Free
Course

Explainable AI

Learn how to interpret the decision-making process of deep neural networks.

  • Skill level

    Intermediate
  • Time to complete

    Approx. 1 hour
  • Certificate of completion

    Yes

About this course

The inner workings of many deep learning systems are complicated, if not impossible, for the human mind to comprehend. Explainable Artificial Intelligence (XAI) aims to provide AI experts with transparency into these systems. In this course, you'll describe what Explainable AI is, how to use it, and the data structures behind XAI's preferred algorithms. Next, you'll explore the interpretability problem and today's state-of-the-art solutions to it. You'll identify XAI regulations, define the "right to explanation", and illustrate real-world examples where this has been applicable. You'll move on to recognize both the Counterfactual and Axiomatic methods, distinguishing their pros and cons. You'll investigate the intelligible models method, along with the concepts of monotonicity and rationalization. Finally, you'll learn how to use a Generative Adversarial Network.

Learning objectives

  • discover the key concepts covered in this course
  • recognize what explainable ai is and its significance
  • define the interpretability problem and its importance

How it works

Expert-led videos

In this course, you'll watch videos created by industry-leading experts for some of the biggest tech companies in the world. They'll cover key concepts, go through sample applications, prepare you for industry certifications, and more. Watch on any device — whenever and wherever you want — to learn at your own pace.

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