Pass your actual test with our Microsoft DP-100 training material at first attempt
Updated: Oct 29, 2026
No. of Questions: 528 Questions & Answers with Testing Engine
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| Certification Vendor: | Microsoft |
|---|---|
| Exam Name: | Designing and Implementing a Data Science Solution on Azure |
| Exam Number: | DP-100 |
| Available Languages: | French, Spanish, English, Korean, Russian, Portuguese (Brazil), Japanese, German, Simplified Chinese |
| Real Exam Qty: | 40-60 |
| Exam Format: | Multiple choice, Multiple response, Case studies, Hands-on lab tasks, Drag and drop |
| Exam Duration: | 100-120 |
| Related Certifications: | Microsoft Certified: Azure Data Scientist Associate |
| Certificate Validity Period: | 1 year (renewable through Microsoft certification renewal assessment) |
| Exam Price: | USD 165 (varies by region) |
| Passing Score: | 700/1000 |
| Recommended Training: | Azure Machine Learning Documentation Microsoft Learn - DP-100 Learning Path |
| Exam Registration: | Official Microsoft Certification Page Pearson VUE Registration |
| Sample Questions: | Microsoft DP-100 Sample Questions |
| Exam Way: | Online proctored or in-person at authorized testing centers (Pearson VUE) |
| Pre Condition: | No mandatory prerequisites. Recommended familiarity with Python, machine learning concepts, and Azure fundamentals. |
| Official Syllabus URL: | https://learn.microsoft.com/en-us/credentials/certifications/azure-data-scientist/ |
By passing the DP-100 certification exam, data scientists and data engineers can demonstrate their expertise in designing and implementing data science solutions on Azure. Designing and Implementing a Data Science Solution on Azure certification can help candidates stand out in a competitive job market and increase their earning potential. It can also provide a foundation for further Microsoft certifications, such as the AI-100 (Designing and Implementing an Azure AI Solution) certification.
Achieving the Microsoft DP-100 certification is a great way to showcase your data science skills and enhance your career prospects. Designing and Implementing a Data Science Solution on Azure certification validates your ability to design and implement data science solutions on Azure, which is one of the most popular cloud platforms for data science and AI workloads. By passing the DP-100 exam, you can demonstrate your proficiency in using Azure tools and services to build intelligent solutions that can help organizations make better decisions and improve their business outcomes.
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
| Section | Objectives |
|---|---|
| Deploy and consume models | - Deploy models to endpoints - Monitor deployed models and endpoints |
| Optimize and manage models | - Improve model performance - Track experiments and manage model lifecycle |
| Explore and analyze data | - Ingest and prepare data for modeling - Perform exploratory data analysis |
| 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 |
| Train machine learning models | - Train models using Azure Machine Learning - Tune hyperparameters and evaluate models |
You plan to run a script as an experiment using a Script Run Configuration. The script uses modules from the scipy library as well as several Python packages that are not typically installed in a default conda environment.
You plan to run the experiment on your local workstation for small datasets and scale out the experiment by running it on more powerful remote compute clusters for larger datasets.
You need to ensure that the experiment runs successfully on local and remote compute with the least administrative effort.
What should you do?
Correct Answer: D 🗳️
Explanation: Only visible for Exam4Docs members. You can sign-up / login (it's free).
You use the Two-Class Neural Network module in Azure Machine Learning Studio to build a binary classification model. You use the Tune Model Hyperparameters module to tune accuracy for the model.
You need to select the hyperparameters that should be tuned using the Tune Model Hyperparameters module.
Which two hyperparameters should you use? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
Correct Answer: A,C 🗳️
Explanation: Only visible for Exam4Docs members. You can sign-up / login (it's free).
You download a .csv file from a notebook in an Azure Machine Learning workspace to a data/sample.csv folder on a compute instance. The file contains 10,000 records. You must generate the summary statistics for the data in the file. The statistics must include the following for each numerical column:
* number of non-empty values
* average value
* standard deviation
* minimum and maximum values
* 25th. 50th. and 75th percentiles
You need to complete the Python code that will generate the summary statistics.
Which code segments should you use? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Correct Answer:

Explanation:
You manage an Azure AI Foundry project in your subscription. You deploy a gpt-4o model. You must test the model before you use it in an existing front-end application. You need to adjust the parameters to get more creative responses.
Solution: Adjust Frequency penalty.
Does the solution meet the goal?
Correct Answer: A 🗳️
You manage an Azure Machine Learning won pace named workspace 1 by using the Python SDK v2. You create a Gene-al Purpose v2 Azure storage account named mlstorage1. The storage account includes a pulley accessible container name micOTtalnerl. The container stores 10 blobs with files in the CSV format.
You must develop Python SDK v2 code to create a data asset referencing all blobs in the container named mtcontamer1.
You need to complete the Python SDK v2 code.
How should you complete the code? To answer select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Correct Answer:

Explanation:
Viewing page 1 out of 106 pages.
Viewing questions 1-5 out of 528 questions.
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