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After obtaining the Microsoft Certified: Azure Data Scientist Associate certification, you become eligible for the data scientist role. Also, with this certification, you can expect to earn a decent remuneration of about $97k on average annually, as stated by PayScale.com. The expected career paths for a data scientist also include senior data scientist with a salary potential of $126,778 and data science manager with a salary potential of $136,781. Another possible path is that of a data science director with a potential pay of $157,095 annually. However, remember that besides, such a certificate work experience also matters.
| Books / Training | DP-100T01-A: Designing and Implementing a Data Science Solution on Azure |
| Exam Price | $165 (USD) |
| Schedule Exam | Pearson VUE |
| Sample Questions | Microsoft Designing and Implementing a Data Science Solution on Azure Sample Questions |
| Passing Score | 700 / 1000 |
| Exam Name | Microsoft Certified - Azure Data Scientist Associate |
| Duration | 120 mins |
| Exam Code | DP-100 |
| Number of Questions | 40-60 |
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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.
Reference: https://www.microsoft.com/en-us/learning/exam-dp-100.aspx
| Section | Objectives |
|---|---|
| Topic 1: Explore and analyze data | - Perform exploratory data analysis - Ingest and prepare data for modeling |
| Topic 2: Deploy and consume models | - Monitor deployed models and endpoints - Deploy models to endpoints |
| Topic 3: Optimize and manage models | - Improve model performance - Track experiments and manage model lifecycle |
| Topic 4: Train machine learning models | - Tune hyperparameters and evaluate models - Train models using Azure Machine Learning |
| Topic 5: 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 |
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