Introduction to AI Techniques in Creative Practice - TFT00119M

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  • Department: Theatre, Film, Television and Interactive Media
  • Credit value: 20 credits
  • Credit level: M
  • Academic year of delivery: 2025-26

Module summary

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.

Module will run

Occurrence Teaching period
A Semester 1 2025-26

Module aims

  • 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

Module learning outcomes

  • 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

Indicative assessment

Task % of module mark
Essay/coursework 100

Special assessment rules

None

Indicative reassessment

Task % of module mark
Essay/coursework 100

Module feedback

You will receive written feedback/mark in line with standard University turnaround times.

Indicative reading

PyTourch Library, https://pytorch.org/docs/stable/index.html

Glassner, A., 2021. Deep learning: a visual approach. No Starch Press.