Apply Generative Adversarial Networks (GANs) (Coursera)

The DeepLearning.AI Generative Adversarial Networks (GANs) Specialization provides an exciting introduction to image generation with GANs, charting a path from foundational concepts to advanced techniques through an easy-to-understand approach. It also covers social implications, including bias in ML and the ways to detect it, privacy preservation, and more.

Build a comprehensive knowledge base and gain hands-on experience in GANs. Train your own model using PyTorch, use it to create images, and evaluate a variety of advanced GANs.

This Specialization provides an accessible pathway for all levels of learners looking to break into the GANs space or apply GANs to their own projects, even without prior familiarity with advanced math and machine learning research.

Course 3 of 3 in the Generative Adversarial Networks (GANs) Specialization

Syllabus

WEEK 1

GANs for Data Augmentation and Privacy

Learn different applications of GANs, understand the pros/cons of using them for data augmentation, and see how they can improve downstream AI models!

WEEK 2

Image-to-Image Translation with Pix2Pix

Understand image-to-image translation, learn about different applications of this framework, and implement a U-Net generator and Pix2Pix, a paired image-to-image translation GAN!

WEEK 3

Unpaired Translation with CycleGAN

Understand how unpaired image-to-image translation differs from paired translation, learn how CycleGAN implements this model using two GANs, and implement a CycleGAN to transform between horses and zebras!