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

  • Exam Code: DP-100
  • Exam Name: Designing and Implementing a Data Science Solution on Azure
  • Updated: Jul 29, 2026
  • Q & A: 528 Questions and Answers

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

Exam Details & Skills Measured

Microsoft DP-100 is an associate-level certification exam. It can be taken as a proctored test if this option is available in your country. If it’s not, you can sit for it as an online exam at one of the Pearson VUE testing centers across the world. You should check the official webpage for more information about scheduling this exam.

When you are ready for this test, you have to pay $165 as a registration fee, which applies to a single delivery of the exam. You can take it in English, Korean, Japanese, or Simplified Chinese. Microsoft DP-100 contains 40-60 questions that cover different types, such as drag and drop, multiple choice, active screen, build list, short answer, best answer, and case studies, among others. If you want to pass this test on the first try, you should get 720 points on a scale of 100-1000.

Step 4: Training with Practice Tests

Practicing more and more before taking the exam can help you score better. Using practice tests, you can also significantly improve your time management skills. You can easily find the relevant practice questions on different online learning platforms.

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

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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Microsoft DP-100 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Optimize language models for AI applications25-30%- Optimize with Retrieval Augmented Generation
  • 1. Create vector stores and indexes
  • 2. Prepare and process data
  • 3. Configure Azure AI Search
- Evaluate and improve models
  • 1. Optimize for accuracy and safety
  • 2. Apply responsible generative AI
  • 3. Test and evaluate responses
- Implement generative AI solutions
  • 1. Build prompt flows
  • 2. Apply prompt engineering
  • 3. Use Azure AI Foundry
Topic 2: Train and deploy models25-30%- Train models
  • 1. Run training scripts
  • 2. Use HyperDrive for hyperparameter tuning
  • 3. Apply responsible AI principles
  • 4. Configure jobs and environments
- Monitor and maintain models
  • 1. Monitor performance and data drift
  • 2. Implement MLOps practices
  • 3. Update and retrain models
- Deploy models
  • 1. Configure compute and scaling
  • 2. Secure endpoints and manage access
  • 3. Deploy to online endpoints
  • 4. Deploy to batch endpoints
- Manage models
  • 1. Register and version models
  • 2. Package and validate models
  • 3. Interpret models and explain predictions
Topic 3: Design and prepare a machine learning solution20-25%- Design a machine learning solution
  • 1. Define compute specifications for workloads
  • 2. Plan model deployment requirements
  • 3. Select development approach
  • 4. Determine dataset structure and format
- Manage compute resources
  • 1. Create and configure compute targets
  • 2. Select environments
  • 3. Attach and monitor compute
- Manage data assets
  • 1. Create and maintain data assets
  • 2. Select storage services
  • 3. Register and manage datastores
- Manage Azure Machine Learning workspace
  • 1. Use developer tools and CLI
  • 2. Set up Git integration
  • 3. Create and configure workspace
  • 4. Work with registries
Topic 4: Explore data and run experiments20-25%- Explore and visualize data
  • 1. Identify features and relationships
  • 2. Detect anomalies and outliers
  • 3. Profile and validate data
- Run experiments
  • 1. Use automated machine learning
  • 2. Define parameters and configurations
  • 3. Configure experiment runs
  • 4. Track runs with MLflow
- Implement pipelines
  • 1. Schedule and monitor pipelines
  • 2. Build reusable components
  • 3. Create and publish pipelines
  • 4. Pass data between steps

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