Data Science - BSc (Hons)
with a Foundation Year

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Data science combines powerful computing technology, sophisticated statistical methods, and expert subject knowledge to analyse and gain practical insights from huge amounts of data produced by modern societies.


Our specialist BSc Data Science programme combines the expertise of internationally-renowned statisticians and mathematicians from the School of Mathematics, Statistics and Actuarial Science and computer scientists and machine learners from the School of Computing to ensure that you develop the expertise and quantitative skills required for a successful future career in the field.

Our degree programme

The BSc Data Science with a Foundation year is studied over four years full time. The Foundation Year provides an opportunity for you to develop your mathematics and computing skills and start learning some university-level material, fully preparing you for university study before you progress onto Stage 1 of the BSc Data Science. Upon successful completion of the Foundation Year, you will have the choice of taking a placement year between stages 2 and 3 by transferring onto the BSc Data Science with a Year in Industry.

On this new programme you gain a systematic understanding of key aspects of knowledge associated with data science and the capability to deploy established approaches accurately. You learn to analyse and solve problems using a high level of skill in calculation and manipulation of the material in the following areas: data mining and modelling, artificial intelligence techniques/statistical machine learning and big data analytics.

You also learn how to apply key aspects of big data science and artificial intelligence/statistical machine learning in well-defined contexts. In addition, you plan and develop a project themed in a data science area such as business, environment, finance, medicine, pharmacy and public health.

Year in industry

If you want to gain paid industry experience as part of your degree programme, our Data Science with a Year in Industry programme may be for you. If you decide to take the Year in Industry, our Placements Team will support you in developing the skills and knowledge needed to successfully secure a placement through a specialist programme of workshops and events.

The School of Computing and the SMSAS have had rich experience in running industrial placement related BSc programmes with a wide range of links to industry, currently holding the top two largest placement student groups in the University.

Study resources

Facilities to support the study of Data Science include The Shed, the School of Computing's Makerspace. You have access to a range of professional mathematical, statistical and computing software such as:

  • R
  • Python
  • Maple
  • Minitab.

Extra activities

You join a thriving student culture, with students from all degree programmes and all degree stages participating in student activities and taking on active roles within the University. As a School of Mathematics, Statistics and Actuarial Science student you benefit from free membership of the Kent Maths Society and Invicta Actuarial Society.

You can also become a Student Rep and share the views of your fellow students to bring about changes. You could be employed as a Student Ambassador, earning money while you study by inspiring the next generation of mathematicians. Or join one of the society committees and organise socials and events for CEMS students.

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Entry requirements

The University will consider applications from students offering a wide range of qualifications. All applications are assessed on an individual basis but some of our typical requirements are listed below. Students offering qualifications not listed are welcome to contact our Admissions Team for further advice. Please also see our general entry requirements.

  • medal-empty

    A level

    CCD including Mathematics grade C (not Use of Mathematics). Either General Studies or Critical Thinking (but not both) can be accepted against the requirements. 

  • medal-empty 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. 

  • medal-empty BTEC Nationals

    BTEC Level 3 Extended Diploma (formerly BTEC National Diploma)  

  • medal-empty International Baccalaureate

    34 points overall or 13 points at HL with Mathematics 4 at HL?or Mathematics 6 at SL.

  • medal-empty International Foundation Programme


  • medal-empty T level

    The University will consider applicants holding T level qualifications in subjects closely aligned to the course.

International students

If you are an international student, visit our International Student website for further information about entry requirements for your country, including details of the International Foundation Programmes. Please note that international fee-paying students who require a Student visa cannot undertake a part-time programme due to visa restrictions.

Please note that meeting the typical offer/minimum requirement does not guarantee that you will receive an offer.

English Language Requirements

Please see our English language entry requirements web page.

Please note that if you do not meet our English language requirements, we offer a number of 'pre-sessional' courses in English for Academic Purposes. You attend these courses before starting your degree programme.


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Course structure

Duration: 4 years full-time

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. 

In stages 1 and 2 will you will study a number of core modules in statistics, mathematics, computer science and artificial intelligence, while in stage 3 you will have a choice from a range of modules in addition to core modules.


The 2023/24 annual tuition fees for this course are:

  • Home full-time £9,250
  • EU full-time £13,500
  • International full-time £18,000

For details of when and how to pay fees and charges, please see our Student Finance Guide.

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.

Additional costs

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


We have a range of subject-specific awards and scholarships for academic, sporting and musical achievement.

Search scholarships

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

The Kent Scholarship for Academic Excellence

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 A*AA over three A levels, or the equivalent qualifications (including BTEC and IB) as specified on our scholarships pages.

Teaching and assessment


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. 

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.

Contact hours

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.

Programme aims

The course aims to:

  • Attract and meet the needs of those contemplating a career as a data scientist. 
  • Equip students with the technical appreciation, skills and knowledge appropriate to graduates in Data Science. 
  • Develop students’ facilities of rigorous reasoning and precise expression. 
  • Develop students’ capabilities to formulate and solve problems, relevant to Data Science. 
  • Develop in students an appreciation of recent developments in Data Science, and of the links between the theory and practical application. 
  • Develop in students a logical approach to solving problems. 
  • Develop in students an enhanced capacity for independent thought and work. 
  • Ensure students are skilled in the use of relevant Data Science software. 
  • Provide students with opportunities to study advanced topics in Data Science, engage in research at some level, and develop communication and personal skills. 

Learning outcomes

Knowledge and understanding

You will gain a knowledge and understanding of:

  • Core mathematical principles of calculus, algebra, mathematical methods and linear algebra. 
  • The subjects of probability and inference. 
  • Information technology skills as relevant to Data Science. 
  • Methods and techniques appropriate to Computing and Statistics. 
  • The role of logical mathematical argument and deductive reasoning.
  • Practice, including problem identification, deploying established approaches accurately to analyse and solve problems and testing and evaluation.  
  • Software, including programming languages and practice, tools and packages, computer applications, structuring of data and information. 
  • The legal background, security and ethical issues involved in data science. 

Intellectual skills

  • Ability to demonstrate a reasonable understanding of the basic body of knowledge for Computing, Mathematics and Statistics used in data science.
  • Ability to demonstrate a reasonable level of skill in calculation and manipulation of mathematical and statistical material written within the course and some capability to solve problems formulated within it. 
  • Ability to apply a range of core concepts and principles in well-defined contexts relevant to Computing, Mathematics and Statistics used in data science. 
  • Ability to use logical argument. 
  • Ability to demonstrate skill in solving problems in Data Science by various appropriate methods. 
  • Ability in relevant computer skills and usage. 
  • Ability to work with relatively little guidance. 
  • Ability to present succinctly to a range of audiences rational and reasoned arguments. 

Subject-specific skills

You will gain these subject-specific skills:

  • Ability to demonstrate knowledge of key mathematical and statistical concepts and topics, both explicitly and by applying them to the solution of problems.
  • Ability to demonstrate skills in codification and storage of data and in pre-processing raw data for later retrieval and analysis.
  • Ability to demonstrate understanding of fundamental computational concepts and algorithmic thinking, including recursive, distributed and parallel possibilities; the role of these in devising artificial intelligence/machine learning algorithms and in statistical modelling as well as in delivering innovative solutions to applied problems. 
  • Ability to comprehend problems, abstract the essentials of problems and formulate them mathematically and in symbolic form in order to facilitate their analysis and solution.
  • Ability to use key aspects of statistics, artificial intelligence/machine learning and optimisation in a principled fashion to address the challenges of small and large data sets in well-defined contexts, showing judgement in the selection and application of tools and techniques.
  • Ability to use computational and more general IT facilities as an aid to mathematical and statistical processes.
  • Ability to present mathematical and statistical arguments and the conclusions from them with clarity and accuracy. 
  • Ability to critically evaluate and analyse complex problems, argument and evidence, including those with incomplete information, and devise appropriate computing solutions, within the constraints of a budget. 

Transferable skills

You gain the following transferable skills:

  • Problem-solving skills, relating to qualitative and quantitative information. 
  • Communication skills. 
  • Numeracy and computational skills. 
  • Information technology skills such as word-processing, internet communication, etc. 
  • Personal and interpersonal skills and management skills.  
  • Time-management and organisational skills, as evidenced by the ability to plan and implement efficient and effective modes of working. 
  • Study skills needed for continuing professional development. 

Independent rankings

Mathematics at Kent was ranked 19th for student satisfaction in The Complete University Guide 2023.


Graduate destinations

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

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.

Career-enhancing skills

You graduate with a solid grounding in the fundamentals of data 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.

Apply for Data Science with a Foundation Year - BSc (Hons)

If you are from the UK or Ireland, you must apply for this course through UCAS. If you are not from the UK or Ireland, you can apply through UCAS or directly on our website if you have never used UCAS and you do not intend to use UCAS in the future.

Find out more about how to apply

All applicants

International applicants

Contact us


United Kingdom/EU enquiries

Enquire online for full-time study

T: +44 (0)1227 768896


International student enquiries

Enquire online

T: +44 (0)1227 823254

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