Azure AI Fundamentals: Machine Learning with Azure AI

Azure 2024    |    Beginner
  • 16 videos | 1h 31m 19s
  • Includes Assessment
  • Earns a Badge
Rating 3.0 of 1 users Rating 3.0 of 1 users (1)
Azure Machine Learning Studio is part of a suite of services that facilitates machine learning (ML) by providing a single interface for building, managing, deploying, testing, and collaborating. In this course, you will discover Azure AI and ML services, beginning with the features and capabilities of Azure Machine Learning Studio and Azure OpenAI Studio. Then you will dig into how to create an Azure Machine Learning Studio account and Azure AI service resources. Next, you will investigate Azure AI services, authentication for Azure AI services, and Azure ML workloads. Finally, you will explore compute resources, dataset management, and pipeline management. 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
    Provide an overview of machine learning (ml) services on the azure platform
    Identify the key features and capabilities of azure machine learning and azure machine learning studio
    Provide an overview of the azure machine learning studio interface and features
    Outline the key features and capabilities of the web-based azure openai studio and describe how it can be used to interact with the azure openai service
    Provide an overview of the azure openai studio web interface and features
    Create and configure an azure machine learning studio account
    Use the azure portal to create azure ai services resources
  • Use azure ai service studio interfaces and associate an ai service resource
    Ensure that only authorized individuals have access to an ai service through authentication
    Identify the processes and functions used in azure machine learning studio for creating, running, and maintaining ai workloads
    Outline the features of a compute target
    Provide an overview of datasets and how they are created and managed
    Manage pipelines in the azure machine learning studio interface
    Recognize limitations and features of automated ml model training
    Summarize the key concepts covered in this course

IN THIS COURSE

  • 1m 2s
    In this video, we will discover the key concepts covered in this course. FREE ACCESS
  • 7m 13s
    After completing this video, you will be able to provide an overview of machine learning (ML) services on the Azure platform. FREE ACCESS
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    3.  Azure Machine Learning Studio
    6m 49s
    Upon completion of this video, you will be able to identify the key features and capabilities of Azure machine learning and Azure Machine Learning Studio. FREE ACCESS
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    4.  Exploring Azure Machine Learning Studio Features
    6m 58s
    In this video, we will provide an overview of the Azure Machine Learning Studio interface and features. FREE ACCESS
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    5.  Azure OpenAI Studio
    7m 23s
    After completing this video, you will be able to outline the key features and capabilities of the web-based Azure OpenAI Studio and describe how it can be used to interact with the Azure OpenAI Service. FREE ACCESS
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    6.  Exploring Azure OpenAI Studio Features
    5m 58s
    In this video, we will provide an overview of the Azure OpenAI Studio web interface and features. FREE ACCESS
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    7.  Creating an Azure Machine Learning Studio Account
    6m 14s
    Find out how to create and configure an Azure Machine Learning Studio account. FREE ACCESS
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    8.  Creating Azure AI Service Resources
    5m 52s
    Learn how to use the Azure portal to create Azure AI services resources. FREE ACCESS
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    9.  Working with Azure AI Services
    6m 12s
    During this video, discover how to use Azure AI service studio interfaces and associate an AI service resource. FREE ACCESS
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    10.  Authenticating Azure AI Services
    5m 34s
    In this video, find out how to ensure that only authorized individuals have access to an AI service through authentication. FREE ACCESS
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    11.  Azure Machine Learning Workloads
    6m 29s
    After completing this video, you will be able to identify the processes and functions used in Azure Machine Learning Studio for creating, running, and maintaining AI workloads. FREE ACCESS
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    12.  Compute Resources
    6m 49s
    Upon completion of this video, you will be able to outline the features of a compute target. FREE ACCESS
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    13.  Dataset Management
    6m 41s
    After completing this video, you will be able to provide an overview of datasets and how they are created and managed. FREE ACCESS
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    14.  Managing Pipelines in Azure ML Studio
    5m 22s
    In this video, discover how to manage pipelines in the Azure Machine Learning Studio interface. FREE ACCESS
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    15.  Algorithms Used for Training
    6m
    After completing this video, you will be able to recognize limitations and features of automated ML model training. FREE ACCESS
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    16.  Course Summary
    44s
    In this video, we will summarize the key concepts covered in this course. FREE ACCESS

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