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DP-100: Designing and Implementing a Data Science Solution on Azure

Microsoft Certified:

DP-100: Designing and Implementing a Data Science Solution on Azure

  • Covers Complete & Official Exam Blueprint
  • Summarized content
  • Case study based approach
  • Ready to practice labs
  • Exam tips
  • Mind maps
  • 100% passing guarantee
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Course
Materials
About Microsoft Certified: Azure Data Scientist Associate
Exam Questions Case study, short answer, repeated answer, MCQs
Number of Questions 110-120
Time to Complete 150 minutes
Exam Fee 165 USD

The Microsoft Certified: Candidates for the Azure Associate certification should have subject matter expertise applying data science and machine learning to implement and run machine learning workloads on Azure. Responsibilities for this role include planning and creating a suitable working environment for data science workloads on Azure. You run data experiments and train predictive models. In addition, you manage, optimize, and deploy machine learning models into production. A candidate for this certification should have knowledge and experience in data science and using Azure Machine Learning and Azure Databricks. This exam measures your ability to accomplish the following technical tasks:

  • Manage Azure resources for machine learning (25–30%)
  • Run experiments and train models (20–25%)
  • Deploy and operationalize machine learning solutions (35–40%)
  • Implement responsible machine learning (5–10%)
 
Recommended Knowledge                                                                   
  • Create an Azure Machine Learning workspace
  • Manage data in an Azure Machine Learning workspace
  • Manage compute for experiments in Azure Machine Learning
  • Implement security and access control in Azure Machine Learning
  • Set up an Azure Machine Learning development environment
  • Set up an Azure Databricks workspace
  • Extract facial information from images
  • Create models by using the Azure Machine Learning designer
  • Run model training scripts
  • Generate metrics from an experiment run
  • Use Automated Machine Learning to create optimal models
  • Tune hyperparameters with Azure Machine Learning
  • Select compute for model deployment
  • Deploy a model as a service
  • Manage models in Azure Machine Learning
  • Create an Azure Machine Learning pipeline for batch inferencing
  • Publish an Azure Machine Learning designer pipeline as a web service
  • Implement pipelines by using the Azure Machine Learning SDK
  • Apply ML Ops practices
  • Use model explainers to interpret models
  • Describe fairness considerations for models
  • Describe privacy considerations for data
All the required information is included in this technology workbook.
  Domain
Domain 1 Manage Azure resources for machine learning 25-30%
Domain 2 Run experiments and train models 20-25%
Domain 3 Deploy and operationalize machine learning solutions 35-40%
Domain 4 Implement responsible machine learning 05-10%

Microsoft Certified:

DP-100: Designing and Implementing a Data Science Solution on Azure

  • Covers Complete & Official Exam Blueprint
  • Summarized content
  • Case study based approach
  • Ready to practice labs
  • Exam tips
  • Mind maps
  • 100% passing guarantee

No, there are no pre-requisites for this course

We believe our content is of high quality and combined with your hard efforts it should be fruitful. However even if in second attempt of the exam, you do not succeed in completion of the certification, please do write to us with all supporting documents and we shall refund your course payment.

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