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Updated: Sep 18, 2026
Q & A: 65 Questions and Answers
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| Certification Vendor: | Microsoft |
|---|---|
| Exam Name: | Perform Cloud Data Science with Azure Machine Learning |
| Exam Number: | 70-774 |
| Passing Score: | 700 (out of 1000) |
| Related Certifications: | MCSA: Data Science Microsoft Certified: Azure Data Scientist Associate (DP-100) |
| Exam Price: | Approx. 165 USD (varies by region) |
| Available Languages: | English |
| Exam Duration: | 120 minutes |
| Exam Format: | Multiple choice, Scenario-based questions, Case studies |
| Real Exam Qty: | 40-60 |
| Certificate Validity Period: | Certification retired (no longer active exam) |
| Recommended Training: | Azure Data Scientist Associate (DP-100) Training Microsoft Learn - Azure Machine Learning Path |
| Exam Registration: | Pearson VUE Microsoft Exams Microsoft Certification Exam Registration |
| Sample Questions: |  |
| 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/ |
| Section | Objectives |
|---|---|
| Prepare and process data for Azure Machine Learning | - Data ingestion and storage
|
| Deploy and manage models | - Operationalization
|
| Evaluate and optimize models | - Model tuning and improvement
|
| Develop machine learning models | - Select and implement algorithms
|
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Through the vendor's official registration channels:
The exam runs Online proctored or test center (Pearson VUE), so pick the setup that suits you when booking.
The Microsoft Perform Cloud Data Science with Azure Machine Learning is the official Microsoft exam behind the MCSA: Data Science (Retired) certification at the Associate level. It's how the vendor verifies that your skills meet its standard — and how employers know they do. Related credentials include MCSA: Data Science, Microsoft Certified: Azure Data Scientist Associate (DP-100), useful context if you're mapping a longer certification path.
40-60 questions, 120 minutes on the clock. That ratio is the real exam-within-the-exam: budget your time per question, learn to flag and move on, and rehearse in the BraindumpsVCE engine under real timing until finishing comfortably becomes your default.
The vendor recommends the following:
No time for scheduled classes? You're not alone — most of our customers are working IT professionals. The 070-774 practice questions from BraindumpsVCE deliver the self-paced alternative, ready whenever your calendar is.
The Microsoft Perform Cloud Data Science with Azure Machine Learning blueprint divides into 4 domains, with Prepare and process data for Azure Machine Learning, Develop machine learning models, Evaluate and optimize models among the headline areas. Let the weightings steer your hours — they tell you where the questions concentrate. The full outline above shows every subtopic.
Registration costs Approx. 165 USD (varies by region), and passing requires 700 (out of 1000). Credit card is the standard, secure way to pay — and note the fee applies per attempt, so a retake costs full price again. Practicing with the 65 questions from BraindumpsVCE until your mock scores clear the bar comfortably is the cheaper insurance.
No formal prerequisites required, but recommended experience with Azure Machine Learning, data science fundamentals, and Python or R programming. Vendor policies evolve, so before booking, confirm the latest eligibility details on the official exam page (official 070-774 exam information).
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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 section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You have an Azure ML experiment that contains an intermediate dataset.
You need to explore data from the intermediate dataset by using Jupyter.
Solution: You add a web service input to retrieve the data for the data source, and then add the Execute R Script module.
Does this meet the goal?
Correct Answer: B 🗳️
You have data about the following:
* Users
* Movies
* User ratings of the movies
You need to predict whether a user will like a particular movie. Which Matchbox recommender should you use?
Correct Answer: D 🗳️
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 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.
The users will use different data sources that follow a standard format. The users will receive results in a standard format by using the fraud prediction web service. The results will be saved to a location specified by the users.
You need to provide the users with the ability to get results for different risk tolerances without affecting the calculation of the model. Which three modules should be configured to use the Web Service Parameters? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
Correct Answer: A,D,E 🗳️
You are building an Azure Machine Learning experiment.
You are preparing the output of a Boosted Decision Tree Regression module. You add a Normalize Data module to the experiment.
You need to ensure that the range of the transformation method produces an output on a scale of -1 to 1.
Which transformation method should you use?
Correct Answer: B 🗳️
You have the following three training datasets for a restaurant:
You must recommend restaurant to a particular user based only on the users features.
You need to use a Matchbox Recommender to make recommendations.
How many input parameters should you specify?
Correct Answer: A 🗳️
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