Modern societies produce huge amounts of data. However, this information is only useful if we can analyse it and gain practical insights. Data science combines powerful computing technology, sophisticated statistical methods, and expert subject knowledge to carry out this analysis. It is a field that has emerged over recent decades, and is now an exciting, fulfilling, and high-profile career choice, with positions available in many diverse fields. Our specialist **BSc Data Science** programme combines the expertise of internationally-renowned statisticians and mathematicians from the School of Mathematics, Statistics and Actuarial Science (SMSAS) 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. You will be encouraged to fulfil your potential whilst studying in our friendly and dynamic schools. You will graduate with capabilities including data science, machine learning and communication skills, as well as more specific knowledge skills in areas such as Python, SQL, Java and Hadoop. By the end of the programme you will have developed: 1. systematic understanding of key aspects of knowledge associated with data science and the capability to deploy established approaches accurately 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. 2. transferable skills in some or all of: presentations, information retrieval and internet research, report writing, information technology (IT) expertise and the use of statistical and computing software and practical and analytical skills such as software development skills, testing and assessment skills, experimental skills, data gathering and processing skills. You will also be able to: 1. apply key aspects of big data science and artificial intelligence/statistical machine learning in well-defined contexts, showing judgement in the selection and application of tools and techniques and of mathematics/statistics and computer technology. 2. plan and develop a project themed in one of data science areas in business, environment, finance, medicine, pharmacy, public health, among others. 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 (UCAS code: G191). 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 BSc Data Science with a Foundation Year(G192) is also available. 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. Superb student experience SMSAS and the School of Computing, within the Division of Computing, Engineering and Mathematical Sciences (CEMS), have 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 SMSAS student you benefit from free membership of the Kent Maths Society and Invicta Actuarial Society. You can 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. You will be encouraged to make the most of your time at university and will have access to support and guidance throughout your studies.

Modules are not listed for this Course.

Assessment Methods are not listed for this Course.

Professional Bodies are not listed for this Course.

26 January This is the deadline for applications to be completed and sent for this course. If the university or college still has places available you can apply after this date, but your application is not guaranteed to be considered.

Course code: G190

Institution code: K24

Campus Name: Main Site

Campus code:

The following entry points are available for this course:

Year 1

Entry Requirements for Advanced Entry are not listed for this Course.

Please click the following link to find out more about qualification requirements for this course

Minimum Further Information are not listed for this Course.

Test	Grade	AdditionalDetails

Applicants should have grade C or 4 in English Language GCSE or a suitable equivalent level qualification.

Please visit our website for further information:

https://www.kent.ac.uk/courses/undergraduate/how-to-apply/english-language-requirements.html

Student satisfaction : 84%

Employment after 15 months (Most common jobs): 56%

Go onto work and study: 85%

All fees for 2022/23 are to be confirmed. Please see the programme page at www.kent.ac.uk for further information on fees and funding options.

Recruitment and Admissions Office
Registry
Address3 are not listed for this Course.
Canterbury
CT2 7NZ