Undergraduate courses » Data Science
Underpinnings and practice of data science
Two courses representing statistics and computer science in perfect synergy:
- three-year BSc in Data Science (Hons)
- four-year integrated masters MSci in Data Science (Hons)
Our three-year BSc in Data Science (DatSci) and four-year MSci in Data Science (MDatSci) are Single Honours courses specifically designed for individuals keen to be exposed to the sophisticated theory and methods required for addressing modern data-analytic challenges. They equip you with the knowledge, skills, and attitude required by emerging challenges in the information age.
The courses are organised jointly by the Department of Statistics and the Department of Computer Science.
The DatSci and MDatSci courses are the first of their kind in the UK. They emphasize 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 these can be addressed by investing in the interaction between statistics and computer science. This realization has led to a great demand for people both in industry and in research who are able to draw upon the mathematics of statistics and computation to make sense of the large amounts of data that are collected in order to solve major problems.
DatSci and MDatSci are our interdisciplinary response to this demand, and in these course students follow a carefully designed curriculum from mathematics, statistics and computer science.
Data Science students' voices
- A recent data science graduate on our alumni page
- First cohort describes time at Warwick
Warwick University Undergraduate pages for Data Science courses
Three-year BSc in Data ScienceLink opens in a new window
Four-year MSci in Data ScienceLink opens in a new window
Related degree courses
BSc and BSc MMathStat in Mathematics and Statistics
BSc and BSc MMORSE in Mathematics, Operational Research, Statistics and Economics (MORSE)
About data science
- 50 Years of Data ScienceLink opens in a new window by Donoho (2017)
- The Role of Academia in Data Science EducationLink opens in a new window by Irizarry (2020)
- Very Short History of Data ScienceLink opens in a new window
- Data Science: An Artificial EcosystemLink opens in a new window Meng (2019) in Harvard Data Science Review
- All Science has become Data ScienceLink opens in a new window
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 science is concerned with turning this data into actionable knowledge 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 the graduates of our Data Science courses, this shortage presents opportunities to forge successful careers in a critical area.
Application should be made to to either DatSci (7G73) or MDatSci (G304) but not both. Transfers between these two courses is straightforward during the first two years at university (details under Course structure).
Transfers between all our courses - 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 courses.
Overseas students need to make changes to their visa when changing their course, even within the same department - see International Student Immigration Service. For EU students such considerations may become relevant in the future, too.
For more information see under Admissions on our Undergraduate pages.
The curriculum is built on the principle that module choices get more and more flexible as you progress through the degree. On top of that, you may choose to study additional options from an even wider range of modules.
The compulsory modules in the first year build a strong, general mathematical foundation. You will also be introduced to mathematical programming, data structures, probability and the foundations of data analysis.
In the second year, 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, games and decisions, and visualisation and communication with data.
The third (final) year of DatSci allows you to forge a strong curriculum through a selection of more advanced modules in statistics and computer science, such as machine learning and Bayesian forecasting. It also includes a Data Science Project, which is your opportunity to showcase and expand your data-analytic knowledge and skills.
The third year of MDatSci also involves a module whose aim is to prepare you for the statistical investigative cycle from problem formulation to the communication of conclusions. The fourth (final) year of MDatSci offers a range of advanced modules from across data science, and you also choose a masters-level dissertation project from a wide selection of topics.
DatSci or MDatSci?
DatSci and MDatSci are the same during the first two years, making it easy to reconsider your preference. Differences become apparent in the final years. In particular, the fourth year of the MDatSci course offers a supervised masters-level dissertation and the possibility to specialize in areas such as advanced statistical learning and big data, high-performance computing, algorithmic game theory, and computational biology and statistical genetics.
Go back to our undergraduate degree page for a wide collection of links about learning and study experience.