Month 12: Generative Models

Week 1: Introduction to Generative Models

• Recap of Machine Learning and Deep Learning Fundamentals
• Overview of Generative Models
• Types of Generative Models

Week 2: Autoencoders

• Introduction to Autoencoders
• Variational Autoencoders (VAEs)
• Convolutional Autoencoders (CAEs)
• Applications of Autoencoders

Week 3: Generative Adversarial Networks (GANs)

• Introduction to GANs
• Architecture of GANs
• Training GANs
• Applications of GANs

Week 4: Other Generative Models

• Boltzmann Machines
• Restricted Boltzmann Machines (RBMs)
• Deep Belief Networks (DBNs)
• Applications of Other Generative Models