Computer Science is an exciting and rapidly evolving subject that offers excellent employment prospects and well-paid careers. At Kent, we teach you the fundamentals of computer science as well as giving you the opportunity to specialise in an area of your choice.
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*.
Our programmes are taught by leading researchers who are experts in their fields. The wide-ranging expertise of our teaching staff means you have the chance to explore a large choice of subjects, from artificial intelligence and computer security to parallel systems and mobile computing.
This programme has full Chartered IT Professional (CITP) accreditation from BCS, The Chartered Institute for IT.
Our programme focuses on the technical aspects of computer science. You learn to code in several languages, starting with the Java programming language, which is widely used in industry across a range of applications including mobile devices.
Building on these programming skills, you learn the principles and techniques that underpin the algorithms and systems shaping our world today. These include artificial intelligence, computer security, network technology, software engineering, and human-computer interaction. You put these principles and techniques into practice to develop software in a variety of ways, from small-scale exercises to a major software project.
On our flexible programme, you take a broad range of compulsory modules in your first and second years. You then select from a variety of options in your final year of study, so it's ideal if you want to keep your options open.
We also offer modules that allow you to gain practical experience. On our Kent IT Consultancy option, you learn how to become an IT consultant, providing computing support to local businesses while earning credits towards your degree.
You can also gain experience in teaching with our Computing in the Classroom module. This gives you the opportunity to apply your knowledge in a school setting.
Kent student Dan talks about his course.
Over half our students choose to take a year in industry after the second year of the programme. This gives you work experience, a salary and the possibility of a job with the same company after graduation. You don’t have to make a decision before you enrol at Kent but certain conditions apply: for details, see see Computer Science with a Year in Industry.
You can also take Computer Science as a themed degree. For more details, see Computer Science (Artificial Intelligence), Computer Science (Networks). All of these programmes are also available with a year in industry.
Facilities to support the study of Computer Science include The Shed, the School of Computing's Makerspace, which houses:
Students also have exclusive access to a computer room and common room, and we run a peer-mentoring scheme.
Computer Science students often take part in TinkerSoc, a student-run 'tinkering' society which meets in 'The Shed', our collaborative workspace. TinkerSoc welcomes all students who like making things.
Whether a member of TinkerSoc or not, you can spend time in The Shed, making, exploring and sharing. In this informal environment you can build physical devices for your coursework, as well as develop your own interests and hobbies.
The School of Computing also hosts events that you are welcome to attend. These include our successful seminar programme where guest speakers from academia and industry discuss current developments in the field. We also host the BCS local branch events on campus.
Our programmes are informed by a stakeholder panel of industry experts who give feedback on the skills that employers require from a modern workforce.
Our successful year in industry programmes have allowed us to build up excellent relationships with leading companies such as BAE Systems, Citigroup and The Walt Disney Company.
We also have a dedicated Employability Coordinator who is the first point of contact for students and employers.
*The University of Kent's Statement of Findings can be found here.
There’s lots of space there, everything is well-equipped and you can always find somewhere quiet when you need to concentrate.
Jamie Howard - Computer Science with a Year in Industry
The University will consider applications from students offering a wide range of qualifications. Typical requirements are listed below. Students offering alternative qualifications should contact us for further advice.
Please note that meeting this typical offer/minimum requirement does not guarantee an offer being made.Please also see our general entry requirements.
If you’ve taken exams under the new GCSE grading system, please see our conversion table to convert your GCSE grades.
AAB-BBB
Mathematics grade 4/C
The University will not necessarily make conditional offers to all Access candidates but will continue to assess them on an individual basis.
If we make you an offer, you will need to obtain/pass the overall Access to Higher Education Diploma and may also be required to obtain a proportion of the total level 3 credits and/or credits in particular subjects at merit grade or above.
Distinction, Distinction, Distinction
34 points overall or 15 points at HL including Mathematics 5 at HL or SL, or Mathematics Studies 6 at SL
The University welcomes applications from international students. Our international recruitment team can guide you on entry requirements. See our International Student website for further information about entry requirements for your country.
However, please note that international fee-paying students cannot undertake a part-time programme due to visa restrictions.
If you need to increase your level of qualification ready for undergraduate study, we offer a number of International Foundation Programmes.
For more advice about applying to Kent, you can meet our staff at a range of international events.
Please see our English language entry requirements web page.
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. You attend these courses before starting your degree programme.
Duration: 3 years full-time
The course structure below gives a flavour of the modules and provides details of the content of this programme. This listing is based on the current curriculum and may change year to year in response to new curriculum developments and innovation.
All modules are compulsory.
This module provides an introduction to object-oriented software development. Software pervades many aspects of most professional fields and sciences, and an understanding of the development of software applications is useful as a basis for many disciplines. This module covers the development of simple software systems. Students will gain an understanding of the software development process, and learn to design and implement applications in a popular object-oriented programming language. Fundamentals of classes and objects are introduced and key features of class descriptions: constructors, methods and fields. Method implementation through assignment, selection control structures, iterative control structures and other statements is introduced. Collection objects are also covered and the availability of library classes as building blocks. Throughout the course, the quality of class design and the need for a professional approach to software development is emphasised and forms part of the assessment criteria.
Mathematical reasoning underpins many aspects of computer science and this module aims to provide the skills needed for other modules on the degree programme; we are not teaching mathematics for its own sake. Topics will include algebra, reasoning and proof, set theory, functions, statistics and computer arithmetic.
An introduction to databases and SQL, focussing on their use as a source for content for websites. Creating static content for websites using HTML(5) and controlling their appearance using CSS. Using PHP to integrate static and dynamic content for web sites. Securing dynamic websites. Using Javascript to improve interactivity and maintainability in web content.
This module follows from COMP3220 and aims to provide students with more understanding of the theory behind the formal underpinnings of computing. It will build upon the abstract reasoning skills introduced in COMP3220. Matrices, vectors, differential calculus, probability and logic will be introduced.
This module provides an introduction to human-computer interaction. Fundamental aspects of human physiology and psychology are introduced and key features of interaction and common interaction styles delineated. A variety of analysis and design methods are introduced (e.g. GOMS. heuristic evaluation, user-centred and contextual design techniques). Throughout the course, the quality of design and the need for a professional, integrated and user-centred approach to interface development is emphasised. Rapid and low-fidelity prototyping feature as one aspect of this.
This module equips students with an understanding of how modern cloud-based applications work. Topics covered may include:
• A high-level view of cloud computing: the economies of scale, security issues, ethical concerns, the typical high-level architecture of a cloud-based application, types of available services (e.g., parallelization, data storage).
• Cloud infrastructure: command line interface; containers and virtual machines; parallelization (e.g., MapReduce, distributed graph processing); data storage (e.g., distributed file systems, distributed databases, distributed shared in-memory data structures).
• Cloud concepts: high-level races, transactions and sequential equivalence; classical distributed algorithms (e.g., election, global snapshot, consensus, distributed mutual exclusion); scheduling, fault-tolerance and reliability in the context of a particular parallelization technology (e.g., MapReduce).
• Operating system support: network services (e.g., TCP/IP, routing, reliable communication), virtualization services (e.g., virtual memory, containers)
This module aims to strengthen the foundational programming-in-the-small abilities of students via a strong, practical, problem solving focus. Specific topics will include introductory algorithms, algorithm correctness, algorithm runtime, as well as big-O notation. Essential data structures and algorithmic programming skills will be covered, such as arrays, lists and trees, searching and sorting, recursion, and divide and conquer.
This module builds on the foundation of object-oriented design and implementation found in CO320 to provide both a broader and a deeper understanding of and facility with object-oriented program design and implementation. Reinforcement of foundational material is through its use in both understanding and working with a range of fundamental data structures and algorithms. More advanced features of object-orientation, such as interface inheritance, abstract classes, nested classes, functional abstractions and exceptions are covered. These allow an application-level view of design and implementation to be explored. Throughout the course, the quality of application design and the need for a professional approach to software development is emphasised.
All modules are compulsory.
The curriculum covers topics in algorithms and data structures. Among data structures, it covers advanced topics on trees, heaps, graphs, et cetera. It provides details of computational complexity notations like O(). It covers the correctness and runtime analysis of recursive algorithms using recurrences. These algorithms range from mathematical computations to sorting algorithms. These algorithms are put in the context of appropriate algorithmic paradigms like divide-and-conquer and dynamic programming. Finally, computational complexity classes and problem reductions are introduced along with the proof techniques for NP-hardness and NP-completeness.
This module covers the basic principles of machine learning and the kinds of problems that can be solved by such techniques. You learn about the philosophy of AI, how knowledge is represented and algorithms to search state spaces. The module also provides an introduction to both machine learning and biologically inspired computation.
This module provides an introduction to the theory and practice of database systems. It extends the study of information systems in Stage 1 by focusing on the design, implementation and use of database systems. Topics include database management systems architecture, data modelling and database design, query languages, recent developments and future prospects.
This module introduces students to the functional programming paradigm, using at least one modern functional programming language to put the core concepts into practice. The module will develop both the foundation and theory of this paradigm, as well as the practice and application of the paradigm to solve problems and build systems. The module will core topics, including:
• Functions as first-class language constructs and as a central organising principle;
• Higher-order functions and compositional programming;
• Basic semantics of functional languages;
• The role of types in programming;
• Algebraic data types and pattern matching;
• Recursion and recursive data types;
• Differences with imperative and object-oriented programming paradigms;
• Properties of programs, (e.g., purity, side-effect freedom, totality, and partiality).
• The lambda-calculus as a programming model and foundation.
• BNF grammars for representing context-free syntax, and its relation to ADTs and language manipulation.
• Testing and issues of building correct software.
The module will develop practical skills in programming and problem solving using functional programming. There will also be a chance to apply functional programming to help understand better concepts in logic and mathematics.
Later parts of the module will then consider concurrent programming in the context of functional programming, including concurrent programming models and primitives (e.g., message-passing concurrency), parallelism, synchronisation and communication, and properties of deadlock, communication-safety, and starvation.
This module aims to provide students with an understanding of the fundamental components (hardware and software) of a typical computer system, and how they collaborate to execute software programs. The module provides a compressive overview from the lowest level of abstractions in hardware to the highest level of abstractions of modern programming languages. For example, they will see logic circuits, machine language, programming language implementations, high-level languages, and applications. This material provides a general understanding of computers, and it will also prepare students to develop software considering the system perspective, e.g. cost of abstraction and performance implications.
Cyber security has always been an important aspect of computing systems but its importance has increased greatly in recent years. The curriculum covers areas where cyber security is of major importance, but have different security requirements and may be exposed to different threats and attacks. It also covers techniques and mechanisms used to secure computer systems and data to meet those requirements and protect them. The areas looked at include computer operating systems (and increasingly, distributed operating systems), distributed applications (such as electronic commerce over the Internet), embedded systems (ranging from smart cards to large industrial plant and telecommunications systems), and users. The techniques and mechanisms looked at include cryptography, authentication & authorisation, and access control. Furthermore, the curriculum integrates the legal, ethical, and professional perspectives, for instance, to address concerns about data security, privacy, and societal impact of computing systems.
The module studies team-based Agile software development in detail and places it in a wider software development context.
Topics covered include
• Concepts, principles, practice and philosophy of an Agile approach to software development, contrasting with more structured approaches.
• Collaboration: programmer collaboration, team values, customer involvement, project management, standards and reporting.
• Planning: release and sprint planning, risk assessment, user stories and resource estimating
• Development practices: incremental requirements, test-driven development, refactoring, scrum, code review, quality assurance, continuous integration.
• Tools: IDEs, version control, automated code quality evaluation, issue tracking.
• Ethics, Intellectual property, codes of conduct and professional responsibility.
Propositional & Predicate Logic, including proofs. Formal languages: finite automata, regular expressions, CFGs. Turing machines, decidability.
Building scaleable web sites using client-side and server-side frameworks (e.g. JQuery, CodeIgniter). Data transfer technologies, e.g. XML and JSON. Building highly interactive web sites using e.g. AJAX. Web services. Deploying applications and services to the web: servers, infrastructure services, and traffic and performance analysis. Web and application development for mobile devices.
You take either CO600 Project, CO620 Research Project or CO650 IT Consultancy Project, plus 90 credits from a list of optional modules.
This module is designed to provide students across the university with access to knowledge, skill development and training in the field of entrepreneurship with a special emphasis on developing a business plan in order to exploit identified opportunities. Hence, the module will be of value for students who aspire to establishing their own business and/or introducing innovation through new product, service, process, project or business development in an established organisation. The module complements students' final year projects in Computing, Law, Biosciences, Electronics, Multimedia, and Drama etc.
This module covers the basic principles of machine learning and the kinds of problems that can be solved by such techniques. You learn about the philosophy of AI, how knowledge is represented and algorithms to search state spaces. The module also provides an introduction to both machine learning and biologically inspired computation.
Students, working in small groups, undertake a project related to computer science and/or software engineering. The project may be self-proposed or may be selected from a list of project proposals. A project will involve the specification, design, implementation, documentation and demonstration of a technical artefact, demonstrating the ability to synthesise information, ideas and practices to provide a quality solution together with an evaluation of that solution.
As a research project, this module is normally aimed at students who are achieving at upper second class level and above, and who may be intending to undertake research following graduation. Each student undertakes a project related to computer science and/or software engineering. The project may be self-proposed or may be selected from a list of project proposals. A project will involve background study and working on an open-ended research problem.
A small number of introductory lectures are given at the start of the project.
The module starts with a comprehensive and detailed study of current computer networks and communications technologies. It includes: a review of network techniques, switching and multiple access; high speed local area networks; network protocols, including data link, network, transport and application layers. A selection of key topics are looked at in greater depth to reveal the state-of-the-art and issues (problems) that remain to be solved.
Security has always been an important aspect of computing systems but its importance has increased greatly in recent years. In this module you learn about areas where security is of major importance and the techniques used to secure them. The areas you look at include computer operating systems (and increasingly, distributed operating systems), distributed applications (such as electronic commerce over the Internet) and embedded systems (ranging from smart cards and pay-TV to large industrial plant and telecommunications systems).
In this module you learn what is meant by neural networks and how to explain the mathematical equations that underlie them. You also familiarise yourself with cognitive neural networks using state of the art simulation technology and apply these networks to the solution of problems. In addition, the module discusses examples of computation applied to neurobiology and cognitive psychology. The module also introduces artificial neural networks from the machine learning perspective. You will study the existing machine learning implementations of neural networks, and you will also engage in implementation of algorithms and procedures relevant to neural networks.
There is an increasing use of nature-inspired computational techniques in computer science. These include the use of biology as a source of inspiration for solving computational problems, such as developments in evolutionary algorithms and swarm intelligence. It is therefore proposed to allow students the opportunity to become exposed to these types of methods for use in their late careers.
The scope of the module is outlined below. Note that topics will not necessarily be delivered in this order:
Professional issues and professional organisations.
Data privacy legislation, and other UK laws relating to the professional use of computer systems.
Criminal law relating to networked computer use, including new Anti-Terrorism legislation; and their application
Intellectual Property Rights, including Copyright, Patent and Contract Law.
Health & Safety issues.
Computer-based Projects, including the vendor-client relationship and professional responsibilities.
Students will spend one half-day per week for ten weeks in a school with a nominated teacher. They will observe sessions taught by their designated teacher and possibly other teachers. Later they will act somewhat in the role of a teaching assistant, by helping individual pupils who are having difficulties or by working with small groups. They may take 'hotspots': brief sessions with the whole class where they explain a technical topic or talk about aspects of university life. They must keep a weekly log of their activities. Each student must also devise a special project in consultation with the teacher and with the module convener. They must then implement and evaluate the project.
Students taking this module will undertake two or (typically) more assignments for the Kent IT Clinic (KITC). Each assignment will be of one of three types: .
Work on one of KITC's contracts with an external client. To the extent that client-funded work allows, every student will be given at least one assignment of this type. Wherever practical, a student will be encouraged to participate in the negotiation and pricing of contracts, under the ultimate supervision of KITC management. For each assignment, the student may work on the assignment individually or as part of a group, as directed by KITC.
A contribution to the infrastructure of KITC itself. These assignments work in a similar way to external assignments, but with KITC as the client.
Formulating a costed proposal for the future development of KITC, and presenting reasoned argument in support of the proposal to KITC management, as a candidate for inclusion in KITC’s strategic plan for the following academic year. Every student will have at least one assignment of this type.
A study of techniques for interpreting and compiling programming languages, implementing them in a typed functional programming language (e.g., OCaml, Haskell). The module will outline a whole compiler from source to machine code, but will focus in depth on key algorithms and techniques. Possible in-depth topics include:
• writing interpreters,
• Hindley-Milner type inference,
• register allocation,
• garbage collection,
• abstract interpretation,
• static single assignment form.
The implemented language will be based on a simple imperative (e.g., Pascal-like) language with some extensions to address advanced topics in data layout (e.g., closures, objects, pattern matching). The course will be organized around a simple, but complete, example compiler that the student will have to understand and modify.
This module is aimed at introducing the principles of concurrency theory (1, 2, 3) and demonstrating how these can be applied to design and implement distributed applications (4). Advanced concepts of Web services will be studied and placed in the perspective of these principles (5, 6).
The following is an indicative list of topics:
• Message passing primitives for concurrency: synchronous versus asynchronous message passing, the actor model.
• Reasoning on processes: temporal logic, safety and liveness properties, bisimulation.
• Channel passing and mobility.
• Design and implementation of application–level protocols.
• Web services: from stateless services to distributed business processes (also known as service orchestrations).
• Transaction protocols on the Web: two-phase commit, long running transactions
This module will give students an overarching introduction to quantum information processing (QIP). At the end of the course the students will have a basic understanding of quantum computation, quantum communication, and quantum cryptography; as well as the implications to other fields such as computation, physics, and cybersecurity.
We will take a multi-disciplinary approach that will encourage and require students to engage in topics outside of their core discipline. The module will cover the most essential mathematical background required to understand QIP. This includes: linear algebra, basic elements of quantum theory (quantum states, evolution of closed quantum systems, Born's rule), and basic theory of computing. The module will introduce students to the following theoretical topics: quantum algorithms, quantum cryptography, quantum communication & information. The module will also address experimental quantum computation & cryptography.
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 data mining tool, and learn to evaluate the quality of discovered knowledge.
The module introduces fundamental techniques employed in image processing and pattern recognition providing an understanding of how practical pattern recognition systems may be developed able to address the inherent difficulties present in real world situations. The material is augmented with a study of biometric and security applications looking at the specific techniques employed to recognise biometric samples.
This module introduces the theory and practice of employing computers as the control and organisational centre of an electronic or mechanical system, and examines time critical systems. It also provides embedded systems design through practical work, including real-time operating systems and microcomputer programming.
The module will study some of the major works in the history of modern philosophy of cognitive science and artificial intelligence. An indicative list of topics is: The Turing test; the Chinese Room argument; the frame problem; connectionism; extended and embodied cognition; artificial consciousness. The approach will be philosophical and critical, and will involve the close reading of texts. Students will be expected to engage critically with the works being studied and to formulate and argue for their own views on the issues covered.
The 2020/21 annual tuition fees for this programme are:
For details of when and how to pay fees and charges, please see our Student Finance Guide.
Full-time tuition fees for Home and EU undergraduates are £9,250.
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.*
The University will assess your fee status as part of the application process. If you are uncertain about your fee status you may wish to seek advice from UKCISA before applying.
Find out more about accommodation and living costs, plus general additional costs that you may pay when studying at Kent.
Within the School of Computing are authors of widely used textbooks, a National Teaching Fellow and Association of Computer Machinery (ACM) Award-winning scientists. Programmes are taught by leading researchers who are experts in their fields.
Teaching is based on lectures, with practical classes and seminars, but we are also introducing more innovative ways of teaching, such as virtual learning environments and work-based tuition. Work includes group projects, case studies and computer simulations, with a large-scale project of your own choice in the final year.
Each stage comprises eight modules. Most modules run for a single 12-week term and have two lectures and one to two hours of classes, making 14 formal contact hours per week and eight hours of 'homework club' drop-in sessions each term.
We provide excellent support for you throughout your time at Kent. This includes access to web-based information systems, podcasts and web forums for students who can benefit from extra help. We use innovative teaching methodologies, including BlueJ and LEGO© Mindstorms for teaching Java programming.
Our staff have written internationally acclaimed textbooks for learning programming, which have been translated into eight languages and are used worldwide. A member of staff has received the SIGCSE Award for Outstanding Contribution to Computer Science Education. The award is made by ACM, the world's largest educational and scientific computing society.
Assessment is by a combination of coursework and end-of-year examination and details are shown in the module outlines on the web. Project modules are assessed wholly by coursework.
The marks from stage one do not go towards your final degree grade, but you must pass to continue to stage two.
Most stage two modules are assessed by coursework and end-of-year examination. Marks from stage two count towards your degree result.
Most stage three modules are assessed by a combination of coursework and end-of-year examination. Projects are assessed by your contribution to the final project, the final report, and oral presentation and viva examination. Marks from stage three count towards your degree result.
In stage three your project counts for 25% of the year's marks.
For a student studying full time, each academic year of the programme will comprise 1200 learning hours which include both direct contact hours and private study hours. The precise breakdown of hours will be subject dependent and will vary according to modules. Please refer to the individual module details under Course Structure.
Methods of assessment will vary according to subject specialism and individual modules. Please refer to the individual module details under Course Structure.
The programme aims to:
You gain knowledge and understanding of:
You develop intellectual skills in:
You gain subject-specific skills in:
You gain transferable skills in:
Computer Science at Kent scored 91.9 out of 100 in The Complete University Guide 2021.
For graduate prospects, Computer Science at Kent scored 92% in The Times Good University Guide 2020, 92% in The Guardian University Guide 2020 and 92 out of 100 in The Complete University Guide 2020.
Over 92% of Computer Science graduates who responded to the most recent national survey of graduate destinations were in professional work or further study within six months (DLHE, 2017).
Our graduates have gone on to work in:
Recent graduates have gone on to develop successful careers at leading companies such as:
The University has a friendly Careers and Employability Service, which can give you advice on how to:
The School has a dedicated Employability Coordinator who is a useful contact for all student employability queries.
You can gain commercial experience working as a student consultant within the Kent IT Consultancy. You can also gain teaching experience by taking the Computing in the Classroom module.
You graduate with a solid grounding in the fundamentals of computer science and a range of professional skills, including:
To help you appeal to employers, you also learn key transferable skills that are essential for all graduates. These include the ability to:
You can also gain extra skills by signing up for one of our Kent Extra activities, such as learning a language or volunteering.
Our Computer Science degree has full Chartered IT Professional (CITP) accreditation from the BCS, The Chartered Institute for IT.
This course page is for the 2020/21 academic year. Please visit the current online prospectus for a list of undergraduate courses we offer.
T: +44 (0)1227 823254
E: internationalstudent@kent.ac.uk
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