Our specialist BSc Data Science with a Year in Industry 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
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
Your year in industry takes place between your second and final year, giving you invaluable work experience. You earn a salary and there may be the possibility of a job with the same company after graduation.
Our students go to a wide range of companies including:
AccentureCGIIBMLloydsBank of England
You have the option to take this programme as a three-year degree, without the year in industry. For details, see Data Science.
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 and statistical software such as:
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 students in the Division of Computing, Engineering and Mathematical Sciences.Teaching
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.
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.
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.
You will gain the ability:
- to demonstrate a reasonable understanding of the basic body of knowledge for Computing, Mathematics and Statistics used in data science
- to demonstrate a reasonable level of skill in calculation and manipulation of mathematical and statistical material written within the programme and some capability to solve problems formulated within it
- to apply a range of core concepts and principles in well-defined contexts relevant to Computing, Mathematics and Statistics used in data science
- to use logical argument
- to demonstrate skill in solving problems in Data Science by various appropriate methods
- in relevant computer skills and usage
- to work with relatively little guidance
- to present succinctly to a range of audiences rational and reasoned arguments.
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.
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.
The programme 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.