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Overview
The course “Introduction to Generative Adversarial Networks (GANs)” provides a foundational understanding of GANs, a groundbreaking class of deep learning models used for generating realistic synthetic data. Designed for students, AI practitioners, and researchers, this course explains the core concepts behind GANs and their transformative impact on fields such as computer vision, image synthesis, and creative AI. Participants will learn about the architecture of GANs, which involves two neural networks—the generator and the discriminator—engaged in a dynamic adversarial process. The...
Syllabus
Introduction
- GANs: Generating new worlds
- What you should know
1. Origin and Examples of GANs
- Introduction to GANs
- Origin: Where did they come from?
- How were they developed?
- Early examples of GANs
2. Architecture and Training Methods
- Model architecture
- Training method
- How the different models learn
- Final model output
3. Training a Model
- Create a basic GAN
- Start training and compare results
4. The Future of Generative AI
- Where generative AI has moved to
- Where generative AI will move to
Instructor
Martin Kemka
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