Microsoft 070-774 dumps - in .pdf

070-774 pdf
  • Exam Code: 070-774
  • Exam Name: Perform Cloud Data Science with Azure Machine Learning
  • Updated: Aug 29, 2026
  • Q & A: 65 Questions and Answers
  • PDF Price: $49.99
  • Free Demo

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  • Exam Code: 070-774
  • Exam Name: Perform Cloud Data Science with Azure Machine Learning
  • Updated: Aug 29, 2026
  • Q & A: 65 Questions and Answers
  • PDF Version + PC Test Engine + Online Test Engine
  • Value Pack Total: $99.98  $69.99
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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: Aug 29, 2026
  • Q & A: 65 Questions and Answers
  • Software Price: $49.99
  • Testing Engine

About Microsoft 070-774 Exam braindumps

Overview about Overview about MICROSOFT 70-774 Exam

  • Number of Questions: 40-60
  • Format: Multiple choice, multiple answer
  • Registration Fee: 165 USD
  • Length of Examination: 120 minutes
  • Passing Score: 70-80%

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

ValidTorrent 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.

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

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: Evaluate and optimize models- Model evaluation techniques
  • 1. ROC and AUC analysis
    • 2. Accuracy, precision, recall, F1 score
      - Model tuning and improvement
      • 1. Hyperparameter tuning
        • 2. Feature selection and engineering
          Topic 2: 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
                  Topic 3: Develop machine learning models- Select and implement algorithms
                  • 1. Supervised learning models
                    • 2. Unsupervised learning models
                      - Training models in Azure Machine Learning
                      • 1. Use Azure ML Studio experiments
                        • 2. Train models using Python or R scripts
                          Topic 4: Deploy and manage models- Operationalization
                          • 1. Monitor deployed models
                            • 2. Update and retrain models
                              - Model deployment in Azure
                              • 1. Deploy to Azure web services
                                • 2. Batch inference pipelines

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