Masters by Research in Computing - MRes *

Artificial Intelligence (AI) is a core component of computer science, aiming at developing intelligent agents that mimic human’s cognitive capability in learning, reasoning, and problem-solving. As a branch of AI, machine learning (ML) allows to learn and adapt (from examples), rather than being explicitly programmed for a particular outcome. Both AI and ML rely on the managing, processing and analysis of large datasets, something that Data Science (DS) is concerned with. Many services provided by technology giants such as Google, Microsoft, IBM, Facebook, Amazon, etc. are powered by DS, ML and AI. The recent advances in these subjects have already led to significant industrial applications such as self-driving cars and personalised medicine.

The aim of this module is to identify, apply and design data visualisations. The module provides you with the fundamental principles and practice-based activities needed to design data visualisations for both different contexts, and different types of data. More advanced visualisation concepts and tools for analysing multi-dimensional data and large data sets will also be examined and appraised. You will learn how to employ visualisation as a tool that can help users understand large and complex data sets, conveying the outputs to a diverse audience. Finally, upon completing the module, you should be able to critically approach the design and implementation of data visualisation solutions.

Data mining is the non-trivial process of finding patterns and building models from data stored in data repositories such as databases and data warehouses. At the heart of Big Data Analytics and business intelligence, data mining algorithms provide readily available solutions to many Big Data problems. Data mining is an established field that provides both predictive and descriptive analytics solutions. Such solutions are often generic and can be applied to a wide range of applications from business to scientific and governmental applications.

In this module, you will be taught the internal mechanisms of developing descriptive and predictive data mining methods. Also you will be taught how to use modern data mining tools to build and numerically validate models and patterns extracted from data. You also will be able to critically evaluate current trends in data mining.

Within this module, you will gain knowledge and experience of advanced concepts of database systems and implementation techniques of database management systems. The module begins with reviewing the fundamental concepts necessary for designing, using, and implementing relational database systems. This includes conceptual design, relational modelling, Structured Query language (SQL) programming and database implementation techniques. The module then explores some of the advanced concepts of databases relevant to the role of database administrator. This includes query planning and optimization, and big data technologies. The objective is to enhance the comprehension and the advanced use of database system in order to optimize its performance. In addition, the module contains a substantial practical element utilising advanced SQL, NoSQL and database application development tools, enabling students to gain transferable skills in designing and developing relatively complex ‘real life’ database applications.

This module provides a comprehensive introduction to a vitally important core IT topic (database technology) that is found in almost every IT installation in the world and as such provides extremely good transferable skills. The module not only introduces you to traditional database skills and knowledge (data models, normalization, SQL etc.) but also looks forward into the future IT world via OO, XML and web-database technologies. Once mastered, these database skills will provide a firm foundation for higher-level academic study or a rewarding IT career.

This highly technical material will be delivered by a combination of formal lectures supported by weekly seminar activities, computer-based lab practical work and appropriate directed study and private research. In addition, the use of electronic (web-based) discussion areas and teaching and learning environments (Moodle) will supplement this face-to-face interaction. Finally, you may of course seek personal interviews with the module staff as and when mutually convenient or simply email tutors between scheduled classes.

The Web, as it stands today, primarily depends on human understanding and the interpretation of the vast information space it encompasses. However the Web was originally designed with a goal to support not only human interaction, but also automated machine processing of data with minimal human intervention.

At the heart of Semantic Web is semantic representation and reasoning of data using ontologies and knowledge engineering. This module is about investigating the next generation of the Web, whose key distinguishing characteristics will be the support for and use of semantics in new, more effective, more intelligent, ways of managing information and supporting applications. The module will look into different aspects of Ontology representation, creation, design, reasoning, programming and applications. The course is focused on ontological engineering, which represents an important part of Semantic Web development.

The module provides you with an opportunity to learn and critically reflect on the skills of Advanced Ethical Hacking and information security within a global context. This module builds on the knowledge and underpinning theory from the networking modules and reviews the requirements for a secure network communication system.

The module covers information security governance and its associated body of knowledge and aims to develop your technical competence in information assurance. Security measures for adequate protection of valuable information assets are essential to guard business success, reputation, and compliance with legal and regulatory requirements. This module provides students with in-depth knowledge and understanding of the concepts, methods, processes, tools and practices underlying good information security governance. Topics to be covered include security governance, risk management, security programme development and management, legislation, policies, standards, frameworks, and issuing bodies, business continuity and cybercrime.

Information security for emerging issues such as autonomous systems, Quantum computing, Internet of Things (IoT), Smart Medical Devices, Blockchain, big data and mobile security are covered in this module. We evaluate how emerging technologies are used to commit cyber-enabled crimes such as digital piracy, intellectual property theft and crypto crimes and align them to the UK and EU cyber laws.

Digital forensic investigation techniques are an essential part of the body of knowledge of every cyber security specialist. They facilitate informed timely management of cyber security breaches. Their understanding is important to develop and deploy effective controls for monitoring, detecting and responding to information security incidents within the scope of criminal, civil and enterprise investigations.

The aim of this module is to provide students with an understanding of digital forensic principles, modern examination techniques using current best practices for handling digital evidence in a forensically sound manner. This module emphasises a ‘practice-led’ approach to developing practical skills and theoretical knowledge of digital forensic investigation techniques using open-source and commercial forensic tools. Students will acquire the keys skills necessary in conducting and auditing a systematic forensic investigation of a computer system for user activity, operating system operation, configuration and connectivity. Practical sessions comprises a series of hands-on analytical experiments to progressively unpack the more advanced aspects of the topic being investigated. All practical sessions will be hosted in the specialist Computer Forensics Laboratory.

The term “Human-Centred Design” refers to a set of processes focused around developing products and services with an emphasis around key identified target audiences. This module will therefore focus on combining theoretical concepts around user experience design with practical hands-on approaches used widely in industry and academia to create effective interactive experiences.

You will learn about the user-centred design process and design thinking strategies that place a core emphasis on creating products, applications, and services for “people”. In particular, you will learn techniques for gathering and understanding a target audience’s requirements and methods for undertaking rapid low-fidelity prototyping.

The “UX Development” module is focused around introducing you to industry-leading frameworks, libraries, and platforms that are commonly utilised to develop front-end user experiences.

In particular, you will gain knowledge around different development methodologies that are adopted and utilised in industry and academic environments. Theories will be discussed and practical applications will be analysed for their suitability for deployment.

You will use the knowledge and skills gained during the module to individually develop the front-end user experience for an interactive application (utilising a library/framework introduced in earlier sessions). This application will be based around the concepts you develop in the “Human-Centred Design” and “Visual Interface Design” modules.

“Visual Interface Design” refers to the methods and processes involved in producing effective visual solutions for interactive digital products and services. This module will therefore provide you with the fundamental knowledge and skills to conceive, develop, and present visually compelling outputs. You will examine and explore the key paradigms of visual communication as applied to the delivery of user experiences in digital devices, establish processes for the generation and development of engaging and understandable visually-led user interfaces, and learn approaches for turning digital prototypes into high-fidelity designs.

Low-fidelity prototypes created in the “Human-Centred Design” module will be taken forward and collaboratively developed into high-fidelity designs. This module will therefore furnish you with the ability to work in interdisciplinary teams to fully realise, communicate, and reflect on your concepts.