School of Computer Science and Statistics
(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 & 2, 10 ECTS) To understand the theory and be able to apply the following techniques
to a set of data.
(Semester 1, ECTS 5) This module aims to equip the student with the knowledge and tools to visualise data in ways that give insight and understanding.
(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 module continues on from CS7CS4 (Machine Learning) with a focus on sampling methods and topical applications.
(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 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.