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

  • Exam Code: 070-774
  • Exam Name: Perform Cloud Data Science with Azure Machine Learning
  • Updated: Aug 17, 2026     Q & A: 65 Questions and Answers

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About Microsoft 070-774 Exam

Perform Cloud Data Science with Azure Machine learning 70-774 Dumps will include below mentioned topics with Exam focused percentage

  • Prepare Data for Analysis in Azure Machine Learning and Export from Azure Machine Learning: 20-25%
  • Use Other Services for Machine Learning: 20-25%
  • Operationalize and Manage Azure Machine Learning Services: 20-25%
  • Develop Machine Learning Models: 20-25%

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Analyzing Big Data with Microsoft R 70-773 Dumps Provided Study Notes

PracticeTorrent expert team recommend you to prepare some notes on these topics along with it don't forget to practice Perform Cloud Data Science with Azure Machine Learning 70-774 Dumps which been written by our expert team, Both these will help you a lot to clear this exam with good marks.

  • Data Science
  • Machine Learning models
  • Microsoft R Servers.
  • Cognitive Services/API
  • Python Languages.
  • Azure Machine Learning.
  • Algorithms for grouping unlabeled Data.
  • SQL/T-SQL
  • Machine Learning Projects and workspace
  • HDinsights

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

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Microsoft 070-774 Exam Syllabus Topics:

SectionObjectives
Topic 1: Deploy and manage models- Model deployment in Azure
  • 1. Batch inference pipelines
    • 2. Deploy to Azure web services
      - Operationalization
      • 1. Monitor deployed models
        • 2. Update and retrain models
          Topic 2: Develop machine learning models- Training models in Azure Machine Learning
          • 1. Train models using Python or R scripts
            • 2. Use Azure ML Studio experiments
              - Select and implement algorithms
              • 1. Supervised learning models
                • 2. Unsupervised learning models
                  Topic 3: Evaluate and optimize models- Model evaluation techniques
                  • 1. Accuracy, precision, recall, F1 score
                    • 2. ROC and AUC analysis
                      - Model tuning and improvement
                      • 1. Hyperparameter tuning
                        • 2. Feature selection and engineering
                          Topic 4: Prepare and process data for Azure Machine Learning- Data preparation and transformation
                          • 1. Clean missing or inconsistent data
                            • 2. Transform features for modeling
                              - Data ingestion and storage
                              • 1. Import data into Azure Machine Learning datasets
                                • 2. Connect to Azure storage services

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