Computing MSc

You undertake a major, in-depth, individual study in an aspect of your course. Normally computing master’s projects are drawn from commercial, industrial or research-based problem areas. The project involves you in researching and investigating aspects of your area of study and then producing a major deliverable, for example software package or tool, design, web-site and research findings. You also critically evaluate your major deliverable, including obtaining third party evaluation where appropriate.

The major deliverable(s) are presented via a poster display, and also via a product demonstration or a conference-type presentation of the research and findings. The research, project process and evaluation is reported via a paper in the style of a specified academic conference or journal paper. The written report, the major deliverable and your presentation of the product are assessed.

The project management process affords supported opportunities for goal setting, reflection and critical evaluation of achievement.

You develop the knowledge and skills to understand the research process in the field of computing and gain the necessary skills to undertake your masters project. You learn how to evaluate previous academic research and generate evidence material to justify your research. You learn different methods of data generation and develop an understanding of how these methods fit into your primary research, development lifecycle, evaluation of the end user experience, use of academic research literature and research ethics.

You gain experience of application development utilising an agile development approach. You also take responsibility for determining project aims, objectives, roles, tasks, deliverables, schedules and documentation.

By learning agile principles and applying a specific agile approach (eg SCRUM) in a live simulation of the methodology, the module will help you to prepare for contemporary practice in industry, developing both knowledge and skills in the application of agile principles.

You gain a deep insight into the business applications of artificial intelligence (AI) and data science (DA). You explore a range of AI and DS applications such as chatbots, virtual assistants, medical diagnosis, biometric recognition, personalisation, fraud detection and autonomous machines, and analyse both the risks and opportunities of applying AI and DS techniques in these areas.

You gain the foundational knowledge to study a wide range of AI applications and solutions, and are introduced to logic-based knowledge representation, reasoning, problem solving and algorithms, planning and AI applications.

You develop your ability to design and implement database, big data and analytics applications to meet business needs. A case study is used to follow the system development lifecycle. You develop a plausible application from inception to implementation for a real-world scenario.

You investigate the issues and technologies associated with implementing and supporting large scale databases and the services that are needed to maintain and access a repository of data. Investigations are undertaken in a number of areas including big data, data warehouses, integrating legacy data, data management and approaches that support the modelling and visualisation of data for a range of use views.

Blockchain technology is disrupting the financial industry and has many applications in payments, insurance, lending, supply chain, settlement of securities transactions and contract execution. You explore what a blockchain is and how you can create one with simple Python codes. You are introduced to cryptocurrencies and the technical concepts related to financial applications of blockchain.

You study topics related to public and private blockchains, cryptography, cryptocurrencies such as Bitcoin and Ether, smart contracts and applications.

You explore cyber security risk assessment and guidance models, practices, tools and techniques to address threats or vulnerabilities. You also look at how to identify common threats and vulnerabilities using appropriate tools and techniques.

The field of information visualisation has expanded rapidly with many designers generating new forms of charts through which to view quantitative data. This module explores the range of charts available from the traditional such as bar charts and pie charts, to the more novel such as stream graphs, tree maps, sunbursts, and force diagrams, and examines their mathematical properties.

By accurately representing quantitative data using appropriate charts, the intended audience can make their own interpretations of the data and identify emerging patterns and themes that are more readily recognisable in chart form than in the form of raw data.

Deep learning is a subset of machine learning that uses artificial neural networks models with many layers to solve problems in computer vision, speech recognition, natural language process and language translation. The main advantage of deep learning is the ability to learn representations from raw data such as images or text without the need to hand engineer features that represent the input for the model and deliver very high accuracy. Deep learning is now the main technology behind many breakthroughs in object and voice recognition, Google Deep Mind AlphaGo, Siri (Apple), Alexa (Amazon) and Face recognition (Facebook). This module covers various deep learning methods and their practical applications.

You explore what is increasingly recognised as one of the most important areas and greatest threats of cybersecurity - the human being. Criminals are increasingly targeting people as an easy way to access a computer system, this is summed up in a famous quote by a well-known writer on cybersecurity, Bruce Schneier ‘Only amateurs attack machines; professionals target people’.

You explore what these types of cybersecurity threats are and what steps individuals and organisations can take to mitigate against them.

Assessment is a case study, exploring cybersecurity event involving issues of human behaviour. You produce a 4000 - 5000 word report identifying and discussing these issues and proposing some solutions for future prevention.

You focus on the fundamentals of tackling decisions of increasing difficulty in technology, health and business decision, and gain an understanding about the need for, and the effectiveness of, computerised methods for supporting decisions. This includes classifications, data mining and knowledge management-based decision methods with examples of various application domains.

You will be provided with the opportunity to implement simple computerised decision support systems applied to specific real-life problems. The process and practices develop your ability to build simple versions of decision support systems and familiarity with full-scale versions of decision support systems for various application domains.

Dynamic, interactive visualisations enable the reader to explore the data for themselves through a variety of perspectives. Static visualisations are excellent for print medium but are restricted to showing a single perspective and do not handle multidimensional datasets well. Using an interactive graphic the reader can zoom in on sections of the data which are of interest, explore more than one dimension at a time, and sort and filter to discover new patterns and themes within the data. Particularly useful is the ability to provide a macro/micro view of the same data, ie a big picture view of the full dataset from which the reader can then ‘drill down’ into the lower level detail.

This module uses the javascript library for Data-Driven Documents (D3js) for creating animated, dynamic graphics for the web, and looks at other alternatives available.

There has been a rapid growth within the field of the Internet of Things (IoT). IoT is applied in environmental monitoring, smart homes, industrial controls and digital cities. IoT incorporates various techniques, including wireless sensor networks, embedded systems, ubiquitous computing, and machine learning that involve unique IoT devices with a distinct set of security risks.

You explore the important concepts in IoT - the use of Internet technologies to access and interact with objects in the physical world. You also develop the capability to understand potential security risks and produce security architecture of IoT systems. This incudes IoT architecture, IoT operating systems and platforms, low power communications, IoT data analysis, IoT security and identity recognition. You also gain experience of practical skills required for the programming of IoT devices.

Assessment is through 100% continuous assessment where you build a project, which addresses challenges in the IoT security area.

You explore the key legal issues to consider if you are anticipating a career in the IT industry. Key topics include introduction to the English legal system, intellectual property rights, computer crime, computer contracts and liability, privacy and data protection. You apply the legal principles studied to realistic scenarios and case studies from the real-world.

You are assessed through a continuous assessment which explores a current IT or computing issue from a legal and ethical point of view in the form of a mini investigative report.

Machine learning is a subfield of computer science concerned with computational techniques rather than performing explicit programmed instructions. You build a model from a task based on observations in order to make predictions about unseen data. Such techniques are useful when the desired output is known but an algorithm is unknown, or when a system needs to adapt to unforeseen circumstances.

You explore statistics and probability theory as the fundamental task is to make inferences from data samples. The contribution from other areas of computer science is also essential for efficient task representation, learning algorithms, and inferences procedures. You gain exposure to a breadth of tasks and techniques in machine learning.

Assessment is an in course assessment (100%).

This module explores in detail an established and widely recognised governance standard method called PRINCE2®. Students will work on simulated project brief in order to build their understanding and critically review the governance methodology.

The module will focus on the structure, processes, documentation, terminology but also tailoring of the governance method in order to plan for a particular project.

The students will be assessed by two in-course assessment elements (60% and 40%) requiring them to work as part of a team.

PRINCE2® is a registered trademark of AXELOS limited

You develop android apps for smartphone and tablet devices to a professional standard. You explore the industry-standard development processes and tools used to build today’s mobile apps. You are also informed by current industry practice, to plan and execute a successful software development project.

Assessment is an in-course assignment. You design, plan and build a mobile app for a smartphone or tablet device using industry approaches. Your artefacts and decisions are assessed by a presentation with supporting materials.

You gain a thorough understanding of the concepts and technologies used in modern mobile devices such as phones, PDAs and laptops. You learn about the hardware used by mobile devices and the networking technologies that allow them to communicate with each other and the outside world. You also explore data compression techniques and security. You attend a series of lectures, tutorials and seminars.

You are assessed by a 100% ICA. You work individually researching an agreed topic and produce a research report (4,000 words).

You cover theoretical concepts including cryptography and cyber security models alongside the practical issues of cyber attacks and countermeasures. You study topics in access control, symmetric and public key cryptography protocols, digital signatures, authentication protocols, wireless network and security, firewall, network security attacks, penetration testing, intrusion detection and access control lists.

You are given an intensive introduction to programming assuming little, if any, previous experience. You cover the principles of object oriented programming and event driven GUI (graphical user interfaces) systems using the Java Language. You are introduced to the fundamental skills required for mobile app and pattern driven development. Topics covered include:
• Object oriented concepts: classes, objects, methods, inheritance, polymorphism.
• Event handling and elements of the Swing GUI API.
• Software development using a source code editor and an IDE.
• Software design techniques, problem solving and algorithm development.
• Software documentation.
• Software testing and evaluation techniques.
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You are assessed by individual course work that requires you to produce a portfolio of practical and reflective work.

Contemporary project management is an evolving and extensive discipline that has grown substantially to meet the needs of modern project management demands. This module cultivates detailed and critical awareness of this domain and its expanding range of philosophies, tools and frameworks.

The purpose of this module is to introduce students to the expanding discipline of project management and familiarise them with modern and contemporary project management modalities and the importance of effective project management to organisational functioning, enterprise growth and development.

We provide you with an advanced level of study in risk management in projects. You explore a range of tools and techniques used in risk identification, qualitative and quantitative risk analysis, risk-planning responses, PERT and risk monitoring. You learn about financial risk, project-appraisal methods and the application of a decision tree within a project.

You gain awareness of probability theory that represents the corner stone of risk management. Invited speakers from the industry give an overview of risk management in different projects; for example IT, finance, construction, and oil and gas. You work in groups on project case studies which apply risk management theory. In addition, you gain hands-on experience in applying the @RISK© tool to a variety of scenarios of risk factors. You develop a deep understanding of the systematic process of risk management and application of @RISK© software.

You gain an introduction to the Python programming language and its application to solving problems in digital innovation. This involves the principles of programming, the syntax and structure of Python, its relevant libraries and modules, and how it is incorporated in existing software tools. You form a solid foundation of producing software solutions to real-world problems.

You develop necessary knowledge and practical understanding of the main statistical techniques. You explore quantitative and qualitative data analysis techniques, reflecting scientific and social science methods. You focus on correlation testing, regression, data categories, normalization - the tools needed, rather than the philosophical approaches. You understand how to apply valid techniques and interpret the results in preparation for experimental work.

Your assessment is a single ICA based around a number of case studies that require you to identify the correct data analysis and modelling processes.

The internship options are:

Vocational: spend one semester working full-time in industry or on placement in the University. We have close links with a range of national and international companies who could offer you the chance to develop your knowledge and professional skills in the workplace through an internship. Although we cannot guarantee internships, we will provide you with practical support and advice on how to find and secure your own internship position. A vocational internship is a great way to gain work experience and give your CV a competitive edge.

Research: develop your research and academic skills by undertaking a research internship within the University. Experience working as part of a research team in an academic setting. Ideal for those who are interested in a career in research or academia.