MSc Data Science (with specialisation in Statistics)

Data Science brings together computational and statistical skills for data-driven problem solving, which is in increasing demand in fields such as marketing, pharmaceutics, finance and management. This MSc will equip students with the analytical tools to design sophisticated technical solutions using modern computational methods and with an emphasis on rigorous statistical thinking.

The programme combines training in core statistical and machine learning methodology, beginning at an introductory level, with a range of optional courses covering more specialized knowledge in statistical computing and modelling.

Please click the headings below for further information:

Programme Structure

Students undertake modules to the value of 180 credits. The programme consists of a foundation module (non-credit bearing), eight taught modules (120 credits) and a research dissertation (60 credits).

Further information about specific course units in Statistical Science, including outline syllabuses and reading lists, is available from the current departmental handbook for taught graduate students.

Further information about specific course units in Computer Science, including outline syllabuses and reading lists, is available from the following webpage.

Modes of Study

Full time, the degree will last 12 months (including a summer project).

Part time study is also available over two years. Studying the MSc Data Science on a part time basis means taking the same compulsory and optional modules over two years, but they are as timetabled for full time students (special teaching times are not offered for part time students). It is possible to arrange with the project supervisor to start to work on the research project earlier than after the exams in the second year, but there is no entitlement to a higher overall amount of supervision than full time students.

Teaching and Assessment

Teaching is by means of lectures and classes, some of which are dedicated to practical work. There is also the possibility of external organisations delivering technical lectures and seminars. The taught degree programme involves about 200 hours of lectures and classes altogether. Students also attend weekly tutorials.

Students will be assessed on eight taught modules in total. For most courses the final mark is based on an in-course assessment (given 10% weighting) and a two-hour written examination sat in term three (given 90% weighting). However, there are no written examinations for the Statistical Design of Investigations and Statistical Computing modules, which are assessed entirely through coursework.

Research Project

The Research Project is a consolidation of the MSc’s taught component. Students will normally analyse and interpret data from a real, complex problem, offering the chance to produce viable solutions. Workshops, which provide preparation for this project, will run during the teaching terms. These will cover the communications of statistics such as the presentation of statistical graphs and tables.

Project topics can be selected from a departmental list, or students can make their own suggestions. The list usually includes some collaborative projects available with pharmaceutical companies or other industrial partners.

Professional Accreditation

The Department of Statistical Science will be seeking Royal Statistical Society (RSS) accreditation for the new MSc Data Science programme. Graduates will then automatically be granted the Society’s Graduate Statistician (GradStat) status (a stepping stone to the Chartered Statistician (CStat) professional qualification) on application to the Society. In the meantime, graduates with this degree may apply individually for GradStat status.

Visit the below link for more details on the RSS and the GradStat and CStat qualifications.

Contact Details

For more information on the programme please contact:

Dr Russell Evans
stats.pgt-admissions AT ucl.ac.uk
+44 (0)20 7679 8311