Artificial Intelligence and Machine Learning

Artificial Intelligence    |    Beginner
  • 11 videos | 1h 36m 46s
  • Includes Assessment
  • Earns a Badge
Rating 4.8 of 23 users Rating 4.8 of 23 users (23)
This course will demystify the world of artificial intelligence (AI) and machine learning (ML), taking you from foundational concepts to practical applications. You'll learn to distinguish AI and ML, explore how algorithms learn, and perform common tasks like classification and clustering. You will begin by learning to confidently distinguish between the broad umbrella of AI and the specific subset of ML, understanding how each contributes to the landscape of intelligent systems. Next, you'll explore the milestones that shaped AI. Then you will discover how to classify the diverse approaches of machine learning. Finally, you will explore the practical aspects of common machine learning problems. You'll learn the meaning of regression, classification, and clustering and how they're applied in real-world scenarios. Discover how to evaluate model performance and explore the workings of popular traditional models like linear regression and decision trees. You'll also be introduced to ensemble learning, where the "wisdom of the crowds" fuels even more accurate predictions.

WHAT YOU WILL LEARN

  • Discover the key concepts covered in this course
    Recognize the nuances in defining artificial intelligence (ai) and machine learning (ml)
    Provide an overview of how machine learning works
    Outline important milestones in artificial intelligence over the last few decades
    Compare supervised and unsupervised learning techniques
    Outline how regression models work and how they can be evaluated
  • Outline how classification models work and how they can be evaluated
    Outline how clustering models work and how they can be evaluated
    Recognize the algorithmic structure of linear regression, logistic regression, and decision tree models
    Outline how ensemble techniques are implemented
    Summarize the key concepts covered in this course

IN THIS COURSE

  • 2m
    In this video, we will discover the key concepts covered in this course. FREE ACCESS
  • 10m 9s
    After completing this video, you will be able to recognize the nuances in defining artificial intelligence (AI) and machine learning (ML). FREE ACCESS
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    3.  Understanding Machine Learning
    13m 56s
    Upon completion of this video, you will be able to provide an overview of how machine learning works. FREE ACCESS
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    4.  A Brief History of Machine Learning
    11m 36s
    After completing this video, you will be able to outline important milestones in artificial intelligence over the last few decades. FREE ACCESS
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    5.  Supervised and Unsupervised Learning
    6m 20s
    Upon completion of this video, you will be able to compare supervised and unsupervised learning techniques. FREE ACCESS
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    6.  Regression
    10m 46s
    After completing this video, you will be able to outline how regression models work and how they can be evaluated. FREE ACCESS
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    7.  Classification
    8m 59s
    Upon completion of this video, you will be able to outline how classification models work and how they can be evaluated. FREE ACCESS
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    8.  Clustering
    10m 38s
    After completing this video, you will be able to outline how clustering models work and how they can be evaluated. FREE ACCESS
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    9.  Linear Regression, Logistic Regression, and Decision Trees
    11m 18s
    Upon completion of this video, you will be able to recognize the algorithmic structure of linear regression, logistic regression, and decision tree models. FREE ACCESS
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    10.  Ensemble Learning
    8m 42s
    After completing this video, you will be able to outline how ensemble techniques are implemented. FREE ACCESS
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    11.  Course Summary
    2m 22s
    In this video, we will summarize the key concepts covered in this course. FREE ACCESS

EARN A DIGITAL BADGE WHEN YOU COMPLETE THIS COURSE

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