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Microsoft DP-100 Practice Test Questions, Microsoft DP-100 Exam Practice Test Questions

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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Who should take the DP-100 exam

The Designing and Implementing a Data Science Solution on Azure (beta) DP-100 Exam certification is an internationally-recognized validation that identifies persons who earn it as possessing skilled as a Microsoft Certified Azure Data Scientist Associate. If candidates want significant improvement in career growth needs enhanced knowledge, skills, and talents. The Designing and Implementing a Data Science Solution on Azure (beta) DP-100 Exam certification provides proof of this advanced knowledge and skill. If a candidate has knowledge of associated technologies and skills that are required to pass Designing and Implementing a Data Science Solution on Azure (beta) DP-100 Exam then he should take this exam.

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

Step 2: Enrolling for the Instructor-Led Training Course

This is the most recommended way of preparing for the Microsoft DP-100 exam. Microsoft offers the official training course under the title “Designing and Implementing a Data Science Solution on Azure” to help the students build a solid knowledge base for the test. The training sessions are delivered to the individuals by the world-class professionals with plenty of experience in the field. So, the candidates get trained accordingly in the best way possible. Another advantage of taking the instructor-led course is that you have an opportunity to ask your questions and receive feedback whenever you face difficulties.

Skills Covered

To nail DP-100, you will need to scrutinize the below-mentioned areas:

• Set up Azure ML Workspace

  The first domain gives considerable attention to skills related to the Azure ML workspace. So, the test-takers have a chance to learn about workspace settings, the management of workspace using Azure ML, and registering in addition to maintaining the datastores.

• Execute Experiments & Train Models

  This objective imparts updated understanding about the concepts like creating models by using Azure ML Designer, custom code modules in Designer, defining a pipeline data flow, and an experiment running by using Azure Machine Learning SDK.

• Deploy and Consume Models

  The last segment is all about deployment and consumption models. Topics like evaluating compute options, creating production compute targets, batch inferencing pipeline creation, and running this pipeline efficiently are well covered within such a scope.

• Manage and Optimize Models

  Using automated ML for the optimal model creation, hyperdrive to tune hyperparameters, model management, and knowing the crucial model explainers to interpret models are some of the key topics explained in this portion.

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