This course on Generative AI Theory & Online Labs is designed to provide students with a comprehensive understanding of generative models in artificial intelligence and hands-on experience through online labs. The course combines theoretical concepts with practical applications to equip students with the skills necessary to develop and implement generative AI solutions.

1. Understand the Foundations of Generative AI: Grasp the theoretical underpinnings of generative models, including probabilistic reasoning, neural networks, and statistical learning.
2. Explore Various Generative Models: Learn about different types of generative models such as GANs (Generative Adversarial Networks), VAEs (Variational Autoencoders), and autoregressive models.
3. Implement Generative Models: Gain practical experience in implementing generative models using popular machine learning frameworks.
4. Analyze and Evaluate Generative Models: Develop skills to critically evaluate the performance and limitations of generative models.
5. Apply Generative AI to Real-World Problems: Learn to apply generative models to solve real-world problems in various domains such as image generation, text generation, and more.