Free Microsoft DP-100 Exam Questions

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 have been tasked with creating a new Azure pipeline via the Machine Learning designer. You have to makes sure that the pipeline trains a model using data in a comma-separated values (CSV) file that is published on a website. A dataset for the file for this file does not exist. Data from the CSV file must be ingested into the designer pipeline with the least amount of administrative effort as possible. Which of the following actions should you take? 

You plan to run a Python script as an Azure Machine Learning experiment. The script must read files from a hierarchy of folders. The files will be passed to the script as a dataset argument. You must specify an appropriate mode for the dataset argument. Which two modes can you use? Each correct answer presents a complete solution. NOTE: Each correct selection is worth one point.

You develop and train a machine learning model to predict fraudulent transactions for a hotel booking website. Traffic to the site varies considerably. The site experiences heavy traffic on Monday and Friday and much lower traffic on other days. Holidays are also high web traffic days. You need to deploy the model as an Azure Machine Learning real-time web service endpoint on compute that can dynamically scale up and down to support demand. Which deployment compute option 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 analyzing a numerical dataset which contains missing values in several columns. You must clean the missing values using an appropriate operation without affecting the dimensionality of the feature set. You need to analyze a full dataset to include all values. Solution: Replace each missing value using the Multiple Imputation by Chained Equations (MICE) method. Does the solution meet the goal?