Augmented and Virtual Reality – Core Modules
(Semester 1 & 2, 10 ECTS) Assess the theory of classic architecture principles and apply an appropriate architectural model in a team-based application under development
(Semester 1, 5 ECTS) Understand what machine learning is and how it works.
(Semester 1, 5 ECTS) Locate, obtain and critique relevant knowledge and evidence to support innovation and research
(Semester 3, 30 ECTS) Engage in a sustained piece of individual, academic research on a
chosen topic within the field of computer science.
(Semester 1, 5 ECTS) Image processing, feature detection and matching, image registration, recognition
and segmentation – Motion flow and object tracking in video – Mathematics for
(Semester 2, 5 ECTS) The aim of this module is to provide students with a deep understanding of the theory and techniques behind real time animation.
(Semester 1, 5 ECTS) Wave equation and its solution; Maxwell´s equations; Fourier transform and analysis; vibration; mass-spring-damper systems; numerical methods; simulation software.
(Semester 1, 5 ECTS) An introduction to computer graphics; problem domain and applications.
(Semester 2, 5 ECTS)
This course covers fundamentals and state-of-the-art in augmented reality, as well
as related areas of 3D computer vision and graphics.
(Semester 2, 5 ECTS) This module deals with programming for GPU pipeline architectures e.g. geometry,
rasterisation, texturing, fragment / pixel and vertex shaders.
Augmented and Virtual Reality – Elective Modules
(Semester 2, 5 ECTS) The aims of this module are to give the student skills to model, analyse and solve optimisation problems that arise in data analytics and modern computing and communication systems.
(Semester 2, 5 ECTS) This module continues on from CS7CS4 (Machine Learning) with a focus on sampling methods and topical applications.
(Semester 2, 5 ECTS) Appreciate the scope, applications and limitations of artificial intelligence;
(Semester 2, 5 ECTS) In this module, students will explore the prevailing vision for an Internet of Things in
a practical, pragmatic manner.
(Semester 2, 5 ECTS) The objectives of this module are: to develop an in-depth understanding of risk, data
privacy, threats and risks of security breaches, an awareness of computer security
(cryptographic) and protocol techniques, and an ability to make appropriate
decisions about securing data.
(Semester 2, 5 ECTS) This course takes a critical look at some of the architectural issues involved in, and paradigms available for, the construction of large-scale distributed systems such as the infrastructures supporting Google’s search engine or Amazon’s online sales platform. In particular, the course considers how to develop systems that must make trade-offs between performance, consistency, reliability, and availability.
(Semester 2, 5 ECTS) Grasp the scope and limitations of finite state methods in text analysis.
(Semester 2, 5 ECTS) User modelling, including Task modelling