The world is full of data, from global banks to Formula 1 teams, supermarkets and the United Nations. Data scientists ask and answer questions like what happened, why it happened, what will happen, and what can be done with the results. Develop the technical, practical and transferrable skills that you need to be a successful data scientist.
Data scientists use principles and practices from the fields of mathematics, statistics, artificial intelligence, and computer engineering, to analyse and generate meaning from data. At Kent, you're taught how to apply cutting-edge machine learning and deep learning methods, and how to make sense of the text data that is all around us.
Taught by experts in the field, you'll use real-world data to learn the technical, practical and transferrable skills needed to be a successful data scientist. You don't need a background in the subject as we start with the foundations of data science theory.
Artificial intelligence and machine learning innovations have made data processing faster and more efficient. Industry demand has created job positions in organisations around the world within the field of data science. Due to the skillset and expertise required, this looks likely to continue over the coming decades. Add an Industrial Placement to further enhance your employability.
The School has a strong reputation for world-class research and a well-established system of support and training with a high level of flexibility, and frequent contact between staff and research students. Postgraduate students develop analytical, communication and research skills. Developing computational skills and applying them to mathematical problems forms a significant part of the postgraduate training in the School, setting you up for a great career.
A 2:2, 2:1 or First Class degree.
All applicants are considered on an individual basis and additional qualifications, professional qualifications and relevant experience may also be taken into account when considering applications.
Please see our International Student website for entry requirements by country and other relevant information. Due to visa restrictions, students who require a student visa to study cannot study part-time unless undertaking a distance or blended-learning programme with no on-campus provision.
This course requires a Good level of English language, equivalent to B2 on CEFR.
Details on how to meet this requirement can be found on our English Language requirements webpage.
Examples:
IELTS 6.0 with a minimum of 5.5 in each component
PTE Academic 63 with a minimum of 59 in each sub-test
A degree from a UK university
A degree from a Majority English Speaking Country
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 through Kent International Pathways.
The following modules are indicative of those offered on this programme. This list is based on the current curriculum and may change year to year in response to new curriculum developments and innovation. Most programmes will require you to study a combination of compulsory and optional modules. You may also have the option to take modules from
other programmes so that you may customise your programme and explore other subject areas that interest you.
You start by gaining solid foundations in data science theory, learning how to model data at the same time as you develop important consultancy skills, including how to present your findings effectively to a client. You’ll be taught how to apply cutting-edge machine learning and deep learning methods, and how to make sense of the text data that is all around us. At the end of your course, you’ll undertake a project that brings together all your knowledge and skills, allowing you to complete a substantial piece of work in a subject of interest to you.
Duration: 2 years full-time
Placements last for 12 months, commencing in June/July of the Summer Term. Placements may be undertaken in the UK or overseas.
The University does not guarantee every student will find a placement. Those who do not secure a placement will be transferred to the MSc programme without a placement.
The placement consists of two modules: Industrial Placement Experience and Industrial Placement Report. The Experience module is assessed as pass/fail only and the Report module is graded on a categorical scale.
Assessments includes extensive analyses of complex real-world data. There will be unseen written examinations but most of the credit is based on coursework, including an independent project and report supported by an academic supervisor. Assessments will involve working with messy data where analyses need to be presented to 'clients', group work on coding projects, and development of data visualisation tools that could be used by a particular organisation. There will be exposure to assessments that are relatively low stakes, such as project plans and presentations. The technology to be used to undertake assessment will be standard: any computer with a modern specification will be appropriate.
The placement consists of two modules: Industrial Placement Experience and Industrial Placement Report. The Industrial Placement lasts 12 months. The Experience module is assessed as pass/fail only and the Report module is graded on a categorical scale.
Any student who does not complete both the Industrial Placement Experience module and the Industrial Placement Report module will be transferred to the equivalent non-Year in Industry programme, and the Year in Industry will not be taken into account for the purposes of calculating the award.
The course aims to:
On completion of the course students will be able to:
On completion of the course students will be able to:
On completion of the course students will be able to:
On completion of the course students will be able to:
Kent’s Computing Service central facility runs Windows. Within the School, postgraduate students can use a range of UNIX servers and workstations. Packages available include R, MATLAB, SPSS, STAN and Python.
Staff publish regularly and widely in journals, conference proceedings and books. Among others, they have recently contributed to: Annals of Statistics; Biometrics; Biometrika; Journal of Royal Society, Series B; Statistics and Computing. Details of recently published books can be found within our staff research interests.
All students registered for a taught Master's programme are eligible to apply for a place on our Global Skills Award Programme. The programme is designed to broaden your understanding of global issues and current affairs as well as to develop personal skills which will enhance your employability.
There has been research in the area of statistical ecology at Kent for many years. We are part of the National Centre for Statistical Ecology (NCSE), which was established in 2005.
The research conducted in this area at Kent is mainly on Bayesian variable selection, Bayesian model fitting, Bayesian nonparametric methods, Markov chain Monte Carlo with applications.
Research is focused on statistical modelling and inference in biology and genetics with applications in complex disease studies. Over the past few decades, large amounts of complex data have been produced by high through-put biotechnologies. The grand challenges offered to statisticians include developing scalable statistical methods for extracting useful information from the data, modelling biological systems with the data, and fostering innovation in global health research.
This theme encompasses both theory and applications. Theory is involved with supervised and unsupervised learning, matrix factorisation, modelling of high-dimensional time series, differential privacy, deep learning and networks, shape analysis and statistics on manifolds, and neuroimaging. Applications in biology, industry, medicine and psychiatry. Often new computational methods are the key to analysing complex big data problems.
In order to describe the data, it is common in statistics to assume a specific probability model. Unfortunately, in many practical applications (for instance in economics, population genetics and social networks) it is not possible to identify a specific structure for the data. Nonparametric methods provide statistical tools for addressing inference in these situations.
At Kent there is particular interest in the use of nonparametric methods including quantile regression and Bayesian nonparametric approaches. Application areas include modelling of the business cycle and capacity utilisation, calculating sovereign credit ratings, modelling of stock return data, and predicting inflation.
Full details of staff research interests can be found on the School's website.
You will be a trained data scientist, equipped to work in many fields. Organisations with data will require your skills: you might work for a national government, an insurance company, as an archaeologist or for a football club or cricket franchise. Alternatively, perhaps you see yourself as a future entrepreneur, using what you’ve learnt about data to develop your own business. To help you decide, you’ll be able to attend talks from professionals who work with data and to attend networking events with employers.
The 2024/25 annual tuition fees for this course are:
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.* If you are uncertain about your fee status please contact information@kent.ac.uk.
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.
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.*
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.
Find out more about general additional costs that you may pay when studying at Kent.
Search our scholarships finder for possible funding opportunities. You may find it helpful to look at both:
We have a range of subject-specific awards and scholarships for academic, sporting and musical achievement.
Next steps
Learn more about the application process or begin your application by clicking on a link below.
You will be able to choose your preferred year of entry once you have started your application. You can also save and return to your application at any time.
Supporting your success
Kent ranked top 50 in The Complete University Guide 2024.
Fees and funding
Kent has risen 11 places in THE’s REF 2021 ranking, confirming us as a leading research university.
Accommodation
