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Microsoft 070-774 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Develop Machine Learning Models | 35% | - Select appropriate algorithms
|
| Operationalize and Manage Azure Machine Learning Services | 25% | - Deploy models as web services
|
| Use Other Services for Machine Learning | 10% | - Integrate with HDInsight - Work with Microsoft Cognitive Toolkit - Use SQL Server R Services - Leverage Cortana Intelligence Gallery |
| Prepare Data for Analysis in Azure Machine Learning | 30% | - Import and export data
|
Better Every Day: Our 070-774 Commitments
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According to the latest exam information, the 070-774 exam contains 40-60 questions and allows 120 minutes minutes. Timed practice under those exact conditions is part of efficient preparation.
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Microsoft specifies these prerequisites for the Microsoft Perform Cloud Data Science with Azure Machine Learning: No mandatory prerequisites; recommended knowledge of data science, Azure basics, and machine learning concepts.
Confirm the current requirements on the official certification page before registering.
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Microsoft points candidates to these official training options:
Structured training plus regular question practice keeps your preparation progressive, never regressive.
The Microsoft Perform Cloud Data Science with Azure Machine Learning blueprint is structured around these principal domains:
- Use Other Services for Machine Learning (10%)
- Operationalize and Manage Azure Machine Learning Services (25%)
- Prepare Data for Analysis in Azure Machine Learning (30%)
Additional domains complete the official outline — the bank covers the full set.
Currently, passing the 070-774 exam requires a score of 700 out of 1000, and registration costs 165 USD. Both are Microsoft's figures and can change, so confirm them on the official site before booking.
Registration goes through the official channels below:
Pick your test center or online session early — preparation moves faster with a deadline in place.
Microsoft Perform Cloud Data Science with Azure Machine Learning Sample Questions:
You are building an Azure Machine Learning experiment.
You need to transform 47 numeric columns into a set of 10 linearly uncorrelated features.
Which module should you add to the experiment?
- A. Normalize Data
- B. Group Data into Bins
- C. Principal Component Analysis
- D. K-Means Clustering
Correct Answer: C 🗳️
You have an Apache Spark cluster in Azure HDinsight. The cluster includes 200 TB in five Apache Hive tables that have multiple foreign key relationships.
You have an Azure Machine Learning model that was built by using SPARK Accelerated Failure Time (AFT) Survival Regression Model (spark-survreg).
You need to prepare the Hive data into a single table as input for the Machine Learning model. The Hive data must be prepared in the least amount of time possible.
What should you use to prepare the data?
- A. the GPU
- B. Java Mapreduce jobs
- C. Spark SQL
- D. a Hive user-defined function (UDF)
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.
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 need to alter the list of columns that will be used for predicting fraud for an input web service endpoint.
The columns from the original data source must be retained while running the Machine Learning experiment.
Which module should you add after the web service input module and before the prediction module?
- A. Select Columns in Dataset
- B. Edit Metadata
- C. Import Data
- D. SMOTE
Correct Answer: A 🗳️
The manager of a call center reports that staffing the center is difficult because the number of calls is unpredictable. You have historical data that contains information about the calls.
You need to build an Azure Machine Learning experiment to predict the number of total calls each hour.
Which model should you use?
- A. Boosted Decision Tree Regression
- B. Poisson Regression
- C. Multiclass Logistic Regression
- D. Decision Forest Regression
Correct Answer: B 🗳️
You are building an Azure Machine Learning experiment.
You need to transform a string column into a label column for a Multiclass Decision Jungle module.
Which module should you use?
- A. Convert to Indicator Values
- B. Select Columns Transform
- C. Edit Metadata
- D. Group Categorical Values
Correct Answer: C 🗳️
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