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The Microsoft DP-100: Designing & Implementing a Data Science Solution on Azure exam evaluates the skills and knowledge of the professionals in a range of technical tasks. These include training models and running experiments, setting up an Azure ML workspace, consuming and deploying models, and managing & optimizing models. This test is the only qualifying exam that leads to the Microsoft Certified: Azure Data Scientist Associate certification.

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The candidates who want to take the Microsoft DP-100 exam are expected to have competence in its objectives. This means that they need to understand the scope of topics covered in this certification test. They are as follows:

1. Azure ML Workspace Set-Up (30-35%):

• Azure ML workspace creation: This area focuses on the students’ skills in creating Azure ML workspace, operating workspaces by using Azure ML studio, and configuring workspace settings.
• Data objects management within Azure ML workspace: The applicants should have competence in the creation and management of datasets, as well as maintenance and registration of datastores.
• Experiment compute contexts management: The test takers must be able to create compute instances and compute targets for training and experiments. They have to know how to establish suitable compute specifications for training workloads.

Reference: https://www.microsoft.com/en-us/learning/exam-dp-100.aspx

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