This course will teach you to understand and build various GANs using PyTorch, including basic GANs and advanced DCGANs. You'll explore techniques to control GANs and build conditional GANs. Additionally, you'll compare generative models, assess GAN fidelity and diversity using the FID method, detect bias in GANs, and implement StyleGAN techniques. The course also covers using GANs for data augmentation and privacy preservation, explores GAN applications, and guides you through building Pix2Pix and CycleGAN for image translation.
🆓 Free to Audit
🕒 Approx. 2 months at 10 hours a week
📈 Intermediate Level
🧾 Paid Certificate Available Upon Completion
🎓 Offered by DeepLearning.AI via Coursera
