Apply Generative Adversarial Networks (GANs)

In this course, you will:- Explore the applications of GANs and examine them wrt data augmentation, privacy, and anonymity

• Leverage the image-to-image translation framework and identify applications to modalities beyond images
• Implement Pix2Pix, a paired image-to-image translation GAN, to adapt satellite images into map routes (and vice versa)
• Compare paired image-to-image translation to unpaired image-to-image translation and identify how their key difference necessitates different GAN architectures
• Implement CycleGAN, an unpaired image-to-image translation model, to adapt horses to zebras (and vice versa) with two GANs in one

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.

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Syllabus

Syllabus - What you will learn from this course
Week 1
Week 1: GANs for Data Augmentation and Privacy
Week 2
Week 2: Image-to-Image Translation with Pix2Pix
Week 3
Week 3: Unpaired Translation with CycleGAN

FAQ

When will I have access to the lectures and assignments?

Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:

The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.

The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.

What will I get if I subscribe to this Specialization?

When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.

Is financial aid available?

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

Reviews

Awesome course, with well explained material that makes state of the art new models easy!

Sharon Zhou, her sister and the rest of the Deeplearning.Ai team is a gift to the world!

I really enjoyed this course. It was easy to follow and clear in terms of content organizations. Thank you!

The applications of GANs were very well illustrated in the course. I thank the coursera team for this :-)