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Microsoft DP-100: Exam Details
Microsoft doesn’t provide detailed information regarding its exams, including the DP-100 certification test. The total number of questions in exam is not published on the official website, but the candidates can expect to encounter about 40-60 items in their delivery of their test. There is also a high probability that they will face scenario-based questions with single-answer and multiple-answer options. The duration is all about 120 minutes. The exam is available in several languages, including Japanese, English, Simplified Chinese, and Korean.
The Microsoft DP-100 exam can be taken at any nearest Pearson VUE testing center or online as a proctored option. The cost for the exam is $165 in the United States but the price is usually different in other countries due to taxation. To find out the actual pricing for your country, simply check the official webpage.
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Target Audience & Requirements
The candidates for this Microsoft exam are Azure Data Scientists. These professionals have expertise in applying their knowledge of machine learning and data science to run and implement ML workloads on Azure. This is particularly in the usage of Azure ML Service. These applicants are the experts in planning and creating the appropriate working environments for data science workloads within Azure. They also train predictive models and run data experiments. The individuals who want to earn ACE college credit can also take this certification test.
The Microsoft DP-100: Designing & Implementing a Data Science Solution on Azure test has no official requirement. However, the candidates must develop an in-depth understanding of the exam topics. They should also have expertise in model optimization and management and ML models deployment within the production.
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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%):
- 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.
- 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.
- 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.
Reference: https://www.microsoft.com/en-us/learning/exam-dp-100.aspx
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Microsoft DP-100日本語 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Optimize and manage models | - Improve model performance - Track experiments and manage model lifecycle |
| Explore and analyze data | - Perform exploratory data analysis - Ingest and prepare data for modeling |
| Deploy and consume models | - Deploy models to endpoints - Monitor deployed models and endpoints |
| Train machine learning models | - Tune hyperparameters and evaluate models - Train models using Azure Machine Learning |
| Design and prepare a machine learning solution | - Plan and configure Azure Machine Learning workspace - Select appropriate Azure services for machine learning workloads - Manage compute and data assets |
