Back to ListGenerative Artificial Intelligence
Level
Intermediate, Advanced, Specialised, Theory, Algorithmic.
This topic concerns generative artificial intelligence for image/video generation, with its courses ranging from algorithmic tools up to specialised applications. It covers both theoretical knowledge and its real-world applications (e.g., in entertainment).
Learning outcomes
Content /Knowledge
Students should be able to:
- Understand and design different generative models including variation auto-encoders, generative adversarial networks and diffusion models.
- Understand/describe the operation and the prompting procedure of different generative models, as well as their differences/modifications for text/image/video generation.
Methodologicalskills
Students should be able to:
- Design and develop models and algorithms for text/image/video generation using existing programming frameworks.
- Perform model tuning and hyperparameter selection for text/image/video generation.
- Effectively prompt and finetune existing generative models and algorithms.
- Evaluate the quality, diversity and speed of the generative AI models.
Transferrable/Application
Students should be able to:
- Work effectively with others in an interdisciplinary and/or international team.
- Design and manage individual projects.
- Clearly and succinctly communicate their ideas to technical audiences.