MSc Machine Learning is a unique programme that introduces students to the computational, mathematical and business views of machine learning. The programme is led and taught by world renowned researchers from the Department of Computer Science and the Gatsby Computational Neuroscience Unit.
The programme will provide students with an understanding of the development and application of new techniques in the field; an ability to analyse the range and scope of algorithms and approaches available; and the skills to design, develop and evaluate appropriate algorithms and methods for new problems and applications.
MSc Machine Learning comprises 8 taught modules and an Individual Project. Of the taught modules, 1 is a core module, with a minimum of 5 modules from options and the remainder from a combination of optional and elective modules.
Compulsory / Core Modules
- COMP0078 - Supervised Learning (15 credits)
- COMP0091 - Individual Project (60 credits)
All modules in this group are compulsory.
- COMP0089 - Advanced Deep Learning and Reinforcement Learning (15 credits)
- COMP0083 - Advanced Topics in Machine Learning (15 credits)
- COMP0053 - Affective Computing and Human-Robot Interaction (15 credits)
- COMP0081 - Applied Machine Learning (15 credits)
- COMP0085 - Approximate Inference and Learning in Probabilistic Models (15 credits)
- COMP0082 - Bioinformatics (15 credits)
- COMP0080 - Graphical Models (15 credits)
- COMP0084 - Information Retrieval and Data Mining (15 credits)
- COMP0090 - Introduction to Deep Learning (15 credits)
- COMP0137 - Machine Vision (15 credits)
- COMP0086 - Probabilistic and Unsupervised Learning (15 credits)
- COMP0087 - Statistical Natural Language Processing (15 credits)
Choose a minimum of 75 credits and a maximum of 90 credits from these optional modules.
Students must take either COMP0080 or COMP0086.
- COMP0118 - Computational Modelling for Biomedical Imaging (15 credits)
- COMP0114 - Inverse Problems in Imaging (15 credits)
- COMP0120 - Numerical Optimisation (15 credits)
- COMP0128 - Robotic Control Theory and Systems (15 credits)
- COMP0127 - Robotic Systems Engineering (15 credits)
Choose a minimum of 15 credits and a maximum of 30 credits from these elective modules.
All choices are subject to timetabling constraints and the approval of the relevant Module Tutor (i.e. to ensure any prerequisites are satisfied) and the Programme Director.
Programme diet (modules available to you)
Your programme has a set curriculum (also called a diet) which prescribes in what combinations modules can be taken, any restrictions on doing so, and how much credit can and must be taken. The programme information pages show which modules form part of each programme, with links to descriptions and module syllabus information. Modules within a programme can be core, optional, or elective, which reflects whether they must be taken or are optionally taken.
Core modules are fundamental to your programme’s core curriculum and are mandatory. You will automatically be registered on your programme's core modules, so will not have to select them. You are guaranteed a place on modules that are core for your programme. There will be no timetable clashes between core modules within a programme.
Optional modules are usually closely related to the programme's core curriculum and you will be able to choose which to take; choices are usually made from within specific groups (for example, choose two optional modules from one group and three from another, etc.) You are not guaranteed a place on optional modules as space is strictly limited. We allocate places on a first come, first serve basis, with preference given to Computer Science students over those of other departments. Bear in mind that some modules have prerequisites that must be met in order to be eligible for a place (see the module syllabus for information.)
Elective modules are usually not specifically related to the programme's curriculum. There is no guarantee of being accepted onto an elective module; they are core and/ or optional on other programme diets, so students on those programmes will be given priority. As with optional modules, some electives have prerequisites that must be met.
Deciding which modules to select
The programme information pages show which modules form part of each programme, with links to detailed module syllabus information and reading lists. You may be able to virtually audit lectures for some modules to get a sense of how the module is delivered. You can look up the timetable for each module via the common timetable to get a sense of the timetable that would eventuate from your module choices, which is an important consideration when making your final choices; you should aim to achieve a timetable that is feasible and will not stretch you too thinly.
Bear in mind that places on optional and elective modules are not guaranteed, so you might not always be able to take all your first choices. In that case, it is a good idea to have a second preference in mind.
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.
English Language Requirements
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 page.
Country-specific information, including details of when UCL representatives are visiting your part of the world, can be obtained from the International Students website.
UK/EU fees (FT): £11,800 for 2017/18
Overseas fees (FT): £24,610 for 2017/18
UK/EU fees (FT): £12,950 for 2018/19
UK/EU fees (PT): N/A for 2018/19
Overseas fees (FT): £26,670 for 2018/19
Overseas fees (PT): N/A for 2018/19
The Department of Computer Science is offering Excellence Scholarships to our taught postgraduate students. To check your eligibility and to apply, see the Computer Science Excellence Scholarship application form.
For a comprehensive list of the funding opportunities available at UCL, including funding relevant to your nationality, please visit the Scholarship and Funding website.
Tuition Fee Deposit
This programme requires that applicants firmly accepting their offer pay a deposit. This allows UCL to effectively plan student numbers, as students are more demonstrably committed towards commencing their studies with us.
For full details about the UCL tuition fee deposit, please see the central UCL pages.
Tuition fee deposits within the Department of Computer Science are currently listed as:
|*where part-time is an available mode of study|
Machine Learning graduate destinations:
Machine Learning graduate roles:
Further study destinations:
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Average starting salary £45,000 (Graduate Surveys, January 2015).
To apply now click here.
This MSc receives many more applications than it has places available and the admissions process is competitive. It may therefore take longer than the Admissions stated 6 weeks for a decision to be made and communicated. Applicants are advised to apply as early as possible due to the competition for places. Those applying for scholarship funding (particularly overseas applicants) should take note of application deadlines.
Deadline 15th June 2018.