Exam Name: Perform Cloud Data Science with Azure Machine Learning
Certification Provider: Microsoft
Corresponding Certification: MCSA-Machine Learning
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Updated: Oct 22, 2026
No. of Questions: 65 Questions & Answers with Testing Engine
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- Total Questions: 65
- Updated on: Oct 22, 2026
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Microsoft 70-774 Exam Overview:
| Certification Vendor: | Microsoft |
|---|---|
| Exam Name: | Perform Cloud Data Science with Azure Machine Learning |
| Exam Number: | 70-774 |
| Exam Price: | Approx. 165 USD (varies by region) |
| Exam Duration: | 120 minutes |
| Related Certifications: | MCSA: Data Science Microsoft Certified: Azure Data Scientist Associate (DP-100) |
| Real Exam Qty: | 40-60 |
| Available Languages: | English |
| Passing Score: | 700 (out of 1000) |
| Certificate Validity Period: | Certification retired (no longer active exam) |
| Exam Format: | Multiple choice, Scenario-based questions, Case studies |
| Recommended Training: | Microsoft Learn - Azure Machine Learning Path Azure Data Scientist Associate (DP-100) Training |
| Exam Registration: | Pearson VUE Microsoft Exams Microsoft Certification Exam Registration |
| Sample Questions: | DOWNLOAD DEMO |
| Exam Way: | Online proctored or test center (Pearson VUE) |
| Pre Condition: | No formal prerequisites required, but recommended experience with Azure Machine Learning, data science fundamentals, and Python or R programming. |
| Official Syllabus URL: | https://learn.microsoft.com/en-us/credentials/certifications/retired-certifications/ |
Microsoft 70-774 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Deploy and manage models | - Operationalization
|
| Develop machine learning models | - Training models in Azure Machine Learning
|
| Prepare and process data for Azure Machine Learning | - Data preparation and transformation
|
| Evaluate and optimize models | - Model evaluation techniques
|
70-774 Exam Essentials and Our Service System
Currently, the 70-774 exam's passing score is 700 (out of 1000) and the registration fee is Approx. 165 USD (varies by region). Both are Microsoft's figures and subject to revision — verify them on the official site before you schedule.
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The Microsoft Perform Cloud Data Science with Azure Machine Learning blueprint covers these core domains:
- Deploy and manage models
- Develop machine learning models
- Evaluate and optimize models
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Microsoft states the following prerequisites for the Microsoft Perform Cloud Data Science with Azure Machine Learning: No formal prerequisites required, but recommended experience with Azure Machine Learning, data science fundamentals, and Python or R programming..
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Microsoft Perform Cloud Data Science with Azure Machine Learning Sample Questions:
Note: This question is part of a series of questions that use the same scenario. For your convenience, the scenario is repeated in each question. Each question presents a different goal and answer choices, but the text of the scenario is exactly the same in each question in this scries.
Start of repeated scenario
You plan to create a predictive analytics solution for credit risk assessment and fraud prediction in Azure Machine Learning. The Machine Learning workspace for the solution will be shared with other users in your organization. You will add assets to projects and conduct experiments in the workspace.
The experiments will be used for training models that will be published to provide scoring from web services.
The experiment for fraud prediction will use Machine Learning modules and APIs to train the models and will predict probabilities in an Apache Hadoop ecosystem.
End of repeated scenario.
You plan to share the Machine Learning workspace with the other users.
You are evaluating whether to assign the User role or the Owner role to several of the users.
Which three actions can be performed by the users who are assigned the User role? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.
- A. Access notebooks.
- B. Delete users from the workspace.
- C. Create, open, modify, and delete experiments.
- D. Create, open, modify, and delete web services.
- E. Create, open, modify, and delete datasets.
- F. Invite users to the workspace.
Correct Answer: A,B,F 🗳️
You plan to use the Import Data module to import data from a web URL by using HTTP.
Which file format can you use as the source of the import operation?
- A. Optimized Row Columnar (ORQ
- B. comma-separated value (CSV)
- C. JavaScript Object Notation (JSON)
- D. Extensible Markup Language (XML)
Correct Answer: C 🗳️
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
After you answer a question in this sections, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You are designing an Azure Machine Learning workflow.
You have a dataset that contains two million large digital photographs.
You plan to detect the presence of trees in the photographs.
You need to ensure that your model supports the following:
Solution: You create an endpoint to the Computer vision API.
Does this meet the goal?
- A. Yes
- B. No
Correct Answer: B 🗳️
Note: This question is part of a series of questions that use the same or similar answer choices. An answer choice may be correct for more than one question in the series. Each question is independent of the other questions in this series. Information and details provided in a question apply only to that question.
You have a non-tabular file that is saved in Azure Blob storage.
You need to download the file locally, access the data in the file, and then format the data as a dataset.
Which module should you use?
- A. Clean Missing Data
- B. Normalize Data
- C. Edit Metadata
- D. Tune Model Hyperparameters
- E. Execute Python Script
- F. Import Data
- G. Select Columns in Dataset
- H. Clip Values
Correct Answer: F 🗳️
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Note: This question is part of a series of questions that use the same scenario. For your convenience, the scenario is repeated in each question. Each question presents a different goal and answer choices, but the text of the scenario is exactly the same in each question in this series.
Start of repeated scenario
You plan to use Azure platform tools to detect and analyze food items in smart refrigerators. To provide families with an integrated experience for grocery shopping and cooking, the refrigerators will connect to other smart appliances, such as stoves and microwave ovens, on a LAN.
You plan to build an object recognition model by using the Microsoft Cognitive Toolkit. The object recognition model will receive input from the connected devices and send results to applications.
The training data will be derived from more than 10 TB of images. You will convert the raw images to the sparse format.
End of repeated scenario.
You need to preprocess the training data by using a Principal Component Analysis (PCA) algorithm in the least amount of time possible. Which implementation method should you use?
- A. Azure Machine Learning Studio and a custom Execute Python Script module
- B. Azure HDInsight using Microsoft R Server
- C. Azure Machine Learning Studio with a custom Execute R Script module
- D. Azure HDInsight using HiveML
Correct Answer: B 🗳️
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