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Microsoft DP-100: Preparation Process
Thorough preparation is an important part of the Microsoft DP-100 exam and its associate-level certification. Here is the ultimate guide to prepare for this test with great deliberation.
Conclusion
Data science is a lucrative career option and you can explore it without any hassle if you’ve managed to taste success in the Microsoft DP-100 exam, which is known to create a skilled workforce of Azure data scientists. However, a great outcome in such a test will only come if the aspirant is referring to the updated and recent study resources like the official courses provided by the exam vendor itself.
Passing the Microsoft DP-100: Designing and Implementing a Data Science Solution on Azure exam is the major requirement for earning the Microsoft Certified: Azure Data Scientist Associate certification. This test measures the ability of the professionals to execute the following technical tasks: setting up an Azure Machine Learning workspace; running experiments & train models; optimizing and handling models; deploying and consuming models.
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 |
|---|---|
| Explore and analyze data | - Ingest and prepare data for modeling - Perform exploratory data analysis |
| Train machine learning models | - Tune hyperparameters and evaluate models - Train models using Azure Machine Learning |
| Optimize and manage models | - Track experiments and manage model lifecycle - Improve model performance |
| Design and prepare a machine learning solution | - Manage compute and data assets - Select appropriate Azure services for machine learning workloads - Plan and configure Azure Machine Learning workspace |
| Deploy and consume models | - Deploy models to endpoints - Monitor deployed models and endpoints |



