This MSc teaches advanced analytical and computational skills for success in a data rich world. Designed to be both mathematically rigorous and relevant, the programme covers fundamental aspects of machine learning and statistics, with potential options in information retrieval, bioinformatics, quantitative finance, artificial intelligence and machine vision.
Modes and duration
Tuition fees (2020/21)
Note on fees: The tuition fees shown are for the year indicated above. Fees for subsequent years may increase or otherwise vary. Further information on fee status, fee increases and the fee schedule can be viewed on the UCL Students website.
Fee deposit: All full time students are required to pay a fee deposit of £2,000 for this programme. All part-time students are required to pay a fee deposit of £1,000.
A minimum of an upper second-class UK Bachelor's degree in a highly quantitative subject such as computer science, statistics, mathematics, electrical engineering or the physical sciences, or an overseas qualification of an equivalent standard. Relevant work experience may also be taken into account. Students must be comfortable with undergraduate-level mathematics; in particular it is essential that the candidate will have knowledge of statistics at an intermediate undergraduate level. The candidate should also be proficient in linear algebra and multivariable 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.
International applicants can find out the equivalent qualification for their country by selecting from the list below.
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About this degree
The programme aims to provide graduates with the foundational principles and the practical experience needed by employers in the area of machine learning and statistics. Graduates of this programme will have had the opportunity to develop their skills by tackling problems related to industrial needs or to leading-edge research.
Students undertake modules to the value of 180 credits.
The programme consists of two core modules (30 credits), three to five optional modules (45 to 75 credits), one to three elective modules (15 to 45 credits) and a research project (60 credits). Please note that not all combinations of optional modules will be available due to timetabling restrictions.
Upon successful completion of 180 credits, you will be awarded a MSc in Computational Statistics and Machine Learning.
- Statistical Models and Data Analysis (15 credits)
- Supervised Learning (15 credits)
- MSc Computational Statistics and Machine Learning Project
Students must choose 45 to 75 credits from these optional modules. Students can also select 15 to 45 credits from elective modules.
- Advanced Topics in Machine Learning (15 credits)
- Applied Machine Learning (15 credits)
- Approximate Inference and Learning in Probabilistic Models (15 credits)
- Graphical Models (15 credits)
- Information Retrieval and Data Mining (15 credits)
- Introduction to Deep Learning (15 credits)
- Inverse Problems in Imaging (15 credits)
- Machine Vision (15 credits)
- Multi-agent Artificial Intelligence (15 credits)
- Probabilistic and Unsupervised Learning (15 credits)
- Reinforcement Learning (15 credits)
- Selected Topics in Statistics (15 credits)
- Statistical Natural Language Processing (15 credits)
Please note: the availability and delivery of optional modules may vary, depending on your selection.
A list of acceptable elective modules is available on the Departmental page.
Please note that the list of modules given here is indicative. This information is published a long time in advance of enrolment and module content and availability is subject to change.
All MSc students undertake an independent research project, which culminates in a dissertation of 10,000-12,000 words.
Teaching and learning
The programme is delivered through a combination of lectures, discussions, practical sessions and project work. Student performance is assessed through unseen written examinations, coursework, practical application and the project assessment process.
For more information about funding opportunities for Department of Computer Science postgraduate programmes, please see the departmental Scholarships and Funding pages: www.ucl.ac.uk/computer-science/scholarships-and-funding
Scholarships relevant to this department are displayed below.
- Deadline: 14 May 2020
- £15,000 (1 year)
- Based on both academic merit and financial need
For a comprehensive list of the funding opportunities available at UCL, including funding relevant to your nationality, please visit the Scholarships and Funding website.
There is a strong national and international demand for graduates with skills at the interface of traditional statistics and machine learning. Substantial sectors of UK industry, including leading, large companies already make extensive use of computational statistics and machine learning techniques in the course of their business activities. Globally there are a large number of very successful users of this technology, many located in the UK. Areas in which expertise in statistics and machine learning is in particular demand include: finance, banking, insurance, retail, e-commerce, pharmaceuticals, and computer security. Graduates have gone on to further study at, for example, the Universities of Cambridge, Helsinki, Chicago, as well as at UCL. The MSc is also ideal preparation for a PhD, in statistics, machine learning or a related area.
Scientific experiments and companies now routinely generate vast databases and machine learning and statistical methodologies are core to their analysis. There is a considerable shortfall in the number of qualified graduates in this area internationally. CSML graduates have been in high demand for PhD positions across the sciences. In London there are many companies looking to understand their customers better who have hired our CSML graduates. Similarly graduates now work in companies in, amongst others, Germany, Iceland, France and the US in large-scale data analysis. The finance sector has also hired several graduates recently.
Why study this degree at UCL?
The Centre for Computational Statistics and Machine Learning (CSML) is a major European Centre for machine learning having coordinated the PASCAL European Network of Excellence.
Coupled with the internationally renowned Gatsby Computational Neuroscience and the Machine Learning Unit, and UCL Statistical Science, this MSc programme draws on world-class research and teaching talents. The centre has excellent links with world-leading companies in internet technology, finance and related information areas.
The programme is designed to train students in both the practical and theoretical sides of machine learning. A significant grounding in computational statistics is also provided.
Department: Computer Science
Application and next steps
Students are advised to apply as early as possible due to competition for places. Those applying for scholarship funding (particularly overseas applicants) should take note of application deadlines.
There is an application processing fee for this programme of £80 for online applications and £105 for paper applications. Further information can be found at: www.ucl.ac.uk/prospective-students/graduate/taught/application.
Who can apply?
The programme is suitable for students with good analytical abilities. Graduates will benefit directly from our excellent academic and industrial links, either by embarking on further study in a leading centre in machine learning/statistics or by taking up a place in industry, in information retrieval, finance or bioinformatics.
- All applicants
- 12 June 2020
Due to the competition for places on this programme, no late applications will be considered.
For more information see our Applications page.Apply now
What are we looking for?
When we assess your application we would like to learn:
- why you want to study Computational Statistics and Machine Learning at graduate level
- why you want to study Computational Statistics and Machine Learning at UCL
- what particularly attracts you to this programme
- how your academic and professional background meets the demands of this programme
- what mathematics and statistics experience you have
- what programming experience you have
- where you would like to go professionally with your degree
Please preface your personal statement with a note on modules taken which strongly relate to: Statistics, Linear Algebra and Multivariable Calculus. Together with essential academic requirements, the personal statement is your opportunity to illustrate whether your reasons for applying to this programme match what the programme will deliver.
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