AI-900 - Azure AI Fundamentals: Introduction to Azure Machine Learning Studio





The Azure Machine Learning Studio provides a proficient design tool that can be used to build machine learning pipelines. In this course, you'll explore Azure Machine Learning Studio and practice using its features for managing, normalizing, and transforming data for use in regression, classification, and clustering models. You’ll begin with Azure service experiments, classification evaluation metrics, and regression evaluation metrics. Then, you’ll learn how to create an Azure Machine Learning workspace, how to create a compute resource, and how to create a dataset. Finally, you’ll discover how to create model packages and how to deploy models. This course is one of a collection that prepares learners for the Microsoft Azure AI Fundamentals (AI-900) exam.




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AI-900 - Azure AI Fundamentals: Introduction to Azure Machine Learning Studio

  • provide an overview of experiments and how to run them in Azure Machine Learning Studio
  • identify and interpret evaluation metrics for a run of a classification model
  • provide an overview of the evaluation metrics for a run of a regression model
  • create and configure an Azure Machine Learning workspace
  • create a compute resource using Azure Machine Learning Studio
  • create a dataset using Azure Machine Learning Studio
  • create Azure Machine Learning model packages
  • outline key considerations for model deployment in Azure Machine Learning, including endpoints and packages


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