Microsoft 070-774 dumps - in .pdf

070-774 pdf
  • Exam Code: 070-774
  • Exam Name: Perform Cloud Data Science with Azure Machine Learning
  • Updated: Sep 26, 2026
  • Q & A: 65 Questions and Answers
  • PDF Price: $49.98

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  • Exam Code: 070-774
  • Exam Name: Perform Cloud Data Science with Azure Machine Learning
  • Updated: Sep 26, 2026
  • Q & A: 65 Questions and Answers
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Microsoft 070-774 dumps - Testing Engine

070-774 Testing Engine
  • Exam Code: 070-774
  • Exam Name: Perform Cloud Data Science with Azure Machine Learning
  • Updated: Sep 26, 2026
  • Q & A: 65 Questions and Answers
  • Software Price: $49.98
  • Testing Engine

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

Microsoft 070-774 certification exam is aimed at individuals who have experience in machine learning and are looking to validate their skills and knowledge. Perform Cloud Data Science with Azure Machine Learning certification exam is designed to focus on particular competencies that are expected from a cloud data scientist who uses Azure Machine Learning. 070-774 exam covers a range of topics that are essential for designing, implementing, and maintaining machine learning solutions that use Azure Machine Learning.

Microsoft 070-774 certification exam is designed for individuals who want to demonstrate their proficiency in performing cloud data science tasks using Azure Machine Learning. 070-774 exam verifies a candidate's ability to use various Azure Machine Learning tools and services to develop and deploy machine learning models in a cloud environment.

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

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Microsoft 070-774 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Operationalize and Manage Azure Machine Learning Services25%- Manage workspaces and experiments
  • 1. Share and collaborate
    • 2. Create and organize projects
      - Consume models and APIs
      • 1. Use Cognitive Services APIs
        • 2. Call deployed web services
          - Deploy models as web services
          • 1. Configure endpoints and access
            • 2. Publish to Azure ML Studio
              Topic 2: Use Other Services for Machine Learning10%- Integrate with HDInsight
              - Use SQL Server R Services
              - Leverage Cortana Intelligence Gallery
              - Work with Microsoft Cognitive Toolkit
              Topic 3: Prepare Data for Analysis in Azure Machine Learning30%- Import and export data
              • 1. Export results and datasets
                • 2. Import from files and external sources
                  • 3. Connect to Azure storage and databases
                    - 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. Remove duplicates and inconsistent entries
                              • 2. Handle missing values and outliers
                                Topic 4: Develop Machine Learning Models35%- Validate and evaluate models
                                • 1. Use accuracy, precision, recall, AUC
                                  • 2. Perform cross-validation
                                    - Select appropriate algorithms
                                    • 1. Unsupervised learning methods
                                      • 2. Supervised learning methods
                                        - Train and tune models
                                        • 1. Split training and test sets
                                          • 2. Configure parameters

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