Course 8: Generative Deep Learning

This advanced course introduces the principles and techniques behind models that can generate new data, such as images, text, or music, rather than just recognizing or classifying existing data. It typically covers the theory and practice of generative models and explores how deep learning can be used to learn data distributions and create new, realistic samples.

 This course will enable you to: 

• Understand the basics of Deep Learning

• Gain a full understanding of Generative Adversarial Networks (GANs)

• Fine-tune Autoencoders (AEs)

• Explore Variational Autoencoders (VAEs)

• Learn how to use Recurrent Generative Models

• Implement Data Augmentation & Synthetic Data

• Consider Ethics and Bias in Generative Models

• Work on real projects

• Apply everything using TensorFlow