MSc Computing Science

Our MSc Computing Science is specially designed for graduates of non-computing subjects to study computer technologies and skills to broaden their knowledge and create new career prospects. It is a one-year full-time course but you can also take it part time over two-years.

In this course, you’ll not only learn essential and advanced computing knowledge and skills but also develop (in Research Techniques Module) your generic, transferable skills for communication, critical thinking and reasoning, problem solving, technical writing, independent and team working and project management. In addition, you learn proper computing professionalism and ethics.

Firstly you will take three fundamental modules: Applications Programming, Database Manipulation, and Internet and Multimedia Techniques. They will teach you essential knowledge and skills in three main and important areas in Computing: Programming, Database and Internet. These modules lay some solid foundations for you to move onto more advanced and/or specialised fields, by choosing some optional modules in advanced and/or specialised areas/themes, such as Machine Learning and Data Mining, Software Engineering and System Development, Computer Graphics and Vision, Distributed and Cloud Computing, Embedded Technologies, etc. If you are not sure what to choose, your adviser will help you.

You also need to do a dissertation project (60 credits) from January to late August, which gives you the chance to specialise in a specific topic and work closely with our world-leading academics. You can choose a project from a list of many proposals made by our faculty members and/or industrial collaborators. Or you may propose your own if you have a good idea. You will be supervised by a supervisor from the School for doing your dissertation, which may result in a publication, and/or some systems that have a potential to be used in research, industries or businesses.

About

If you are a graduate from any non-computing subject and are interested in computers, this Masters course is designed for you to broaden your existing knowledge to the sensational computing fields.

It does not require any previous knowledge and experience in computing as it starts by teaching very fundamental computing knowledge, such as Application Programming, Internet technology, Databases. It then offers plenty of options to steer your learning towards your own aspirations in some more advanced specialised areas, e.g. machine learning, data mining, computer vision, and modern embedded technology, and more.

Upon graduation you’ll be professionally competitive and also highly flexible to take a career in a challenging and changing employment environment. Over the years, our graduates found their employment in various companies, such as Microsoft, BT, Aviva, WorldPay, PwC, China Mobile, public sectors, e.g. National Statistics, and Research Institutes etc.

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Course Reference Number: 663622

Important Information

Whilst the University will make every effort to offer the courses listed, changes may sometimes be made arising from the regular review of course programmes. Where this activity leads to significant (but not minor) changes to programmes, there will normally be prior consultation of students and others. Changes may for example consist of variations to the content and method of delivery of programmes, courses and other services, to discontinue programmes, courses and other services and to merge or combine programmes or courses. The University will endeavour to keep such changes to a minimum, and will inform students.

Assessment for Year 1

We’ll use a wide range of methods to assess your learning – including programming assignments, technical reports, class tests, problem sheets, laboratory reports, presentations and demonstrations. It depends on the module content and learning objectives to decide which ones are used. Most modules are assessed through a mixture of coursework and exams, while some are entirely assessed by coursework only. In your dissertation module, you will be assessed particularly through a demonstration/presentation and the dissertation on your understanding, how you integrate knowledge from different areas of the subject and apply them into your project work.

Structure

On this one-year course you’ll take a set of key modules to give you a thorough grounding in the subject, complemented by your choice of optional modules.

Your key modules will be Applications Programming, Database Manipulation and Internet and Multimedia Techniques. If you have already covered these subjects before, you can consider swapping these for optional modules after getting a permission from the course director.

In the Applications Programming module you’ll gain a clear understanding of Object Oriented Programming (OOP) and essential Objected Oriented Methodologies for developing application software. You’ll learn Java programming language and use it as a vehicle to learn important concepts, such as objects, classes, inheritance, encapsulation and polymorphism. You’ll also learn Unified Modelling Language (UML) as a tool for object-oriented analysis and design, software development life cycle models, software testing strategies and techniques, and version control.

The Database Manipulation module introduces you to most aspects of databases, database manipulation and database management systems. You’ll gain practical experience of database manipulation through the use of SQL and the Java JDBC interface on a relational database management system. Plus you’ll get an introduction to database design using Entity-Relationship modelling and normalisation.

In the Internet and Multimedia Techniques module you will learn about the development and core technologies of the web, website design, deployment on desktop and mobile devices, current issues (such as security), and its impact on society. In the practical part of the module you will work on the design and integration of websites, emphasising maintainability, accessibility and usability.

In addition to these core modules you’ll choose two modules (40 credits) from optional modules covering topics such as Applied Statistics, Computer Vision, Data Mining, Machine Learning, Distributed Computing, Information Visualisation, Modern Embedded Technology and Systems Engineering Issues, Software Engineering, etc.

Two compulsory modules are Research Techniques Module (over two semesters) and the Dissertation Module. For your dissertation you’ll work on a topic of your own choice with the support of a tutor. Examples of recent dissertation titles include:

Hybrid positioning technologies for location-based services with iPhone
Predicting earthquakes with time series data mining
An application of video shot detection
Machine learning ensemble methods for identifying fake on-line reviews or fake news
Predicting the results of tennis matches in real time
Predicting energy consumption for residential customer using smart meter data.

Teaching and Learning

You’ll have an average of 15 hours of contact time per week with teaching staff through lectures, laboratory sessions and seminars – although this may vary depending on your module choices. Additionally, you should allocate at least 25 hours per week for independent study, coursework assignments and projects.

You’ll be taught through lectures, seminars, directed studies and laboratory exercises, involving individual and teamwork. Your modules are all integrated in a web-based framework and you’ll be grouped as teams with other students to design and implement a substantial web-based application.

Independent study

Alongside your formal learning, you’ll study independently to gain a deeper appreciation of specialist topics. You’ll build up to your MSc dissertation project, where you will explore a topic or work on a problem that is usually related to the School's research areas. This project gives you an opportunity to apply the knowledge and skills you have learned from the course to carry out in-depth research on a topic, or develop a working system for various applications. Some project work may be done with companies and could involve paid placement at a company.

Assessment for Year 1

Compulsory Modules

RESEARCH TECHNIQUES (RESEARCH METHODS)

Code CMP-7030Y

Credits 20

This module aims to prepare postgraduate students with necessary intellectual and practical skills for successfully carrying out research work for their MSc Dissertation in Computing Sciences and Computational Biology. Specifically, it teaches research methodologies, techniques and tools used in computing sciences. More importantly, it provides systematic training to enhance students' transferable skills and their understanding in ethics, social and legal issues involved in computing professions.

DISSERTATION

Code CMP-7027X

Credits 60

In this module, each Masters student is required to carry out project work with substantial research and practical elements on a specified topic for their MSc dissertation from January to late August. The topic can be chosen and allocated from the lists of proposals from faculty members, or proposed by students themselves with an agreement from their supervisor and also an approval from the module organiser. The work may be undertaken as part of a large collaborative or group project. A dissertation must be written as the outcome of the module.

Optional A Modules

(60 credits)

APPLICATIONS PROGRAMMING

Code CMP-7000A

Credits 20

The module aims to establish a clear understanding of Object Oriented Programming (OOP) and essential Objected Oriented Methodologies for developing application software. It teaches Java programming language and uses it as a vehicle to learn important concepts, such as objects, classes, inheritance, encapsulation and polymorphism. It also covers the Unified Modelling Language (UML) as a tool for object-oriented analysis and design, software development life cycle models, software testing strategies and techniques and version control.

INTERNET & MULTIMEDIA TECHNIQUES

Code CMP-7003A

Credits 20

In this module you will learn about the current development and core technologies underpinning the Internet and Web. In this module you will learn to use technologies, tools and good practice for web development. Wider technical and social issues (e.g. security, impact on society) will also be covered.

DATABASE MANIPULATION

Code CMP-7025A

Credits 20

This module looks into how best to perform database manipulation, exploring techniques that allow us to use and manage data of various types efficiently. We will examine methods to ensure that correctness of data, in terms of availability, reliability, consistency and scalability can be achieved and maintained. In turn, this will provide opportunities to turning data into knowledge intelligently and informing stakeholders alike and helping them to make better decisions.

Optional B Modules

(40 credits)

SYSTEMS ENGINEERING ISSUES

Code CMP-7004B

Credits 20

This module draws together a wide range of material and considers it in the context of developing modern large-scale computer systems. Topics such as Systems Thinking, Causal Loop Diagrams, Systems Failure, Outsourcing, Quality, Risk Management, Measurement, Project Management, Software Process Improvement, Configuration Management, Maintainability, Testing and Peopleware are covered in this module. The module is supported by well documented case studies and includes guest speakers from the industry.

APPLIED STATISTICS

Code CMP-7008B

Credits 20

This is a module designed to give students the opportunity to apply statistical methods in realistic situations. While no advanced knowledge of probability and statistics is required, we expect students to have some background in probability and statistics before taking this module. The aim is to teach the R statistical language and to cover a range of topics in applied statistics, such as: Linear Regression.

INFORMATION VISUALISATION

Code CMP-7022B

Credits 20

This module is an introduction to information visualisation. You will learn techniques for summarising and presenting a wide range of data. There is a strong emphasis on understanding the appropriate context and use of visualisation techniques. You will also learn about problems and techniques for dealing with large data flows and issues of integrating multiple data sources.

DATA MINING

Code CMP-7023B

Credits 20

This module is designed for postgraduate students studying on MSc courses. You will explore the methodologies of Knowledge Discovery and Data Mining (KDD). You will cover each stage of the KDD process, including preliminary data exploration, data cleansing, pre-processing and the various data analysis tasks that fall under the heading of data mining, focusing on clustering, classification and association rule induction. Through this module, you will gain knowledge of algorithms and methods for data analysis, as well as practical experience using leading KDD software packages.

COMPUTER VISION

Code CMP-7026B

Credits 20

Computer Vision is about “teaching machines how to see”. You will study methods for acquiring, analysing and understanding images in both lectures and laboratories. The practical exercises and projects that you undertake in the laboratory will support the underpinning theory and enable you to implement contemporary computer vision algorithms.

DEVELOPING SECURE SOFTWARE

Code CMP-7038B

Credits 20

This module will focus on the methods and techniques for delivering robust, maintainable and secure software. Students will learn about the importance of security when designing and developing software. The module will include a broad range of software security threats and vulnerabilities and methods of mitigating these issues. The module will cover ethical hacking, penetration testing and structured approaches to security testing.

UBIQUITOUS COMPUTING

Code CMP-7040B

Credits 20

In this module we will introduce the multifaceted topic of Ubiquitous Computing. You will learn about how computing power can be taken away from desktop computer setting and be applied anywhere. The module draws upon many other areas such as Signal Processing, Machine Learning, Human Computer Interaction, Internet of Things, Networks, and the use of hardware such as microcontrollers, various sensors to create systems that sense and interpret the outside world to help solve a wide range of problems.  These systems can be wearable devices, smartphone apps that use the phone’s sensors, or bespoke devices that can be deployed in buildings, vehicles, urban and natural environments. This is project and coursework orientated module with an emphasis on developing your own ideas to gain the skills needed to take the power of computing to be everywhere.

Important Information

Whilst the University will make every effort to offer the modules listed, changes may sometimes be made arising from the annual monitoring, review and update of modules. Where this activity leads to significant (but not minor) changes to programmes and their constituent modules, the University will endeavour to consult with students and others. It is also possible that the University may not be able to offer a module for reasons outside of its control, such as the illness of a member of staff. In some cases optional modules can have limited places available and so you may be asked to make additional module choices in the event you do not gain a place on your first choice. Where this is the case, the University will inform students.

MSc COMPUTING SCIENCE