Azure AI Fundamentals: Azure Machine Learning Fundamentals

Azure 2024    |    Beginner
  • 12 videos | 1h 6m 40s
  • Includes Assessment
  • Earns a Badge
Rating 4.7 of 3 users Rating 4.7 of 3 users (3)
Artificial intelligence (AI) and machine learning (ML) seem to be everywhere we look, and with each passing day, there are new breakthroughs in AI/ML technology. In this course, you will explore key features and uses of AI and ML, computer vision in Azure, and natural language processing (NLP) in Azure. Then you will discover the purpose of knowledge mining in Azure, investigate document intelligence in Azure, and examine generative AI in Azure. Finally, you'll delve into ethical considerations for AI, challenges and risks associated with AI, and critical considerations for the design and implementation of responsible AI. 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 ai features and uses
    Describe key ml features and uses
    Describe the features and purposes of computer vision with ai
    Outline the purpose of and key considerations for nlp in ml
    Provide an overview of knowledge mining and its purpose in ml applications
  • Outline the role of document intelligence, including how it is leveraged in ml applications
    Describe generative ai and its uses
    Provide an overview of ethical considerations for ai
    Outline challenges and risks commonly associated with ai
    Describe key considerations for designing and implementing responsible ai
    Summarize the key concepts covered in this course

IN THIS COURSE

  • 1m 5s
    In this video, we will discover the key concepts covered in this course. FREE ACCESS
  • 6m 59s
    After completing this video, you will be able to provide an overview of AI features and uses. FREE ACCESS
  • Locked
    3.  Machine Learning (ML)
    7m 41s
    Upon completion of this video, you will be able to describe key ML features and uses. FREE ACCESS
  • Locked
    4.  Computer Vision in Azure
    6m 9s
    After completing this video, you will be able to describe the features and purposes of computer vision with AI. FREE ACCESS
  • Locked
    5.  Natural Language Processing (NLP) in Azure
    7m 20s
    Upon completion of this video, you will be able to outline the purpose of and key considerations for NLP in ML. FREE ACCESS
  • Locked
    6.  Knowledge Mining in Azure
    5m 19s
    After completing this video, you will be able to provide an overview of knowledge mining and its purpose in ML applications. FREE ACCESS
  • Locked
    7.  Document Intelligence in Azure
    5m 56s
    Upon completion of this video, you will be able to outline the role of document intelligence, including how it is leveraged in ML applications. FREE ACCESS
  • Locked
    8.  Generative AI in Azure
    7m 7s
    After completing this video, you will be able to describe generative AI and its uses. FREE ACCESS
  • Locked
    9.  Ethical Considerations for AI
    6m 42s
    Upon completion of this video, you will be able to provide an overview of ethical considerations for AI. FREE ACCESS
  • Locked
    10.  Challenges and Risks of AI
    6m 10s
    After completing this video, you will be able to outline challenges and risks commonly associated with AI. FREE ACCESS
  • Locked
    11.  Responsible AI
    5m 35s
    Upon completion of this video, you will be able to describe key considerations for designing and implementing responsible AI. FREE ACCESS
  • Locked
    12.  Course Summary
    37s
    In this video, we will summarize the key concepts covered in this course. FREE ACCESS

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