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  • Course Type: Elective
  • Specialization: Generative AI
  • Instructor: Dr. Tom Yeh, Professor of Computer Science
  • Prior knowledge needed: TBD

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Learning Outcomes

  • Learn the key models for Generative AI, including ChatGPT and the Transformer for text, and the GAN and  the Diffusion Model for images.
  • Develop a strong theoretical foundation and practical math skills for Generative AI.
  • Understand the capabilities and limitations of Generative AI.

Course Content

Duration: 3 hours

Welcome to "Introduction to Generative AI." This first week, you will learn about ChatGPT, the first generative AI system that gained world-wide attention, ushering in a new era of AI research!

Duration: 3 hours

This week, you will learn about the Generative Adversarial Network, the first successful deep learning approach to generating realistic looking images, which started a new wave of generative AI research.

Duration: 3 hours

This week, you will learn about the Transformer Model, which is the model behind most of the state-of-the-art systems for generative text, including ChatGPT.

Duration: 3 hours

This week, you will learn about Diffusion Model, which is the model behind most of the state-of-the-art systems for generative images.

Duration: 2 hours

This module contains materials for the final exam. If you've upgraded to the for-credit version of this course, please make sure you review the additional for-credit materials in the Introductory module and anywhere else they may be found.

Notes

  • Cross-listed Courses: Courses that are offered under two or more programs. Considered equivalent when evaluating progress toward degree requirements. You may not earn credit for more than one version of a cross-listed course.
  • Page Updates: This page is periodically updated. Course information on the Coursera platform supersedes the information on this page. Click the View on Coursera button above for the most up-to-date information.