A minimum of an upper second-class UK Bachelor's degree in a highly quantitative subject such as computer science, mathematics, electrical engineering or the physical sciences, or an overseas qualification of an equivalent standard. Relevant work experience may also be taken into account. Additionally, candidates must be comfortable with undergraduate mathematics in areas such as linear algebra and calculus.
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
The Machine Learning MSc at UCL is a truly unique programme and provides an excellent environment to study the subject. It introduces the computational, mathematical and business views of machine learning to those who want to upgrade their expertise and portfolio of skills in this domain.
UCL Computer Science is recognised as a world leader in teaching and research, and our Master's programmes have some of the highest employment rates and starting salaries.
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.
This MSc is one of the few leading Master's programmes entirely dedicated to machine learning. It combines a rigorous theoretical academic framework along with specific knowledge of a variety of application fields to fast-track your commercial career or to prepare for PhD research.
Full-time: 1 year;
Qualification and course duration
The programme is delivered through a combination of lectures, seminars, class discussions and project supervision. Student performance is assessed though a combination of unseen written examination, coursework (much of which involves programming and/or data analysis), practical application, and the research project.
Course contact details
- +44 (0)20 3370 1214