• Online, Self-Paced
Course Description

Azure Machine Learning Studio can make use of various types of data stores and datasets for training and testing data.

In this course, you'll learn about the types of data stores that are available in Azure, including Azure Storage (blob and file containers), Azure Data Lake stores, Azure SQL Database, and Azure Databricks file system. Next, you'll explore how to create and register data stores and the types of datasets that can be created. Next, you'll learn how to run a notebook using Jupyter to work with data, data stores, and datasets, as well as how to create a compute cluster. You'll examine the available compute targets such as local compute, compute clusters, and attached compute, as well as the types of environments. Finally, you'll learn to create and manage a compute instance and a compute cluster in the Azure Machine Learning workspace.

This course is one in a collection that prepares learners for the Designing and Implementing a Data Science Solution on Azure (DP-100) exam.

Learning Objectives

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Framework Connections

The materials within this course focus on the Knowledge Skills and Abilities (KSAs) identified within the Specialty Areas listed below. Click to view Specialty Area details within the interactive National Cybersecurity Workforce Framework.