Azure AI Fundamentals: Using Azure Machine Learning Studio

Azure    |    Beginner
  • 18 videos | 1h 29m 46s
  • Includes Assessment
  • Earns a Badge
Rating 4.7 of 27 users Rating 4.7 of 27 users (27)
The Azure Machine Learning Studio is a complete web tool and graphical user interface for building, managing, deploying, evaluating, and testing machine learning algorithms and workloads from initial design to final deployment. In this course, you'll investigate the different features of the Azure ML Studio interface and use it to create datasets, ingest data, create models automatically, build prediction services, and finally, manage endpoints for a machine learning model. Furthermore, you'll explore the datastores, compute resources, experiments, pipelines, and model management interfaces that are utilized when working with Azure ML Studio. This course is one of a collection that prepares learners for the Microsoft Azure AI Fundamentals (AI-900) exam.

WHAT YOU WILL LEARN

  • Discover the key concepts covered in this course
    Create and configure an azure machine learning workspace
    Create and use a compute resource using azure ml studio
    Create and use a dataset in azure ml studio
    Ingest data from an azure storage source
    Ingest data from an azure blob storage resource
    Label data within a dataset in the azure ml studio interface
    Identify how to run test scripts manually using notebook
    Use the automated ml model to create an experiment that will automatically find the best-fit model
  • Run an automated ml model experiment to find the best-fit model
    Evaluate the results of an automated ml model experiment to investigate the best model results
    Deploy an automated ml model as a predictive service
    Test an automated ml predictive service by using it to get predictions based on test data
    Manage and manipulate compute resources and datastores from the azure ml studio
    Manipulate and configure datasets and experiments, including for other team members, in azure ml studio
    Manage stored pipelines and models in azure ml studio
    Manage and configure endpoints in azure ml studio
    Summarize the key concepts covered in this course

IN THIS COURSE

  • 56s
  • 5m 4s
    During this video, you will discover how to create and configure an Azure Machine Learning workspace. FREE ACCESS
  • Locked
    3.  Creating a Compute Resource Using Azure ML Studio
    5m 11s
    In this video, you will learn how to create and use a compute resource using Azure ML Studio. FREE ACCESS
  • Locked
    4.  Creating and Using a Dataset in Azure ML Studio
    4m 33s
    Discover how to create and use datasets in Azure ML Studio. FREE ACCESS
  • Locked
    5.  Ingesting Data from Azure Storage
    7m 46s
    In this video, you will ingest data from an Azure Storage account. FREE ACCESS
  • Locked
    6.  Ingesting Data from Azure Blob Storage
    6m 57s
    After completing this video, you will be able to ingest data from an Azure Blob storage resource. FREE ACCESS
  • Locked
    7.  Labeling Data in Azure ML Studio
    8m 10s
    In this video, you will learn how to label data within a dataset in the Azure ML Studio interface. FREE ACCESS
  • Locked
    8.  Running and Testing Scripts Using Notebook
    5m 34s
    Upon completion of this video, you will be able to identify how to run test scripts using Notebook. FREE ACCESS
  • Locked
    9.  Creating an Automated ML Model
    5m 25s
    During this video, you will learn how to use the automated ML model to create an experiment that will automatically find the best-fitting model. FREE ACCESS
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    10.  Running an Automated Experiment
    4m 32s
    Find out how to run an automated machine learning model experiment to find the best-fit model. FREE ACCESS
  • Locked
    11.  Determining the Best Model after an Experiment
    4m 5s
    Learn how to evaluate the results of an automated ML model experiment to investigate the best model results. FREE ACCESS
  • Locked
    12.  Deploying a Model as a Predictive Service
    3m 9s
    In this video, you will learn how to deploy an automated ML model as a predictive service. FREE ACCESS
  • Locked
    13.  Testing the Predictive Service
    5m 51s
    During this video, you will discover how to test an automated ML predictive service by using it to get predictions based on test data. FREE ACCESS
  • Locked
    14.  Managing Compute Resources and Datastores
    4m 49s
    In this video, you'll learn how to manage and manipulate compute resources and datastores from Azure ML Studio. FREE ACCESS
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    15.  Managing Datasets and Experiments in Azure ML Studio
    5m 23s
    Discover how to manipulate and configure datasets and experiments, including for other team members, in Azure ML Studio. FREE ACCESS
  • Locked
    16.  Managing Pipelines and Models in Azure ML Studio
    6m 36s
    In this video, you will learn how to manage stored pipelines and models in Azure ML Studio. FREE ACCESS
  • Locked
    17.  Managing Endpoints in Azure ML Studio
    4m 49s
    After completing this video, you will be able to manage and configure endpoints in Azure ML Studio. FREE ACCESS
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    18.  Course Summary
    56s
    In this video, we will summarize the key concepts covered in this course. FREE ACCESS

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