Cloud Computing and Big Data remain hot topics in the media and there is strong demand for graduates with technical skills in this area. Kent’s Advanced Computer Science (Cloud Computing & Big Data) MSc equips you with the advanced knowledge and skills for a wide range of careers from data analysts to computer scientists and IT consultants.
The programme combines a wide choice of advanced topics in computer science with specialist modules relating to cloud computing and big data.
This programme is available with an optional industrial placement which provides an opportunity to work in real-world, technical and business roles, enhancing your study experience and having a dramatic impact on your choices after graduation. We have strong links with industry including Cisco, IBM, Microsoft and Oracle and are among the top ten in the UK for graduate employment prospects.
The Advanced Computer Science (Cloud Computing & Big Data) MSc is aimed at graduates considering a career in research and development. It would also provide an excellent foundation for PhD study.
About the School of Computing
Our world-leading researchers earned us an outstanding result in the recent Research Excellence Framework (REF). Our submission was ranked 12th in the UK for research intensity, with an impressive 98% of our research judged to be of international quality.
Strong links with industry underpin all our work, notably with Cisco Systems Inc, Huawei, Microsoft, Oracle, IBM, Nvidia, Erlang Solutions, GCHQ and Google.
Our programmes are taught by leading researchers who are experts in their fields. The School of Computing at Kent is home to several authors of leading textbooks, a National Teaching Fellow, an IET (Institute of Engineering and Technology) Fellow and two Association of Computer Machinery (ACM) award-winning scientists. Kent was awarded gold, the highest rating, in the UK Government’s Teaching Excellence Framework*.
While studying with us, you can gain work experience through an industrial placement. Our dedicated placement team can help you gain a suitable paid position and provide support throughout your placement.
We have a large range of equipment providing both Linux and PC-based systems. Our resources include a multicore enterprise server and a virtual machine server that supports computer security experiments.
*The University of Kent's Statement of Findings can be found here
In the Research Excellence Framework (REF) 2014, research by the School of Computing was ranked 12th in the UK for research intensity.
An impressive 98% of our research was judged to be of international quality, with 81% of this judged world-leading or internationally excellent. The School’s environment was judged to be conducive to supporting the development of research of international excellence.
Each of our taught MSc courses is available in several formats to accommodate students from different backgrounds and to provide maximum flexibility. See more about Taught Master's course formats.
The following modules are indicative of those offered on this programme. This list is based on the current curriculum and may change year to year in response to new curriculum developments and innovation.
You take compulsory modules CO820 - Data and Signal Analysis for Computing, CO821 - Programme for Data Handling, CO836 - Cognitive Neural Networks, CO816 - eHealth, CO880 - Project and Dissertation and those listed below.
|Compulsory modules currently include||Credits|
CO832 - Data Mining and Knowledge Discovery
This module explores a range of different data mining and knowledge discovery techniques and algorithms. You learn about the strengths and weaknesses of different techniques and how to choose the most appropriate for any particular task. You use a state-of-the-art data-mining tool, and learn to evaluate the quality of discovered knowledge.View full module details
CO839 - Data Science
The amount of data generated worldwide is more than doubling every year. Traditional data analysis techniques are inadequate for dealing with the vast ocean of data. This module introduces modern techniques, platforms and tools for analysing large data sets efficiently, along with key applications, to equip students to join the new generation of data scientists sought after by industry and academia.
• Information theory and information entropy
• More: it's all data rather than samples
• Messy: it’s disorder/uncertainty rather than accuracy (Chua’s local activity)
• Correlation: it’s correlation rather than causation
• Open Data
• Data ethics: algorithmic transparency, bias, and discrimination.
• Big personal data and data protection
• Linear programming
• Data civilisation: creating tools for pervasive understanding of publicly available data
• Deep learning
• Predictive analytics of sensor/mobile/social networks
• Digital/personal healthcare systems
• Next generation data scientistsView full module details
CO846 - Cloud Computing
"Cloud computing is Internet-based computing, whereby shared servers provide resources, software, and data to computers and other devices on demand, as with the electricity grid. Cloud computing is a natural evolution of the widespread adoption of virtualization, service-oriented architecture and utility computing. Details are abstracted from consumers, who no longer have need for expertise in, or control over, the technology infrastructure "in the cloud" that supports them.
Cloud computing describes a new supplement, consumption, and delivery model for IT services based on the Internet, and it typically involves over-the-Internet provision of dynamically scalable and often virtualized resources. It is a byproduct and consequence of the ease-of-access to remote computing sites provided by the Internet. This frequently takes the form of web-based tools or applications that users can access and use through a web browser as if it were a program installed locally on their own computer."
The curriculum will include:
• Overview of web services and their use in grid/cloud computing;
• Review grid computing technologies and the relations and differences between grid computing and cloud computing;
• Virtualisation technologies, tools for cloud computing (Xen or KVM);
• Open source cloud infrastructures and applications, including Hadoop,Eucalyptus etc;
• Cutting edge commercial cloud infrastructure and applications.View full module details
CO885 - Project Research
The crowning piece of most Masters degrees is the Project and Dissertation in which you apply a wide range of skills learned in the taught modules to an interesting research problem or practical application of your choice. The Project Research module provides useful transferable skills for doing the project, and supports you in some preparatory tasks such as literature study and project planning.
Training in research methods is provided through a series of workshops, covering the following topics:
• Introduction to research
• Project selection
• Topic analysis
• Information gathering
• Simulation, experimentation and data analysis
• Writing about research
• Presenting research
• Intellectual property
• The publication process
• The review process
The module culminates in a mini-conference where students present their research.View full module details
Teaching and Assessment
Assessment is through a mixture of written examinations and coursework, the relative weights of which vary according to the nature of the module. The final project is assessed by a dissertation.
This programme aims to:
- enhance the career prospects of graduates seeking employment in the computing/IT sector
- prepare you for research and/or professional practice at the forefront of the discipline
- develop an integrated and critically aware understanding of one or more areas of computing/IT and their applications (according to your degree title)
- develop a variety of advanced intellectual and transferable skills
- equip you with the lifelong learning skills necessary to keep abreast of future developments in the field.
Knowledge and understanding
You gain knowledge and understanding of:
- how to engineer software systems that satisfy the needs of customers, using a state-of-the art methodology and an industrially-relevant programming language
- a broad variety of advanced topics relating to computing/IT
- cloud computing technologies and the analysis of large data sets
You develop intellectual skills in:
- the ability to identify, analyse and formulate criteria and specifications appropriate to a given problem
- the ability to model problems and their solutions with an awareness of any tradeoffs involved
- the ability to evaluate systems, processes or methodologies in terms of general quality attributes and possible tradeoffs
- the ability to deal with complex issues both systematically and creatively
- the ability to work with self-direction and originality in tackling and solving problems
- the ability to make sound judgements in the absence of complete data
- the ability to review a research paper or technical report critically and to present your findings to a group of peers
- the ability to plan and execute a substantial research or development-based project and to report the work in the form of a dissertation.
You gain subject-specific skills in:
- the ability to specify, design, implement and test computer-based systems
- the ability to deploy effectively the tools used for the construction and documentation of software
- the ability to undertake practical work that explores techniques covered in the programme and to analyse and comment on the findings
- the abillity to perform operations in existing cloud infrastructures and to create new cloud infrastructures using appropriate tools.
You gain the following transferable skills:
- the ability to plan, work and study independently and to use relevant resources in a manner that reflects good practice
- the ability to make effective use of general IT facilities, including information retrieval skills
- time management and organisational skills, including the ability to manage your own learning and development
- an appreciation of the importance of continued professional development as part of lifelong learning
- the ability to work effectively as a member of a team
- the ability to communicate technical issues clearly to specialist and nonspecialists
- the ability to present ideas, arguments and results in the form of a well-structured written report
- the ability to act autonomously in planning and implementing tasks at professional or equivalent level.
Our graduates have gone on to work in:
- software engineering
- mobile applications development
- systems analysis
- web design and e-commerce
- finance and insurance
Recent graduates have gone on to develop successful careers at leading companies such as:
- BAE Systems
- The Walt Disney Company
Help finding a job
The University has a friendly Careers and Employability Service, which can give you advice on how to:
- apply for jobs
- write a good CV
- perform well in interviews.
The School has a dedicated Employability Coordinator who is a useful contact for all student employability queries.
You can gain practical work experience as part of your degree through our industrial placements scheme - we have a dedicated Placement Team who can give advice and guidance. All our placements are in paid roles.
In previous years, students have worked at a wide range of large and small organisations, including well-known names such as:
- Kent Police
- Morgan Stanley
- The Walt Disney Company.
You can take your work placement abroad. Previous destinations include Hong Kong and the US.
An industrial placement gives you invaluable workplace experience, which greatly enhances your employment prospects and also helps put your academic learning into a real-world context.
The University has already been hugely proactive in my future career plans by helping me to get real experience during such an amazing industrial placementDaniel Lawrence Advanced Computer Science MSc
The School of Computing has a large range of equipment providing both UNIX (TM) and PC-based systems and a cluster facility consisting of 30 Linux-based PCs for parallel computation. New resources include a multi-core enterprise server with 128 hardware threads and a virtual machine server that supports computer security experiments.
All students benefit from a well-stocked library, giving access to e-books and online journals as well as books, and a high bandwidth internet gateway. The School and its research groups hold a series of regular seminars presented by staff as well as by visiting speakers and our students are welcome to attend.
Our taught postgraduate students enjoy a high level of access to academic staff. Students whose course includes an industrial placement are supported by a dedicated team which helps them gain a suitable position and provides support throughout the placement.
Dynamic publishing culture
Staff and research students publish regularly and widely in journals, conference proceedings and books. Among others, they have recently contributed to: Expert System with Applications; Data Mining and Knowledge Discovery; ACM Data Communication (SIGCOMM); ACM Transactions on Information Systems; Distributed Computing Systems; Internet, Cloud, and Enterprise Networks and Services; IEEE Transactions on Pattern Analysis and Machine Intelligence.
Links with industry
Strong links with industry underpin all our work, notably with Cisco, Microsoft, Oracle, IBM, Agilent Technologies, Erlang Solutions, Hewlett Packard Laboratories, Ericsson and Nexor.
The Kent IT Consultancy
The Kent IT Consultancy (KITC) provides School of Computing students with consultancy experience while studying. KITC provides a project-based consulting service to small businesses in Kent. Its wide variety of services range from e-commerce solutions and network support contracts to substantial software development projects.
Global Skills Award
All students registered for a taught Master's programme are eligible to apply for a place on our Global Skills Award Programme. The programme is designed to broaden your understanding of global issues and current affairs as well as to develop personal skills which will enhance your employability.
A first, 2.1 or good 2.2 honours degree (or equivalent) in computing or a related subject.
All applicants are considered on an individual basis and additional qualifications, professional qualifications and experience will also be taken into account.
Please see our International Student website for entry requirements by country and other relevant information for your country. Please note that international fee-paying students cannot undertake a part-time programme due to visa restrictions.
English language entry requirements
The University requires all non-native speakers of English to reach a minimum standard of proficiency in written and spoken English before beginning a postgraduate degree. Certain subjects require a higher level.
For detailed information see our English language requirements web pages.
Need help with English?
Please note that if you are required to meet an English language condition, we offer a number of pre-sessional courses in English for Academic Purposes through Kent International Pathways.
Data Science Research Group
Data Science is about developing new techniques to better understand data and draws on many areas within and outside of computer science. Our research group develops and applies methods to interpret rich information sources.
Our research comes under three themes:
- Dr Caroline Li gathers and analyses EEG data for the study of seasonal affective disorder.
- Dr Srivas Chennu works on neurodynamics of consciousness, developing new tools to study brain networks, including improved diagnostics and prognostics during emergence from coma. He also uses neural network modelling for predictive coding in cognition.
- Professor Ian McLoughlin studies speech signal processing, human hearing, automatic speech recognition as well as deep neural network acoustic models.
- Dr Palani Ramaswamy has worked on biological signal analysis, brain-computer interfaces and biometrics. He has applied machine learning techniques to these and other fields.
- Dr Fernando Otero, Professor Alex Frietas and Dr Matteo Migliavacca, have developed new search-based approaches to computation, such as ant colony optimisation methods for predicting protein function.
- Professor Frank Wang has shown that memristors can provide a radically new way to construct neural networks. In addition he has developed models of cloud computing for big data.
- Dr Michael Kampouridis and Dr Fernando Otero research in the areas of algorithmic trading and financial forecasting. They have worked with different types of data, such as foreign exchange ultra-high frequency data. Algorithms they've used include genetic programming and ant colony optimisation.
- Dr Kampouridis works on the pricing of weather derivatives by using machine learning algorithms.
Programming Languages and Systems Group
Our research involves all aspects of programming languages and systems, from fundamental theory to practical implementation. The Group has interests across a wide range of programming paradigms: object-oriented, concurrent, functional and logic. We research the links between logic and programming languages, the verification of the correctness of programs, and develop tools for refactoring, tracing and testing. We are interested in incorporating safe concurrent programming practices into language design.
The Group is also interested in practical implementation of programming languages, from massively concurrent parallel processing to battery-operated mobile systems. Particular research topics include lightweight multi-threading kernels, highly concurrent operating systems, memory managers and garbage collectors.
Research areas include:
- theoretical and architectural questions concerning designs for both hardware and software
- abstractions and implementations of concurrency in programming languages
- formal specification of systems and their architecture
- design patterns and tools for enabling the safe and scalable exploitation of concurrency
- compilers, memory managers and garbage collectors
- lightweight multi-threading kernels and highly concurrent operating systems
- refactoring of functional and concurrent languages
- applications of formal methods to provably correct, secure systems
- model checking and abstract interpretation, including applications to discovering security vulnerabilities
- program verification and theorem proving
Computational Intelligence Group
This Group brings together interdisciplinary researchers investigating the interface between computer science and the domains of bioscience and cognition. In terms of applying computation to other domains, we have experts in investigating the modelling of gene expression and modelling of human attention, emotions and reasoning. From the perspective of applying biological metaphors to computation, we research new computational methods such as genetic algorithms and swarm intelligence.
The Group also develops novel techniques for data mining, visualisation and simulation. These use the results of interdisciplinary research for finding solutions to computationally expensive problems.
The Group has strong links with other schools at the University of Kent, as well as with universities, hospitals and scientific research institutes throughout the country and internationally.
Areas of research activity within the group include:
- bio-inspired computing including neural networks, evolutionary
- computing and swarm intelligence
- application of computational simulations in biology and medicine
- systems biology including gene expression modelling
- theory and application of diagrammatic visualisation methods
- data mining and knowledge discovery
- construction of computational models of the human cognitive and neural system.
Cyber Security Research Group
Security - of information, systems, and communications - has become a central issue in our society. Interaction between people's personal devices (far beyond just phones and computers) and the rest of the connected world is nearly continuous; and with the advent of the Internet Of Things its scope will only grow.
In that context, so much can go wrong - every communication can potentially be intercepted, modified, or spoofed, and surreptitiously obtained data can be commercially exploited or used for privacy invasions. In fact, data flows in society are such that many people already feel they have lost control over where (their) data goes.
The cyber security research group operates within that context. All members bring a particular technological emphasis - the analysis of particular classes of security problems or their solutions - but are fully aware that it all fits within a wider context of people using systems and communicating data in secure and insecure ways, and how external pressures beyond the mere technology impact on that. The topic of computer security then naturally widens to include topics like privacy, cyber crime, and ethics and law relating to computing, as well as bringing in aspects of psychology, sociology and economics.
From that perspective, the Cyber Security research group played a key role in setting up, and continues to be a core contributor to, the University's Interdisciplinary Cyber Security Research Centre, see www.cybersecurity.kent.ac.uk.
The group has a strong involvement with postgraduate teaching in this area. It teaches most of the core modules in MSc programmes in Computer Security, and Networks and Security. A new (from September 2017) MSc Course in Cyber Security has been provisionally certified by GCHQ. The group is also involved in undergraduate modules in this area, as well as postgraduate programmes in other schools such as the MSc Information Security and Biometrics, and in UK activities to define curricula in Cyber Security.
Areas of Research Activity
Members are engaged in the following areas of research (research areas in more detail) .
- Data Ethics and Privacy
- Authorisation Infrastructures
- Internet Of Things Security and Privacy
- Quantum Computation and Information, with Security Applications
- Formal Methods for Cryptography
- Steganography and Steganalysis
- Trust Management and Metrics and Reputation Systems
- Tools for Vulnerability Analysis
- Self-Adaptation applied to Security and Privacy
- Cloud Security
- Human Aspects of Security
- Blockchain and Distributed Ledger Technology
- Identity Management
Computing Education Group
We focus on disciplinary-specific pedagogy, especially the teaching and learning of computer science and programming.
Our research interests focus on understanding the aspects of learning that are specific to computing education, and which range from examining general theories of learning, through thematically focused investigations (such as gender), to tool construction. We examine education from multiple aspects, including supporting computing education research infrastructure, working with teachers, or focusing on student learning.
Areas of interest include:
- building an evidence base of research on early programming education
- tool support for learning and teaching of programming, including custom-made development tools, such as educational programming languages, or development environments, which can adapt to changes in programming paradigms and technology and pedagogical advances
- analysis of data generated as a part of the learning process, which could be text-based, naturally occurring in the classroom (eg, assessments), generated as a reflective process on learning (eg, diaries), or generated from interaction with programming environments.
Staff research interests
Full details of staff research interests can be found on the School's website.
Michael Kampouridis: Lecturer
Computational finance; application of computational intelligence (CI) techniques to business-related problems, such as economics and finance; use of evolutionary techniques (eg, genetic algorithms, genetic programming); financial forecasting; intelligent decision support systems for business.View Profile
Dr Caroline Li: Lecturer
Tools for controlling computer/robot using brain signal; body sensor data fusion for healthcare and sports; methods for diagnosing, classifying and monitoring states of brain health/ illness; signal processing and machine learning methods.View Profile
Fernando Otero: Lecturer
Development of ant colony optimisation algorithms for data mining; economic applications of data mining; bioinformatics; evolutionary algorithms, mainly genetic programming.View Profile
Professor Frank Wang: Professor of Future Computing
Future computing; unconventional computing; non-Turing architecture; cloud computing; big data; deep learning; memristor; neural networks; nature-inspired computing; green computing.View Profile
Professor Ian McLoughlin: Head of School (Medway)
Speech is the primary communications mechanism for humans, and is increasingly the way we interact with computers and mobile devices. In my research I deal with all aspects of speech, language and hearing, and ally this with powerful machine learning techniques that mimic how human brains acquire language and recognise sounds (machine hearing). My research team also works with speech-impaired patients to develop techniques that enable them to regain the power of speech in their daily lives.View Profile
Dr Matteo Migliavacca: Lecturer
Stream processing, database systems, parallel data processing, networked systems, cloud computing, distributed systems, big data.View Profile
Shoaib Jameel: Lecturer
Data science, signal processing, machine learning, security and statistics.View Profile
Dr Anna Jordanous: Lecturer
Computational creativity and its evaluation, music informatics, digital humanities, knowledge modelling, Semantic Web, and natural language processing.View Profile
Dr Palaniappan Ramaswamy: Reader, Admissions Officer (Medway)
Analysis of biomedical signals (such as EEG, PCG and ECG) for various applications: brain-computer interface, biometrics, electrophysiological analysis, cardiovascular disease diagnosis and stress management. Also, analysis of speech and image data for various engineering and computer science applications. Tools utilised: advanced signal processing and machine learning (such as neural networks and genetic algorithms).View Profile
The 2019/20 annual tuition fees for this programme are:
|Advanced Computer Science (Cloud Computing and Big Data) - MSc at Medway:|
|Advanced Computer Science (Cloud Computing and Big Data) with an Industrial Placement - MSc at Medway:|
For students continuing on this programme fees will increase year on year by no more than RPI + 3% in each academic year of study except where regulated.* If you are uncertain about your fee status please contact firstname.lastname@example.org
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