Taught course

Web Science and Big Data Analytics

UCL - University College London · Computer Science

Entry requirements

A minimum of an upper second-class UK Bachelor's degree in a highly quantitative subject, or an overseas qualification of an equivalent standard. Students should also have some experience with a programming language such as Java or python. If your education has not been conducted in the English language, you will be expected to demonstrate evidence of an adequate level of English proficiency. The English language level for this programme is: Good. Further information can be found on our English language requirements http://www.ucl.ac.uk/prospective-students/graduate/life/international/english-requirements page.

Months of entry


Course content

The MRes covers web-related technologies and big data analytics. It is intended for students with a general science and engineering background and makes them well equipped to proceed to become the ideal choice for the best employers in internet-related industries and the areas requiring big data analytical skills.

UCL Computer Science is recognised as a world leader in teaching and research, and was one of the top-rated departments in the country according to the UK government's recent Research Excellence Framework.

Our Master's programmes have some of the highest employment rates and starting salaries, with graduates entering a wide variety of industries, from entertainment to finance.

We take an experimental approach to our subject, enjoy the challenge and opportunity of entrepreneurial partnerships and place a high value on our extensive range of industrial collaborations.

Full-time: 1 year;

Qualification and course duration


full time
12 months


The programme is delivered through a combination of lectures, tutorials and seminars. Lectures are often supported by laboratory work with help from demonstrators. For the research project, each student is liaised with their academic or industrial supervisor to choose a study area of mutual interest. Student performance is assessed by unseen written examinations, coursework and the research dissertation.

Course contact details

+44 (0)20 3370 1214