Microsoft 070-774 : Perform Cloud Data Science with Azure Machine Learning

070-774 real exams

Exam Code: 070-774

Exam Name: Perform Cloud Data Science with Azure Machine Learning

Updated: Oct 01, 2026

Q & A: 65 Questions and Answers

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Reference: https://www.microsoft.com/en-us/learning/exam-70-774.aspx

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Perform Cloud Data Science with Azure Machine Learning 70-774 Exam

Perform Cloud Data Science with Azure Machine Learning 70-774 Exam is centered around Azure Machine Learning, Bot Framework, and Cognitive Services. The exam is designed to target candidates who are Data Scientists or Analysts using the Microsoft Azure cloud services to build and deploy intelligent solutions. This exam will test your understanding and familiarity with common data science processes such as filtering and transforming data sets, model estimation, and model evaluation. Machine Learning is one of the hottest topics and technologies in the industry right now.

Machine Learning is being used to combine with Big Data to automate the processes of gaining insights and predicting future behavior of systems, devices, and people. In an effort to expand out the breadth of certifications and exams offered around Microsoft Azure and the cloud, Microsoft has added the Perform Cloud Data Science with Azure Machine Learning Microsoft 70-774 Exam. This exam only available for the candidates till 30th June 2019 after that this may get replace with some other exam so you can plan get it completed before it get expire.

We think our Perform Cloud Data Science with Azure Machine Learning 70-774 Exam Practice Test Paper and Dumps will provide you 100% confidence to make you appear for Microsoft 70-774 Exam

This is the list of the contents in our Perform Cloud Data Science with Azure Machine Learning 70-774

  • Perform data sciences at scale by using HD Insights
  • Validate models
  • Import and Export Data to and from ML.
  • Cleanse data for Azure Machine Learning
  • Azure Machine Learning models
  • Explore and summarize data

Microsoft 070-774 Exam Syllabus Topics:

SectionWeightObjectives
Use Other Services for Machine Learning10%- Work with Microsoft Cognitive Toolkit
- Leverage Cortana Intelligence Gallery
- Integrate with HDInsight
- Use SQL Server R Services
Operationalize and Manage Azure Machine Learning Services25%- Deploy models as web services
  • 1. Configure endpoints and access
    • 2. Publish to Azure ML Studio
      - Manage workspaces and experiments
      • 1. Create and organize projects
        • 2. Share and collaborate
          - Consume models and APIs
          • 1. Call deployed web services
            • 2. Use Cognitive Services APIs
              Prepare Data for Analysis in Azure Machine Learning30%- Perform feature engineering
              • 1. Normalize and scale features
                • 2. Create derived features
                  - Explore and summarize data
                  • 1. Visualize data distributions
                    • 2. Generate statistical summaries
                      - Cleanse and transform data
                      • 1. Handle missing values and outliers
                        • 2. Remove duplicates and inconsistent entries
                          - Import and export data
                          • 1. Export results and datasets
                            • 2. Import from files and external sources
                              • 3. Connect to Azure storage and databases
                                Develop Machine Learning Models35%- Select appropriate algorithms
                                • 1. Supervised learning methods
                                  • 2. Unsupervised learning methods
                                    - Validate and evaluate models
                                    • 1. Use accuracy, precision, recall, AUC
                                      • 2. Perform cross-validation
                                        - Train and tune models
                                        • 1. Configure parameters
                                          • 2. Split training and test sets

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