Azure AI Fundamentals: Artificial Intelligence Concepts

Azure 2024    |    Beginner
  • 12 videos | 1h 2m 43s
  • Includes Assessment
  • Earns a Badge
Rating 5.0 of 1 users Rating 5.0 of 1 users (1)
Artificial intelligence (AI) and machine learning (ML) are expansive concepts that mean different things to different people. With a vast and ever-growing list of practical applications for AI/ML, it is no surprise that the technology is garnering the attention of organizations far and wide. In this course, you will explore key concepts of AI, beginning with ML types. Then you will discover data in ML, labeled and unlabeled data, and data features. Next, you will delve into key methods and techniques, such as regression, binary classification, multi-class classification, and clustering. Finally, you will focus on the features, advantages, and disadvantages of supervised and unsupervised learning, and the purpose of deep 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 typical ml types
    Outline key considerations for datasets and data manipulation in ml
    Provide an overview of labeled and unlabeled data and their purpose in ml applications
    Describe how features are selected and used from datasets in artificial intelligence (ai) algorithms
    Provide an overview of regression algorithms and their role in ml
  • Outline binary classification, multi-class, multi-label, and imbalanced algorithms and their roles in classifying objects or relationships in ml
    Provide an overview of clustering algorithms and how they can be used to determine groupings in data
    Describe key features, benefits, and drawbacks of supervised ml models
    Describe key features, benefits, and drawbacks of unsupervised ml models
    Outline the purpose and features of deep learning algorithms
    Summarize the key concepts covered in this course

IN THIS COURSE

  • 1m 1s
    In this video, we will discover the key concepts covered in this course. FREE ACCESS
  • 5m 43s
    After completing this video, you will be able to provide an overview of typical ML types. FREE ACCESS
  • Locked
    3.  Data in Machine Learning
    6m 1s
    Upon completion of this video, you will be able to outline key considerations for datasets and data manipulation in ML. FREE ACCESS
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    4.  Labeled and Unlabeled Data
    6m 25s
    After completing this video, you will be able to provide an overview of labeled and unlabeled data and their purpose in ML applications. FREE ACCESS
  • Locked
    5.  Data Features
    5m 56s
    Upon completion of this video, you will be able to describe how features are selected and used from datasets in artificial intelligence (AI) algorithms. FREE ACCESS
  • Locked
    6.  Regression
    6m 59s
    After completing this video, you will be able to provide an overview of regression algorithms and their role in ML. FREE ACCESS
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    7.  Machine Learning Classification
    6m 11s
    Upon completion of this video, you will be able to outline binary classification, multi-class, multi-label, and imbalanced algorithms and their roles in classifying objects or relationships in ML. FREE ACCESS
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    8.  Clustering
    5m 37s
    After completing this video, you will be able to provide an overview of clustering algorithms and how they can be used to determine groupings in data. FREE ACCESS
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    9.  Supervised Learning
    6m 19s
    Upon completion of this video, you will be able to describe key features, benefits, and drawbacks of supervised ML models. FREE ACCESS
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    10.  Unsupervised Learning
    6m 19s
    After completing this video, you will be able to describe key features, benefits, and drawbacks of unsupervised ML models. FREE ACCESS
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    11.  Deep Learning
    5m 36s
    Upon completion of this video, you will be able to outline the purpose and features of deep learning algorithms. FREE ACCESS
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    12.  Course Summary
    36s
    In this video, we will summarize the key concepts covered in this course. FREE ACCESS

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