Azure Data Scientist Associate: Machine Learning Data Stores & Compute

Azure    |    Intermediate
  • 11 videos | 57m 43s
  • Includes Assessment
  • Earns a Badge
Rating 4.9 of 8 users Rating 4.9 of 8 users (8)
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.

WHAT YOU WILL LEARN

  • Discover the key concepts covered in this course
    Describe 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 (dbfs)
    Create and register data stores in machine learning studio for azure blob container, azure file share, and azure data lake storage gen 2
    Describe the types of datasets that can be created and then create, register, and use datasets
    Run a notebook using jupyter to work with data, data stores, and datasets
    Describe types of machine learning studio compute targets such as local compute, compute clusters, and attached compute
  • Show various methods for creating python environments in machine learning studio
    Create and manage a compute instance in the azure machine learning workspace
    Create and manage a compute cluster in the azure machine learning workspace
    Run a notebook using jupyter to create a compute cluster
    Summarize the key concepts covered in this course

IN THIS COURSE

  • 1m 34s
  • 6m 56s
  • Locked
    3.  Creating and Registering Data Stores
    6m 57s
  • Locked
    4.  Working with Datasets
    6m 24s
  • Locked
    5.  Running a Jupyter Notebook to Work with Data
    7m 2s
  • Locked
    6.  Machine Learning Studio Compute Targets
    4m 51s
  • Locked
    7.  Creating Python Environments in Azure ML Studio
    7m 23s
  • Locked
    8.  Working with a Compute Instance in Azure
    4m 33s
  • Locked
    9.  Creating an Azure Machine Learning Compute Cluster
    5m 33s
  • Locked
    10.  Running a Jupyter Notebook with Compute
    5m 50s
  • Locked
    11.  Course Summary
    40s

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