School of Computer Science and Statistics
(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 1, 5 ECTS) This module aims to provide a theoretical and practical understanding of modern scalable systems and architectures, from billions of highly distributed Internet of Things devices, through to present and future concepts, such as Quantum and Nanotech systems.
(Semester 1, 5 ECTS) This module aims to provide both a theoretical and practical understanding of urban
computing and associated cyber-physical concepts, principles, challenges and
solutions.
(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) In this module, students will explore the prevailing vision for an Internet of Things in
a practical, pragmatic manner.
(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) Locate, obtain and critique relevant knowledge and evidence to support innovation and research
(Semester 1, 5 ECTS) Understand what machine learning is and how it works.
(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