Machine Learning SDK to implement a batch inference pipeline that uses a ParallelRunStep to score input data using the model. You must specify a value for the ParallelRunConfig compute_target setting of the pipeline step.
You need to create the compute target.
Which class should you use?
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