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Undergraduate degrees » Data Science


Big data:

Computer science and statistical methods in perfect synergy:

  • three-year BSc Data Science (Hons)
  • new: four-year MSci in Data Science

These degrees are designed for able mathematicians with an interest in pursuing sophisticated theory and methods relevant to modern applications requiring large-scale data analysis. It prepares you for cutting edge data handling and analysis for the information challenges of tomorrow.

It is organised jointly by the Department of Statistics and the Department of Computer Science.

Data Science

This degree is the first of its kind in the UK. It emphasizes a mathematical approach to the computational analysis of data.

The 21st Century has brought new challenges in the analysis of data, and it is increasingly apparent that solutions to these are both statistical and computational. This has led to a great demand for people both in industry and in research who are able to draw upon the mathematics of both computation and probability to make sense of the large amounts of data that are collected in order to solve major problems.

Data science is an interdisciplinary response to this demand, and in our BSc degree programme students follow a carefully selected curriculum from Computer Science, Mathematics and Statistics.

More Information

Undergraduate brochure(PDF Document)

Warwick University Undergraduate prospectus

Data Science including videos with academics.

Related degree courses

MathStat, MMathStat 


Data science students' voices

About data science


Demand for Data Scientists

In every facet of modern life, from online shopping and social networks to scientific research and finance, we collect immensely detailed information. Data scientists are concerned with turning this data into intelligence through the application of cutting-edge techniques in Statistics and Computer Science.

Global demand for combined statistical and computing expertise outstrips supply, with evidence-based predictions of a major shortage in this area for at least the next 10 years. For graduates in Data Science this shortage presents opportunities to forge careers in a critical area.

two students


Application should be made to to either DatSci (7G73) or MDatSci (G304) but not both. Transfers between these two degrees is straightforward during the first two years at university (details under Course structure).

Transfers between all our degrees - DatSci, MDatSci, MathStat, MMathStat, MORSE and MMORSE - are usually straightforward for offer-holders and even beyond; see FAQs for more details. We therefore recommend applying to just one of our degrees.

Overseas students need to make changes to their visa when changing their degree course, even within the same department - see International Student Immigration Service.

For more information see under Admissions on our Undergraduate pages.

Course structure

The curriculum is built on the principle that module choices get more and more flexible as you progress through the degree. In any year, you may choose to 'overload' and study additional options.

Year 1

The compulsory modules in year 1 build a strong, general mathematical foundation. You will also be introduced to Programming, Data Structures, Probability and Exploratory Data Analysis.

Year 2

In year 2, Statistical topics are explored in considerable depth, and students are exposed to Algorithms, Databases and Software Engineering. There are a number of optional modules, such as Artificial Intelligence and Linear Statistical Modelling.

Year 3

The only compulsory module is the Data Science Project, which allows you to showcase the skills you have developed. The remainder of the year consists of optional, advanced modules from both Statistics and Computer Science, such as Machine Learning and Bayesian Forecasting.



More information on optional modules can be found in the course handbook. (Currently only available for the 3-year degree, but coming soon for the new 4-year degree.)

More information

Go back to our undergraduate degree page for a wide collection of links about learning and study experience.

Undergraduate courses