Entry Requirements
Entry Requirements
- This MSc programme is designed for graduates with a first or upper second-class Honours degree (or equivalent) in a highly quantitative subject such as computer science, mathematics, electrical engineering or the physical sciences, who can handle the required underlying mathematics. Students should also have some experience with a programming language such as Matlab.
- Additionally, candidates will be expected to have successfully completed as part of their first degree, one or more introductory courses covering appropriate foundation material on Machine Learning, or to have gained this through industrial experience.
- Appropriate industrial experience may also be considered in some cases
You may wish to look at the Preparation Guide on our course webpages. This gives more information on what you should have covered before you begin the course.
English Language Requirements (needed in addition to above requirements)
International English Language Testing System (IELTS) :
- Overall grade of 6.5 with a minimum of 6.0 in each of the subtests.
Test of English as a Foreign Language (TOEFL):
Paper based version
- Score of 580, plus 4 in Test of Written English (TWE).
Internet based version
- Score of 92, plus 24/30 in the reading and writing subtests and 23/30 in the listening and speaking subtests.
Other English Language Qualifications:
Please click here for the full list of accepted English Language qualifications.
MSc ML requires UCL's "Standard" level of English
- Applicants are required to meet both the entry requirements and the English Language requirements separately.
- Each applicant will be considered on an individual basis.
- The grades and qualifications listed above are intended to give an approximate level of achievement we believe you will need to succeed on the programme. These are for guidance only and are in addition to UCL's general entry requirements.
Department of Computer Science, UCL (University College London)
Malet Place, London WC1E 6BT, UK
Phone: 020 7679 7214 (+44 20 7679 7214)
Fax: 020 7387 1397 (+44 20 7387 1397)













