Data Science
University of Kent
UCAS Code: G190 | Bachelor of Science (with Honours) - BSc (Hons)
University of Kent
UCAS Code: G190 | Bachelor of Science (with Honours) - BSc (Hons)
Entry requirements
A level
The University welcomes applications from Access to Higher Education Diploma candidates for consideration. A typical offer may require you to obtain a proportion of Level 3 credits in relevant subjects at merit grade or above.
GCSE/National 4/National 5
Applicants should have grade B or 6 in Mathematics GCSE or a suitable equivalent level qualification.
International Baccalaureate Diploma Programme
30 points in the IB Diploma or 120 UCAS tariff points
Pearson BTEC Level 3 National Extended Diploma (first teaching from September 2016)
Scottish Higher qualifications are considered on an individual basis
T Level
UCAS Tariff
About this course
**Data Science**
Data science combines powerful computing technology, sophisticated statistical methods, and expert subject knowledge to analyse and gain practical insights from the huge amounts of data produced by modern societies. This new course combines the expertise of internationally renowned statisticians and mathematicians, computer scientists and machine learners to ensure that you develop the expertise and quantitative skills required for a successful future career in the field.
You'll 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.
**Your Future**
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.
An industrial placement can greatly enhance your studies and have a dramatic impact on your graduate choices.
**Location**
Our city, your time.
It has never been a better time to study in Canterbury. Our high student population creates a vibrant, diverse and student-friendly atmosphere.
We are a hub of exciting new ideas emerging from a stunning historic city - join us and get involved!
Modules
The following modules are what students typically study, but this may change year to year in response to new developments and innovations.
Year 1 compulsory modules currently include the following: Mathematics for Data Science; Programming I; Programming II; Internet Technologies; Essential Principles of Probability and Statistics; Applications and Practice with R and Python.
Year 2 compulsory modules currently include the following: Algorithms; Database Systems; Predictive and Explanatory Modelling in Context; Optimisation for Data Analysis; Preparing for Professional Practice; Fundamentals of AI.
Year 3 compulsory modules currently include the following: Natural Computation; Machine Learning and Deep Learning; Bayesian Machine Learning; Data Science Project. Optional modules may include the following: Data Mining and Knowledge Discovery; Natural Language Processing.
For more detailed information about these modules, please visit our website.
Extra funding
Kent offers generous financial support schemes to assist eligible undergraduate students during their studies. See our funding page for more details - https://www.kent.ac.uk/courses/undergraduate/fees-and-funding
The Uni
Canterbury campus
School of Mathematics, Statistics and Actuarial Science
What students say
We've crunched the numbers to see if the overall teaching satisfaction score here is high, medium or low compared to students studying this subject(s) at other universities.
How do students rate their degree experience?
The stats below relate to the general subject area/s at this university, not this specific course. We show this where there isn’t enough data about the course, or where this is the most detailed info available to us.
Computer science
Teaching and learning
Assessment and feedback
Resources and organisation
Student voice
Who studies this subject and how do they get on?
Most popular A-Levels studied (and grade achieved)
Mathematics
Teaching and learning
Assessment and feedback
Resources and organisation
Student voice
Who studies this subject and how do they get on?
Most popular A-Levels studied (and grade achieved)
After graduation
The stats in this section relate to the general subject area/s at this university – not this specific course. We show this where there isn't enough data about the course, or where this is the most detailed info available to us.
Computer science
What are graduates doing after six months?
This is what graduates told us they were doing (and earning), shortly after completing their course. We've crunched the numbers to show you if these immediate prospects are high, medium or low, compared to those studying this subject/s at other universities.
Top job areas of graduates
This is a newly-classified subject area for this kind of data, so we don’t currently have very much information to display or analyse yet. The subject is linked to important and growing computing industries, and over time we can expect more students to study them — there could be opportunities that open up for graduates in these subjects as the economy develops over the next few years.
Mathematics
What are graduates doing after six months?
This is what graduates told us they were doing (and earning), shortly after completing their course. We've crunched the numbers to show you if these immediate prospects are high, medium or low, compared to those studying this subject/s at other universities.
Top job areas of graduates
Want to feel needed? This is one of the most flexible degrees of all and with so much of modern work being based on data, there are options everywhere for maths graduates. With all that training in handling figures, it's hardly surprising that a lot of maths graduates go into well-paid jobs in the IT or finance industries, and last year, a maths graduate in London could expect a very respectable average starting salary of £27k. And we're always short of teachers in maths, so that is an excellent option for anyone wanting to help the next generation. And if you want a research job, you'll want a doctorate — and a really good maths doctorate will get you all sorts of interest from academia and finance — and might secure some of the highest salaries going for new leavers from university.
What about your long term prospects?
Looking further ahead, below is a rough guide for what graduates went on to earn.
Computer science
The graph shows median earnings of graduates who achieved a degree in this subject area one, three and five years after graduating from here.
£29k
£37k
£46k
Note: this data only looks at employees (and not those who are self-employed or also studying) and covers a broad sample of graduates and the various paths they've taken, which might not always be a direct result of their degree.
Mathematics
The graph shows median earnings of graduates who achieved a degree in this subject area one, three and five years after graduating from here.
£25k
£31k
£37k
Note: this data only looks at employees (and not those who are self-employed or also studying) and covers a broad sample of graduates and the various paths they've taken, which might not always be a direct result of their degree.
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Higher entry requirements
Lower entry requirements
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Teaching Excellence Framework (TEF):
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This information comes from the National Student Survey, an annual student survey of final-year students. You can use this to see how satisfied students studying this subject area at this university, are (not the individual course).
This is the percentage of final-year students at this university who were "definitely" or "mostly" satisfied with their course. We've analysed this figure against other universities so you can see whether this is high, medium or low.
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This information is from the Higher Education Statistics Agency (HESA), for undergraduate students only.
You can use this to get an idea of who you might share a lecture with and how they progressed in this subject, here. It's also worth comparing typical A-level subjects and grades students achieved with the current course entry requirements; similarities or differences here could indicate how flexible (or not) a university might be.
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Post-six month graduation stats:
This is from the Destinations of Leavers from Higher Education Survey, based on responses from graduates who studied the same subject area here.
It offers a snapshot of what grads went on to do six months later, what they were earning on average, and whether they felt their degree helped them obtain a 'graduate role'. We calculate a mean rating to indicate if this is high, medium or low compared to other universities.
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Graduate field commentary:
The Higher Education Careers Services Unit have provided some further context for all graduates in this subject area, including details that numbers alone might not show
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The Longitudinal Educational Outcomes dataset combines HRMC earnings data with student records from the Higher Education Statistics Agency.
While there are lots of factors at play when it comes to your future earnings, use this as a rough timeline of what graduates in this subject area were earning on average one, three and five years later. Can you see a steady increase in salary, or did grads need some experience under their belt before seeing a nice bump up in their pay packet?
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