Our degree teaches you the fundamentals of computer science as well as a broad range of Artificial Intelligence (AI) techniques, including neural networks and evolutionary algorithms, which draw on philosophy and psychology. You have the opportunity to exercise your skills on a paid industry placement, which greatly enhances your employment prospects and allows you to put your academic learning into a real-world context.
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.
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: 4 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.
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.
This module follows from CO322 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 CO322. 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.
The curriculum covers topics in algorithms and data structures, such as sorting, searching, and graph algorithms. It addresses how to program such algorithms, as well as how to test them, reason about their correctness and analyse their efficiency.
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 will introduce students to fundamental concepts of functional and concurrent programming, using a suitable language (e.g. Erlang) as a vehicle to put these concepts into practice. The first part of the module will cover basic ideas in functional programming, such as expressions, types, values, lists, pattern-matching and recursion, together with the specific language concurrency model, including process creation, message sending and receiving. Good concurrent design practices will be considered, based on networks of communicating processes (e.g. Actor and CSP models), and avoiding problems such as deadlock, livelock and starvation. The later part of the module will cover more advanced topics (higher-order functions) and look at alternative concurrency models (e.g. synchronous, channel-based, join-based and shared-memory) and their relationship to the model described in the first part of the module. Alongside this, consideration will be given to the relevance and applicability of functional and concurrent programming for use in real applications.
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 and the techniques used to secure computer systems. The areas looked 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 to large industrial plant and telecommunications systems). 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.
Building scaleable web sites using client-side and 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.
Propositional & Predicate Logic, including proofs. Formal languages: finite automata, regular expressions, CFGs. Turing machines, decidability.
You spend a year working in an industrial or commercial environment between Stages 2 and 3. Our students go to a wide range of companies including:
They have also been to overseas employers in locations including Amsterdam, Hong Kong and the US.
The year in industry forms an integral part of your degree and constitutes 10% of your final grade. Assessment comprises an employer evaluation, a reflective report and a logbook/portfolio.
Although it is your responsibility to find a suitable placement, the School of Computing’s dedicated Placement Team will help to identify suitable opportunities, assist with your application and prepare you for interviews.
To automatically progress onto the year in industry, you must pass Stage 2 at the first attempt. If you fail, you must pass the first resit opportunity in the August of the same year. Students who do not obtain a work placement will have their registration changed to the equivalent three-year programme without a year in industry.
Students spend a year (minimum 44 weeks) working in an industrial or commercial setting, applying and enhancing the skills and techniques they have developed and studied in the earlier stages of their degree programme. The work they do is entirely under the direction of their industrial supervisor, but support is provided via a dedicated Placement Support Officer with the School. This support includes ensuring that the work they are being expected to do is such that they can meet the learning outcomes of the module.
Students spend a year (minimum 44 weeks) working in an industrial or commercial setting, applying and enhancing the skills and techniques they have developed and studied in the earlier stages of their degree programme.
The report required for this module should provide evidence of the subject specific and generic learning outcomes, and of reflection by the student on them as an independent learner.
You take all compulsory modules and either CO600 Project, CO620 Research Project or CO650 IT Consultancy Project, plus 60 credits from a list of optional modules.
In this module you learn what is meant by neural networks and how to explain the mathematical equations that underlie them. You also build 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.
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.
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.
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 and Internet security protocols, including data link, network, transport and application layers; network attacks and defence mechanisms including encryption and tunnelling. 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.
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 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 shows students what trade-offs are involved in designing a programming language, and how those trade-offs ultimately influence programmer productivity. The module starts with a quick, example-based introduction to the basics of programming languages. It then continues with a series of problems that are each solved in several programming languages. After each problem, we stop and reflect on which language features help and which hinder. Finally, towards the end of the module, several of the language features previously identified are discussed in a more general setting. Indicative examples are:
• Problem solving, in multiple languages. The problems will involve concepts such as parsing, evaluation, trees, graphs, memoization, randomization, big data algorithms, reactive user interfaces.
• Language features: pattern matching, first order functions, polymorphism, effects, exceptions, types, algebraic data types, modules, objects, classes.
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.
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.
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.
Full-time tuition fees for Home and EU undergraduates are £1,385.
Full-time tuition fees for Home and EU undergraduates are £1,385.
Students studying abroad for less than one academic year will pay full fees according to their fee status.
Kent offers generous financial support schemes to assist eligible undergraduate students during their studies. See our funding page for more details.
You may be eligible for government finance to help pay for the costs of studying. See the Government's student finance website.
Scholarships are available for excellence in academic performance, sport and music and are awarded on merit. For further information on the range of awards available and to make an application see our scholarships website.
At Kent we recognise, encourage and reward excellence. We have created the Kent Scholarship for Academic Excellence.
The scholarship will be awarded to any applicant who achieves a minimum of AAA over three A levels, or the equivalent qualifications (including BTEC and IB) as specified on our scholarships pages.
The scholarship is also extended to those who achieve AAB at A level (or specified equivalents) where one of the subjects is either mathematics or a modern foreign language. Please review the eligibility criteria.
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. Each module has 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 gain intellectual skills in:
You gain subject-specific skills in:
You gain transferable skills in:
All University of Kent courses are regulated by the Office for Students.
Based on the evidence available, the TEF Panel judged that the University of Kent delivers consistently outstanding teaching, learning and outcomes for its students. It is of the highest quality found in the UK.
Please see the University of Kent's Statement of Findings for more information.
Computer Science at Kent scored 91.9 out of 100 in The Complete University Guide 2020.
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).
Graduates who have both IT knowledge and business skills can expect excellent career prospects. Our graduates have gone on to work in:
Recent graduates have gone on to develop successful careers at leading companies such as:
Employers are always keen to employ graduates with experience of the workplace, so your year in industry gives you a real advantage when it comes to starting your career.
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 BCS, The Chartered Institute for IT.
Full-time applicants (including international applicants) should apply through the Universities and Colleges Admissions Service (UCAS) system. If you need help or advice on your application, you should speak with your careers adviser or contact UCAS Customer Contact Centre.
The institution code number for the University of Kent is K24, and the code name is KENT.
See the UCAS website for an outline of the UCAS process and application deadlines.
If you are applying for courses based at Medway, you should add the campus code K in Section 3(d).
Discover Uni is designed to support prospective students in deciding whether, where and what to study. The site replaces Unistats from September 2019.
Discover Uni is jointly owned by the Office for Students, the Department for the Economy Northern Ireland, the Higher Education Funding Council for Wales and the Scottish Funding Council.
Find out more about the Unistats dataset on the Higher Education Statistics Agency website.