Microsoft DP-100 : Designing and Implementing a Data Science Solution on Azure

Step 5: Studying with Books

Books is another efficient preparation tool. There are several guides available for the Microsoft DP-100 exam but the most popular are listed below:

• Designing and Implementing a Data Science Solution on Azure - Exam Prep: Microsoft Azure DP-100 Certification Exam | Most Unique & Latest Questionnaires by VB Dev
• Learn How to Pass DP-100: Designing and Implementing a Data Science Solution on Azure Exam: Learn at your fingertips by Rodrezil Publications
• How I Passed DP-100: Designing and Implementing a Data Science Solution on Azure: Sure Shot Certification Tips by Empirical Matt Publications
• Exam Ref DP-100 Designing and Implementing a Data Science Solution on Azure 1st Edition by Pierstefano Tucci
• Designing and Implementing a Data Science Solution on Azure: Prepare for exam DP-100 by Stavros Koureas

How to study the DP-100 Exam

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

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Microsoft DP-100: Career Prospects

After successfully passing the Microsoft DP-100 exam, you will obtain the Microsoft Certified: Azure Data Scientist Associate certification. Getting certified will allow you to qualify for several positions, including the following titles:

• Software Developer
• Data Analyst
• Administrative Analyst
• Data Engineer

Obtaining this certification is also beneficial from a financial point of view. In fact, the average salary that a certified professional can earn is $96,642 per year.

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Skills Covered

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

• 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.

• 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.

• 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.

• 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.

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Microsoft DP-100 Exam Syllabus Topics: