A minimum of an upper second-class UK Bachelor's degree (or overseas equivalent) in a quantitative subject as computer science, engineering, mathematics, physics or a quantitative social science subject.
Applicants must be proficient in object-orientated and/or analytical programming, have strong communication skills, and an outstanding aptitude for quantitative analysis.
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
This exciting and challenging programme studies how data can be utilised to solve major business and societal challenges. The programme provides students with the knowledge, technical ability and skills for leadership roles in the fields of business analytics and data science.
UCL Computer Science is a global leader in research in experimental computer science. The 2014 Research Excellence Framework (REF) ranked the department as first in the UK for research, with 96% regarded as 'world-leading' or 'internationally excellent'.
The department consists of a team of world-class academics specialising in big data, computational statistics, machine learning and complexity.
The programme aims to create the next generation of outstanding academics and industry pioneers, who will use data analysis to deliver real social and business impact.
Full-time: 1 year;
Qualification and course duration
The programme is delivered through a combination of lectures by world-class academics and industry leaders, seminars, workshops, tutorials and project work. The programme comprises two terms of taught material, followed by examinations and then a project. Assessment is through unseen written examinations, coursework and the dissertation.
Further details are available on the subject website.
Course contact details
- +44 (0)20 3370 1214