Course overview
This course is an introduction to the mathematical basis for generative AI in stochastic modelling and differential equations, as well as a practical overview of modern approaches to generating synthetic media using deep learning techniques that are built on top of those theoretical foundations.
- Mathematical foundations of generative AI
- Deep learning for generative AI
- Applications and ethics of generative AI
Course learning outcomes
- Describe modern generative AI techniques and connect it with the underlying mathematical principles
- Demonstrate an understanding of how deep learning is used in generative AI and how it can be deployed in real-world applications
- Demonstrate skills in deploying generative algorithms using computer programming of both traditional and modern techniques
- Apply mathematical techniques to solve a variety of problems that underly generative AI at an appropriate level of difficulty
- Demonstrate skills in communicating about generative AI using both mathematics and English, including ethical considerations