Computing

Computer Science (Artificial Intelligence) with a Year in Industry - BSc (Hons)

UCAS code G4GR

CLEARING 2018

Planning to start this September? We may still have full-time vacancies available for this course. View 2018 course details.
2019

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.

Overview

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*.

This programme has full Chartered IT Professional (CITP) accreditation from BCS, The Chartered Institute for IT.

Our degree programme

On this themed degree, the specific focus (here, Artificial Intelligence) is decided at the time of enrolment and named in your degree title. You can also study our general Computer Science degree, where a subject focus is decided during the course of your study.

Our programme focuses on the technical aspects of computer science. The first language you learn is Java, the standard programming language for many mobile devices and widely used in the industry. 

Other areas covered include software engineering, network technology and human-computer interaction. You learn how to develop software, program mobile devices and discover the underlying protocols on which the internet runs.

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, which gives you the opportunity to apply your knowledge in a school setting.

Year in industry

Your year in industry takes place between your second and final years. You gain invaluable work experience, earn a salary and there may be the possibility of a job with the same company after graduation. 

In previous years, students have worked in a range of large and small organisations including well-known names such as: 

  • IBM 
  • Intel
  • Disney
  • Morgan Stanley.

It is also possible to take this degree as a three-year programme, without a year in industry. For details, see Computer Science (Artificial Intelligence).

Study resources

Facilities to support the study of Computer Science include The Shed, the School of Computing's Makerspace, which houses:

  • 3D printers
  • laser-cutting facilities 
  • development equipment, including Oculus Rift and Raspberry Pi. 

Students also have exclusive access to a computer room and common room, and we run a peer-mentoring scheme.

Extra activities

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.

Professional network

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.

Independent rankings

For graduate prospects, Computer Science at Kent was ranked 7th in The Guardian University Guide 2018

Of Computer Science students who graduated from Kent in 2016, over 97% were in work or further study within six months (DLHE).

Teaching Excellence Framework

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.

TEF Gold logo

Course structure

The following modules are indicative of those offered on this programme. This listing is based on the current curriculum and may change year to year in response to new curriculum developments and innovation.  

On most programmes, you study a combination of compulsory and optional modules. You may also be able to take ‘wild’ modules from other programmes so you can customise your programme and explore other subjects that interest you.

Stage 1

Modules may include Credits

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 emphasized

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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.

Introduction: revision of basic mathematical and algebraic concepts and techniques.

Set theory: sets and elements, union, intersection, complement and difference, subsets, tuples, Cartesian product, counting, powersets, strings.

Functions: functions as rules, identity function, composition, inverses, injections, bijections, surjections.

Relations: equivalence relations, partial and total orderings. • Statistics: sample mean and variance, Normal and Poisson distributions.

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• An introduction to databases and SQL, focusing 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

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This module aims to provide students with an understanding of the fundamental behaviour and components (hardware and software) of a typical computer system, and how they collaborate to manage resources and provide services in scales from small embedded devices up to the global internet. The module has two strands: 'Computer Architecture' and 'Operating Systems and Networks,' which form around 35% and 65% of the material respectively. Both strands contain material which is of general interest to computer users; quite apart from their academic value, they will be useful to anyone using any modern computer system:

[a] Computer Architecture

- Data representation: Bits, bytes and words. Numeric and non-numeric data. Number representation.

- Computer architecture: Fundamental building blocks (e.g. registers). The fetch/execute cycle. Instruction sets and types.

- Data storage: Memory hierarchies and associated technologies. Physical and virtual memory.

- Sustainability. Energy consumption of computer systems: ways that this can be reduced and methods to estimate use.

[b] Operating Systems and Networks

- Operating systems principles. Abstraction. Processes and resources. Security. UNIX-style operating system fundamentals.

- Device interfaces: Handshaking, buffering, programmed and interrupt-driven i/o. Direct Memory Access.

- File Systems: Physical structure. File and directory organisation, structure and contents. Naming hierarchies and access. Backup.

- Fundamentals of networking and the Internet.

- Networks and protocols: LANs and WANs, layered protocol design. The TCP/IP protocol stack; theory and practice. Connection-oriented and connectionless communication. Unicast, multicast and broadcast. Naming and addressing. Application protocols; worked examples (e.g. SMTP, HTTP).

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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 computer arithmetic will be introduced.

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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.

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Design and communication, what makes for good written communication, how people get and process information, Personal Development Project, effective spoken communication, how to work successfully in a group, doing academic research, about preparing and giving a presentation, history of computing and the history of communication, the effects of technology, Health and safety issues with computing, the Business of Computing, Employment in IT, software development and software engineering, preparing for examinations, designing –for the web: web usability and web accessibility, the basics of IPR, relevant Laws applying to the use and development of computing, such as the Computer Misuse Act and the Data Protection Acts.

A range of social issues relating to computing, Representative content might include, Digital divide, Cyber bullying, Case studies

Sustainability: e.g. energy consumption, How to estimate? Substantial challenge, Rules of thumb (eg what to upgrade and when, when not to), Legal requirements of sustainability, Economic and ethical constraints.

How to make money in the IT industry: Consultancy, Selling software, Business planning, Pricing and estimating (case studies of what (not) to do from KITC).

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This module builds on the foundation of object-oriented design and implementation found in module CO320 Introduction to Object-Oriented Programming to provide a deeper understanding of and facility with object-oriented program design and implementation. More advanced features of object-orientation, such as inheritance, abstract classes, nested classes, graphical-user interfaces (GUIs), exceptions, input-output are covered. These allow an application-level view of design and implementation to be explored. Throughout the module the quality of application design and the need for a professional approach to software development is emphasized.

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Stage 2

Modules may include Credits

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.

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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.

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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.

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13. A synopsis of the curriculum Phase 1 – theory and tools:

• Introduction to basic design principles of systems;

• Software process - concepts & implementation:

o life cycle models (from Extreme Programming to CMM);

o definition, model, measurement, analysis, improvement of software and team (organization) process;

• Requirements elicitation, analysis and specification;

• Introduction to modelling principles (decomposition, abstraction, generalization, projection/views), and types of models (information, behavioural, structural, domain, and functional);

• Basic UML: uses cases, classes, sequence and collaboration diagrams;

• Risk & risk management in software:

o risk management: identification, analysis and prioritization

o software risks: project, process and product

o development methods for reducing risk

• Training in handling electrical components commonly encountered in computing systems and safe working practices.

• Software management: project estimation and metrics, software and process quality assurance, documentation and revision control;

• Introduction to project management;

• Software engineering tools: configuration control (e.g. SVN, GIT, etc.), project management (e.g Trac), integrated development environments (e.g. Eclipse, NetBeans, etc.), and a UML tool (e.g. IBM Rational Rose).

Phase 2 – Practice and techniques:

• Introduction to design patterns;

• More UML: state, activity diagrams, and OCL;

• Project management practice;

• Introduction to software testing: unit testing, coverage analysis, black box testing, integration testing, test cases based use cases, system and acceptance testing, and testing tools;

• Understanding of a number of business techniques including estimation of time, costs and evaluation of technical alternatives in the business context;

• Professional practice (reflective):

o codes of ethics and professional conduct;

o social, legal, historical, and professional issues and concerns;

• Design and implement a simple software system to meet a specified business goal.

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Propositional & Predicate Logic, including proofs

• Formal languages: finite automata, regular expressions, CFGs

• Turing machines, decidability

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Year in industry

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:

  • Accenture
  • BT
  • GSK
  • IBM
  • Kent Police
  • Microsoft
  • Morgan Stanley
  • The Walt Disney Company.

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.

Modules may include Credits

Stage 3

Modules may include Credits

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.

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This module enables students to take ideas from the natural sciences and use them as inspiration for new computational techniques. You examine developments in biological-inspired computation and their applications. There is also a practical element to the module; you implement one of the algorithms discussed in the lectures on the computers. Topics covered, include evolutionary computation and swarm intelligence.

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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 workallows, every student will be given at least one assignment of this type. Wherever practical, astudent will be encouraged to participate in the negotiation and pricing of contracts, under theultimate supervision of KITC management. For each assignment, the student may work on theassignment 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.

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The project gives you the opportunity to follow and develop your particular technical interests, undertake a larger and less tightly specified piece of work than you have before (at university), and develop the project organisation, implementation and documentation techniques which you have learnt in other modules. The technical and professional aspects of project courses are seen as particularly important by both employers (who will often bring them up in interviews) and by professional bodies.

The project may be self-proposed or may be selected from a list of project proposals. Typically, a project will involve the specification, design, implementation, documentation and demonstration of a technical artefact. The project is supervised by a member of the academic staff, who holds weekly meetings with the group, during which s/he will give general advice and will assess the progress of the group and the contributions by individual students.

Project deliverables are:

- a technical report, in the style of an academic paper, describing the scientific/technical outcome of the project;

- a well-indexed corpus of material that supports the achievements claimed.

In addition, each individual prepares a report outlining his/her contributions to each of the various aspects of the project. This report should not be a repeat of other material delivered as part of the project, but an assessment of the progress of the project and reflections on what the individual has learnt from undertaking it. In particular, it should include a description of the particular activities and outcomes that individual has contributed to the project, and of how the group worked together. This report will be discussed at a viva voce examination which should include a short presentation/demonstration of the project.

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The project gives you the opportunity to follow and develop your particular technical interests, undertake a larger and less tightly specified piece of work than you have before (at university), and develop the project organisation, implementation and documentation techniques which you have learnt in other modules. The technical and professional aspects of project courses are seen as particularly important by both employers (who will often bring them up in interviews) and by professional bodies.

The project may be self-proposed or may be selected from a list of project proposals. Typically, a project will involve the specification, design, implementation, documentation and demonstration of a technical artefact. The project is supervised by a member of the academic staff, who holds weekly meetings with the group, during which s/he will give general advice and will assess the progress of the group and the contributions by individual students.

Project deliverables are:

- a technical report, in the style of an academic paper, describing the scientific/technical outcome of the project;

- a well-indexed corpus of material that supports the achievements claimed.

In addition, each individual prepares a report outlining his/her contributions to each of the various aspects of the project. This report should not be a repeat of other material delivered as part of the project, but an assessment of the progress of the project and reflections on what the individual has learnt from undertaking it. In particular, it should include a description of the particular activities and outcomes that individual has contributed to the project, and of how the group worked together. This report will be discussed at a viva voce examination which should include a short presentation/demonstration of the project.

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The module aim is to give students an overview and understanding of key

theoretical, practical and philosophical research and issues around

computational creativity, and to give them practical experience in writing and

evaluating creative software.

The module will cover the following topics:

• Introduction to computational creativity

Examples of computational creativity software e.g. musical systems,

artistic systems, linguistic systems, proof generator systems,

furniture design systems

• Evaluation of computational creativity systems (both of the quality

and the creativity of systems)

• Philosophical issues concerning creativity in computers

• Comparison of computer creativity to human creativity

• Collaborative creativity between humans and computers

• Overview of recent research directions/results in computational

creativity

• Practical experience in writing creative software

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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.

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Lecture Syllabus

IMAGES AND IMAGE PROCESSING

Introduction to the module. Scope, philosophy and range of relevant applications. Vision as a physiological, psychological and computational process. Image representation, spatial and amplitude digitisation, resolution, colour in images, and computational implications. Array tessellation, connectivity, object representation, binarisation and thresholding. Image histograms and properties, image quality. Image enhancement processing and filtering. Histogram modification techniques and contrast enhancement. Image subtraction, simple motion detection, skeletonisation. Image segmentation, edge-based and region-based methods, multi-attribute segmentation, the Hough transform and its generalisation. Shape descriptors and feature measurement. Morphological operators for image processing. Principles of simple image coding and implications. Case studies.

ANALYSING IMAGES

Principles of image analysis and understanding. Representation of objects and scenes. The concept of formalised pattern recognition. Pattern descriptors and pattern classes, preprocessing and normalisation. Feature extraction and imager characterisation. Texture analysis as an example of object description – texture descriptors, analysis using co-occurrence matrices. Basic decision theory and the Bayesian classifier. Cost and risk, minimum risk and minimum error-rate classification, rejection margins and error-rate trade-off, canonical descriptions of classifier structure. Implementation considerations and approaches to estimation of class-conditional feature distributions. Minimum distance classifiers. Alternative classification strategies. Case studies.

SECURITY AND BIOMETRICS

Introduction to security issues. Alternative approaches to personal identification, access control and data security, and applications in industrial, media, commercial and other related scenarios. Fundamentals of biometrics, biometric modalities, user requirements and user acceptability, template construction. Physiological and behavioural features, static and dynamic analyses, error sources and performance measures. False acceptance and false rejection measures, equal error rate, ROC descriptions. Variability and stability of biometric data, template ageing and related issues in enrolment and deployment. Characterisation of typical common modalities: face recognition, fingerprint processing, iris recognition, and automatic signature verification, and their underlying technologies. Usability issues, the human interface, system integration. Testing and evaluation of biometric systems. Revocable biometrics. Applications of biometric systems. Case studies.

NEURAL NETWORK PROCESSING

The concept of neural networks as architectures for image analysis. Exploration of techniques for automated learning and generalisation with artificial neural networks. Fundamentals of neural network design, basic design philosophy and application of neural networks to practical problems. Example: perceptrons and the perceptron learning algorithm.

Coursework

EXAMPLES CLASSES

There will be 4 assessed examples classes, one for each lecture series.

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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.

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Computer graphics and animation are important for a variety of technical and artistic applications including web design, HCI and GUI development, games and simulations, digital photography and cinema, medical and scientific visualization, etc.

This module introduces the subject from the perspective of computing. You will learn about technologies and techniques for modeling, manipulating, capturing, displaying and storing 2D and 3D scenes, digital images, animations and video. You will also gain practical experience of 3D modelling and animation tools.

Digital Imaging and Video:

Human vision

Colour models

Images, video and 3D

Capture and display

Enhancement and conversion

Formats and compression (e.g. GIF, JPEG, MPEG)

Computer Graphics:

Graphics pipeline

3D object and scene modelling with polygon meshes

Transformations

Projection, clipping and visible surface determination

Illumination and shading

Ray tracing and photorealism

Computer Animation:

Key-frame animation

Warping and morphing

Articulated figures

Kinematics, dynamics and collision detection

Particle systems and flocking

Computer-generated human characters and video-realism

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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 Laws

Health & Safety issues.

Computer-based Projects, including the vendor-client relationship and professional responsibilities

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Students taking this module will undertake one 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.

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.

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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.

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Teaching and assessment

Teaching

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.

Overall workload

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.

Academic support

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.

Teaching staff

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

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.

Percentage of the course assessed by coursework

In stage three your project counts for 25% of the year's marks. 

Programme aims

The programme aims to:

  • provide a programme that will attract and meet the needs of both those contemplating a career in computing and those motivated primarily by an intellectual interest in computer science
  • be compatible with widening participation in higher education by offering a wide variety of entry routes
  • provide a sound knowledge and systematic understanding of the principles of computer science
  • provide computing skills that will be of lasting value in a field that is constantly changing 
  • offer a range of options to enable students to match their interests and study some selected areas of computing in more depth
  • provide teaching which is informed by current research and scholarship and which requires students to engage with aspects of work at the frontiers of knowledge
  • develop general critical, analytical and problem-solving skills that can be applied in a wide range of different computing and non-computing settings.
  • provide knowledge of key areas in artificial intelligence.

Learning outcomes

Knowledge and understanding

You gain knowledge and understanding of:

  • hardware: the major functional components of a computer system
  • software: programming languages and practice; tools and packages; computer applications; structuring of data and information
  • communication and interaction: basic computer communication network concepts; communication between computers and people; the control and operation of computers
  • practice: problem identification and analysis; design development, testing and evaluation
  • theory: algorithm design and analysis; formal methods and description; modelling
  • the philosophical and psychological principles of knowledge and cognition
  • machine intelligence: systems, algorithms and applications
  • aspects of the core subject areas from the perspective of a commercial or industrial organisation.

Intellectual skills

You gain intellectual skills in:

  • modelling: knowledge and understanding in the modelling and design of computer-based systems in a way that demonstrates comprehension of the trade-off involved in design choices
  • reflection and communication: presenting succinctly to a range of audiences rational and reasoned arguments
  • requirements: identifying and analysing criteria and specifications appropriate to specific problems and planning strategies for their solution
  • criteria evaluation and testing: analysing the extent to which a computer-based system meets the criteria defined for its current use and future development
  • methods and tools: deploying appropriate theory, practices, and tools for the specification, design, implementation, and evaluation of computer-based systems
  • professional responsibility: recognising and being guided by the professional, economic, social, environmental, moral and ethical issues involved in the sustainable exploitation of computer technology
  • computational thinking: demonstrating a basic analytical ability and its relevance to everyday life
  • apply some of the intellectual skills specified for the programme from the perspective of a commercial or industrial organisation. 

Subject-specific skills

You gain subject-specific skills in:

  • design and implementation: specifying, designing, and implementing computer-based systems
  • evaluation: evaluating systems in terms of general quality attributes and possible trade-offs presented within the given problem
  • information management: applying the principles of effective information management, information organisation, and information retrieval skills to information of various kinds, including text, images, sound, and video
  • tools: deploying effectively the tools used for the construction and documentation of software, with particular emphasis on understanding the whole process involved in using computers to solve practical problems
  • operation: operating computing equipment and software systems effectively
  • identifying and developing solutions for computational problems requiring machine intelligence
  • apply some of the subject-specific skills specified for the programme from the perspective of a commercial or industrial organisation.

Transferable skills

You gain transferable skills in:

  • teamwork: being able to work effectively as a member of a development team
  • communication: making succinct presentations to a range of audiences about technical problems and their solutions
  • IT: effective use of general IT facilities; information retrieval skills
  • numeracy and literacy: understanding and explaining the quantitative and qualitative dimensions of a problem.
  • self management: managing one’s own learning and development, including time management and organisational skills
  • professional development: appreciating the need for continuing professional development in recognition of the need for lifelong learning.

Careers

Graduate destinations

Graduates who have both IT knowledge and business skills can expect excellent career prospects. Our graduates have gone on to work in:

  • software engineering
  • mobile applications development
  • systems analysis
  • consultancy
  • networking
  • web design and e-commerce
  • finance and insurance
  • commerce
  • engineering
  • education
  • government
  • healthcare. 

Recent graduates have gone on to develop successful careers at leading companies such as:

  • BAE Systems
  • Cisco 
  • IBM
  • The Walt Disney Company
  • Citigroup 
  • BT.

Help finding a job

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:

  • 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.

Work experience

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.

Career-enhancing skills

You graduate with a solid grounding in the fundamentals of computer science and a range of professional skills, including:

  • programming
  • modelling
  • design.

To help you appeal to employers, you also learn key transferable skills that are essential for all graduates. These include the ability to:

  • think critically
  • communicate your ideas and opinions
  • analyse situations and troubleshoot problems
  • work independently or as part of a team.

You can also gain extra skills by signing up for one of our Kent Extra activities, such as learning a language or volunteering.

Professional recognition

Our Computer Science degree has full Chartered IT Professional (CITP) accreditation from BCS, The Chartered Institute for IT.

Independent rankings

Of Computer Science students who graduated from Kent in 2016, over 97% were in work or further study within six months (DLHE).

According to Which? University (2017), the average starting salary for graduates of this degree is ‘high’ at £27,000.

Entry requirements

Home/EU students

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. 

It is not possible to offer places to all students who meet this typical offer/minimum requirement.

New GCSE grades

If you’ve taken exams under the new GCSE grading system, please see our conversion table to convert your GCSE grades.

Qualification Typical offer/minimum requirement
A level

AAB

GCSE

Mathematics grade C

Access to HE Diploma

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.

BTEC Level 3 Extended Diploma (formerly BTEC National Diploma)

Distinction, Distinction, Distinction

International Baccalaureate

34 points overall or 16 points at HL including Mathematics 5 at HL or SL, or Mathematics Studies 6 at SL

International students

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.

If you need to increase your level of qualification ready for undergraduate study, we offer a number of International Foundation Programmes.

Meet our staff in your country

For more advice about applying to Kent, you can meet our staff at a range of international events.

English Language Requirements

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. 

General entry requirements

Please also see our general entry requirements.

Fees

The 2019/20 tuition fees have not yet been set. As a guide only, the 2018/19 annual tuition fees for this programme are:

UK/EU Overseas
Full-time £9250 £18400

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.* 

Your fee status

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.

Fees for Year in Industry

For 2018/19 entrants, the standard year in industry fee for home, EU and international students is £1,385

Fees for Year Abroad

UK, EU and international students on an approved year abroad for the full 2018/19 academic year pay £1,385 for that year. 

Students studying abroad for less than one academic year will pay full fees according to their fee status. 

General additional costs

Find out more about accommodation and living costs, plus general additional costs that you may pay when studying at Kent.

Funding

University funding

Kent offers generous financial support schemes to assist eligible undergraduate students during their studies. See our funding page for more details. 

Government funding

You may be eligible for government finance to help pay for the costs of studying. See the Government's student finance website.

Scholarships

General scholarships

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.

The Kent Scholarship for Academic Excellence

At Kent we recognise, encourage and reward excellence. We have created the Kent Scholarship for Academic Excellence. 

For 2018/19 entry, 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.

The Key Information Set (KIS) data is compiled by UNISTATS and draws from a variety of sources which includes the National Student Survey and the Higher Education Statistical Agency. The data for assessment and contact hours is compiled from the most populous modules (to the total of 120 credits for an academic session) for this particular degree programme. 

Depending on module selection, there may be some variation between the KIS data and an individual's experience. For further information on how the KIS data is compiled please see the UNISTATS website.

If you have any queries about a particular programme, please contact information@kent.ac.uk.