DP-100 Exam Dumps Retired

Retired

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

This exam has been retired by the vendor. Current exam: AI-300
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DP-100 — Microsoft Designing and Implementing a Data Science Solution on Azure Retired

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DP-100 is a retired exam

DP-100 (Designing and Implementing a Data Science Solution on Azure) has been retired by Microsoft. You can no longer schedule this exam as a current certification.

If you are preparing now, the current exam is AI-300 — AI-300 — Operationalizing Machine Learning and Generative AI Solutions.

Go to AI-300 exam prep

This DP-100 page is kept for search and indexing. The PDF below is the retired question set, not the current exam.

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About DP-100

The DP-100 exam measures a candidate’s ability to apply data science and machine learning techniques to implement and run machine learning workloads on Microsoft Azure.

This exam is designed for data scientists who use Azure Machine Learning and other Azure services to train, evaluate, and deploy models that solve business problems.


Skills Measured

The exam evaluates the following technical areas:

  • Design and prepare a machine learning solution
  • Explore data and train models
  • Prepare a model for deployment
  • Deploy and retrain a model

Exam Details

  • Exam Code: DP-100
  • Certification: Microsoft Certified: Azure Data Scientist Associate
  • Exam Duration: Approximately 100–120 minutes
  • Question Types: Multiple choice, case studies, and scenario-based questions
  • Passing Score: 700 out of 1000

Target Audience

This exam is intended for data scientists and professionals who:

  • Work with machine learning models
  • Use Azure Machine Learning services
  • Have knowledge of Python and data science libraries
  • Are responsible for training, evaluating, and deploying models

About the Certification

Earning the Azure Data Scientist Associate certification demonstrates expertise in:

  • Applying data science techniques on Azure
  • Building and operationalizing machine learning solutions
  • Managing the full lifecycle of machine learning models

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