This introductory course offers a comprehensive exploration of Generative AI, including Transformers, ChatGPT for generating text, and Generative Adversarial Networks (GANs), the Diffusion Model for generating images. By the end of this course, you will gain a basic understanding of these Generative AI models, their underlying theories, and practical considerations. You will build a solid foundation and become ready to dive deeper into more advanced topics in the next course.

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What you'll learn

- 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

Syllabus

Generative Model

Module 1

Welcome to "Introduction to Generative AI." This first week, you will learn about the basics of a Generative Model.

Generative Adversarial Network (GAN)

Module 2

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.

Language Model

Module 3

This week, you will learn about Language Models for Generative AI, including Transformer and ChatGPT.

Image Model

Module 4

This week, you will learn about Image Models for Generative AI, from basic probabilistic models to state-of-the art Diffusion Models.

Generative AI

ChatGPT

Transformer Models

Generative Adversarial Networks

Diffusion Models

GANs

Large Language Models

LLMs

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