Azure Data Scientist Associate: Machine Learning Services

Azure    |    Intermediate
  • 8 videos | 44m 21s
  • Includes Assessment
  • Earns a Badge
Rating 4.7 of 18 users Rating 4.7 of 18 users (18)
Azure Machine Learning Studio can be used to create and train machine learning models. Support is provided for multiple development tools, programming languages such as Python and R, and numerous machine learning frameworks. In this course, you'll learn about the services provided by the Azure Machine Learning Studio, how to create an Azure account, and how to register and signup to use Azure Machine Learning Studio. You'll also explore available Azure Machine Learning Studio components, which can be used to create machine learning workflows, ingest data from an Azure Blob storage resource, create and use an Azure Machine Learning workspaces, and create and use a compute resource. 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 azure machine learning services
    Describe the azure machine learning studio
    Register and signup for an azure machine learning studio account and access the studio dashboard
  • Inspect the azure ml studio sidebar components for creating machine learning workflows
    Ingest data from an azure blob storage resource
    Create and use a compute resource
    Summarize the key concepts covered in this course

IN THIS COURSE

  • 1m 27s
    In this video, you’ll learn more about this course and your instructor. In this course, you’ll learn about the services provided by Azure ML Studio. You’ll also create an Azure account and sign up for ML Studio. Finally, you'll discover available ML Studio components that can be used to create machine learning studio workflows, ingest data from an Azure blob storage resource, create an Azure Machine Learning workspace, and create a Compute resource. FREE ACCESS
  • 7m 12s
    In this video, you’ll learn more about Microsoft Azure. Azure provides a multitude of tools and components that help data scientists perform their machine learning objectives. Specifically, Microsoft provides Azure Machine Learning Services. Azure's Machine Learning Services are cloud-based which means you can access them through your browser or with your own code, via an API. This also means the actual Machine Learning that Azure performs, can use the scalability of Microsoft's cloud data centers. FREE ACCESS
  • Locked
    3.  Azure Machine Learning Studio
    9m 46s
    In this video, you’ll learn more about Azure's Machine Learning Studio or ML Studio. ML Studio is a specific implementation of Azure's Machine Learning services. It's cloud-based like all of Azure's Machine Learning services. It’s easy to use, scalable, and highly intuitive. ML Studio is also a fully integrated environment. It includes standard things like data management, compute, and pipelines. FREE ACCESS
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    4.  Creating an Azure ML Studio Account
    5m 22s
    In this video, you’ll watch a demo. In this demo, you’ll create and configure an Azure Machine Learning workspace. To do that, you’ll use the Azure portal to create a machine learning resource. First, you’ll need to make sure you have access to an Azure account. If not, you’ll create one for free at azure.microsoft.com/free. Then, you’ll navigate to the Azure portal in your browser and create an Azure resource. FREE ACCESS
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    5.  Inspecting Azure ML Studio Components
    8m 14s
    In this video, you’ll watch a demo. In this demo, you’ll inspect the Azure ML Studio sidebar components to understand where to find the various tools and components needed for creating machine learning workflows. You’ll do this by clicking through each of the sidebar options in ML Studio. First, you’ll head to the ML Studio in your browser. You'll see along the left-hand side there's a menu of options that are categorized. FREE ACCESS
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    6.  Ingesting Data from Azure Blob Storage
    6m 31s
    In this video, you’ll watch a demo. In this demo, you’ll create a dataset from blobs stored in an Azure storage account. To do that, you’ll create a storage account, create a Blob store, and add some content to that store. Then, you’ll use Azure Machine Learning Studio to connect to it. You’ll see that connecting to a storage account is perfect for situations where you want to add files for AI processing later on. FREE ACCESS
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    7.  Creating and Using Compute
    5m 12s
    In this video, you’ll watch a demo. In this demo, you’ll create and configure a compute instance, as well as a compute cluster in your Azure Machine Learning workspace. To do that, you’ll use the Azure Machine Learning Studio tied to your Machine Learning workspace. First, you’ll head to Azure ML Studio in your browser. In this demo, you’ll focus on creating some compute capability. Click on Compute in the Manage area. FREE ACCESS
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    8.  Course Summary
    38s
    In this video, you’ll summarize what you’ve learned in this course. In this course, you’ve learned about the Machine Learning Services provided by Azure. You explored Azure Machine Learning Services and Azure ML Studio. You also created an Azure ML Studio account and accessed the dashboard. You learned about the Azure ML Studio sidebar components and their uses. Finally, you learned about Azure blob storage data and learned to create a compute resource. FREE ACCESS

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