Azure AI Fundamentals: Artificial Intelligence Principles

Azure 2024    |    Beginner
  • 14 videos | 1h 25m 20s
  • Includes Assessment
  • Earns a Badge
Rating 4.0 of 1 users Rating 4.0 of 1 users (1)
Artificial intelligence (AI) and machine learning (ML) are solving a significant number of business and social problems and giving computers a new way to handle and process vast amounts of data. In this course, you'll learn about AI principles, beginning with fairness, reliability, and safety in AI algorithms, privacy and security for responsible AI, and inclusiveness, transparency, and accountability in AI algorithms. Then you'll dig into Azure AI's capabilities, Machine Language Operations (MLOps), Azure AI model management, and Azure AI model training. Finally, you'll explore key concepts surrounding Azure AI content safety and Azure reinforcement learning. 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 how the principle of fairness in artificial intelligence (ai) algorithms results in responsible ai
    Outline how to ensure responsible ai algorithms through reliability and safety
    Outline how privacy and security must be considered when responsibly creating and using ai solutions
    Provide an overview of how inclusiveness in ai algorithms can benefit everyone
    Outline how transparency should be used with ai algorithms in a responsible manner
    Identify how governance and organizational policies provide accountability for ai responsibility
  • Provide an overview of azure and ai service capabilities
    Outline the purpose, features, and characteristics of mlops
    Provide an overview of azure ai model management capabilities, including pipelines, working with assets, how to manage models, and git integration
    Provide an overview of the purpose of training ai models
    Provide an overview of azure ai content safety and content moderator and how they aid in the dealing with harmful content in applications and services
    Review the features and benefits of azure ml reinforcement learning and how it delivers personalized and relevant experiences for users
    Summarize the key concepts covered in this course

IN THIS COURSE

  • 1m 6s
    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 how the principle of fairness in artificial intelligence (AI) algorithms results in responsible AI. FREE ACCESS
  • Locked
    3.  Reliability and Safety in AI Algorithms
    6m 7s
    Upon completion of this video, you will be able to outline how to ensure responsible AI algorithms through reliability and safety. FREE ACCESS
  • Locked
    4.  Privacy and Security and Responsible AI
    6m 18s
    After completing this video, you will be able to outline how privacy and security must be considered when responsibly creating and using AI solutions. FREE ACCESS
  • Locked
    5.  Inclusiveness in AI Algorithms
    6m 33s
    Upon completion of this video, you will be able to provide an overview of how inclusiveness in AI algorithms can benefit everyone. FREE ACCESS
  • Locked
    6.  Transparency in AI Algorithms
    6m 20s
    After completing this video, you will be able to outline how transparency should be used with AI algorithms in a responsible manner. FREE ACCESS
  • Locked
    7.  Accountability in AI Algorithms
    6m 52s
    Upon completion of this video, you will be able to identify how governance and organizational policies provide accountability for AI responsibility. FREE ACCESS
  • Locked
    8.  Azure AI Capabilities
    6m 25s
    After completing this video, you will be able to provide an overview of Azure and AI service capabilities. FREE ACCESS
  • Locked
    9.  MLOps
    6m 34s
    Upon completion of this video, you will be able to outline the purpose, features, and characteristics of MLOps. FREE ACCESS
  • Locked
    10.  Azure AI Model Management
    7m 52s
    After completing this video, you will be able to provide an overview of Azure AI model management capabilities, including pipelines, working with assets, how to manage models, and Git integration. FREE ACCESS
  • Locked
    11.  Azure AI Model Training
    5m 51s
    Upon completion of this video, you will be able to provide an overview of the purpose of training AI models. FREE ACCESS
  • Locked
    12.  Ensuring Azure AI Content Safety
    7m 8s
    In this video, we will provide an overview of Azure AI Content Safety and Content Moderator and how they aid in the dealing with harmful content in applications and services. FREE ACCESS
  • Locked
    13.  Exploring Azure Reinforcement Learning
    10m 33s
    In this video, we will review the features and benefits of Azure ML reinforcement learning and how it delivers personalized and relevant experiences for users. FREE ACCESS
  • Locked
    14.  Course Summary
    43s
    In this video, we will summarize the key concepts covered in this course. FREE ACCESS

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