- Department: Theatre, Film, Television and Interactive Media
- Credit value: 20 credits
- Credit level: M
- Academic year of delivery: 2023-24
- See module specification for other years: 2024-25
This module delivers fundamental concepts and principles required to implement modern AI systems in the context of real-world applications for creative industries along, while allowing to develop relevant programming skills. Key digital image processing techniques, that allow processing and augmentation of datasets containing images, videos, etc. will be introduced and discussed.
Occurrence | Teaching period |
---|---|
A | Semester 1 2023-24 |
To introduce core concepts of Convolutional Neural Networks (CNNs) and data augmentation
To develop students’ skills for implementing AI techniques
To develop students’ understanding of techniques and tools for processing multimedia content in the context of AI applications
Be able to use syntax and semantics of some open source frameworks widely used in the context of AI applications
Be able to apply basic image and sound processing techniques
Be able to critically evaluate complex AI techniques
Task | % of module mark |
---|---|
Essay/coursework | 100 |
None
Task | % of module mark |
---|---|
Essay/coursework | 100 |
You will receive written feedback/mark in line with standard University turnaround times.
PyTourch Library, https://pytorch.org/docs/stable/index.html
Glassner, A., 2021. Deep learning: a visual approach. No Starch Press.