Introduction to Generative AI
Learn key Generative AI models like ChatGPT, Transformer, GAN, and Diffusion. Develop theoretical foundations and practical skills.
Learn key Generative AI models like ChatGPT, Transformer, GAN, and Diffusion. Develop theoretical foundations and practical skills.
This comprehensive course on Generative AI covers essential models such as Transformers, ChatGPT for text generation, and Generative Adversarial Networks (GANs) and Diffusion Models for image generation. Students will gain a solid understanding of these Generative AI models, their underlying theories, and practical applications. The course is designed to build a strong foundation in Generative AI, preparing learners for more advanced topics in subsequent courses. Through a series of modules, students will explore the basics of generative models, dive into the architecture and functionality of GANs, study language models including Transformers and ChatGPT, and examine image models from basic probabilistic approaches to state-of-the-art Diffusion Models. This course combines theoretical knowledge with practical insights, enabling students to grasp the capabilities and limitations of Generative AI technologies.
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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
Gain insights into joint probability distributions and sampling techniques for generative models
Explore the architecture and training process of Generative Adversarial Networks (GANs)
Study language models, including attention mechanisms and the Transformer architecture
Skills you'll gain
This course includes:
237 Minutes PreRecorded video
21 quizzes, 4 assignments
Access on Mobile, Tablet, Desktop
FullTime access
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There are 4 modules in this course
This introductory course offers a comprehensive exploration of Generative AI, covering key models and techniques. Students will learn about Transformers and ChatGPT for text generation, as well as Generative Adversarial Networks (GANs) and Diffusion Models for image generation. The course provides a strong theoretical foundation while also focusing on practical applications. By the end of the course, learners will have a solid understanding of Generative AI models, their underlying principles, and real-world uses. This knowledge base prepares students for more advanced topics in the field of Generative AI.
Generative Model
Module 1 · 2 Hours to complete
Generative Adversarial Network (GAN)
Module 2 · 2 Hours to complete
Language Model
Module 3 · 3 Hours to complete
Image Model
Module 4 · 1 Hours to complete
Fee Structure
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Instructor
Innovator in AI and Human-Computer Interaction
Dr. Tom Yeh is an Associate Professor of Computer Science at the University of Colorado Boulder, where he also serves as the Director of the Center for the Brain, AI, and Child (BAIC) and is a faculty member of the Mortenson Center in Global Engineering. His research interests encompass a broad range of topics including artificial intelligence (AI), the ethics of AI, generative AI, assistive technology, 3D printing, STEM education, computer vision, brain imaging, and citizen science. Dr. Yeh earned his Ph.D. from the Massachusetts Institute of Technology, focusing on vision-based user interfaces, and subsequently completed a postdoctoral fellowship at the University of Maryland Institute for Advanced Computer Studies (UMIACS). With over 70 published articles to his name, he has received multiple best paper awards from prestigious conferences such as CHI and SIGCSE. His research is supported by notable organizations including the National Science Foundation (NSF), the National Institutes of Health (NIH), and the Defense Advanced Research Projects Agency (DARPA). Dr. Yeh's work not only advances technological innovation but also emphasizes ethical considerations in AI, making significant contributions to both academia and society.
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4.4 course rating
61 ratings
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