Computational Statistics and Machine Learning MSc
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, quantative finance, artificial intelligence and machine vision.
Mode of study
- Full-time 1 year
- UK/EU Full-time: £10,450
- Overseas Full-time: £21,700
- All applicants: 1 August 2014
More details in Application section.
What will I learn?
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.
Why should I 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 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.
Students undertake modules to the value of 180 credits. The programme consists of four core modules (60 credits), four optional modules (60 credits) and a research project (60 credits).
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.
Further details available on subject website:
We are offering four MSc Excellence Scholarships worth £4,000 to UK/EU offer holders with a record of excellent academic achievement. Please note that the closing date for applying for this is 30 June 2014.
Scholarships available for this department
This award is based on financial need.
Further information about funding and scholarships can be found on the Scholarships and funding website.
A minimum of an upper second-class UK Bachelor's degree in 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.
Select your country for equivalent alternative requirements
English language proficiency level: Standard
How to apply
Students are advised to apply as early as possible due to competition for places. Applications received after the end of March are less likely to be successful.
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.
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
There is a strong national and international demand for graduates with skills at the interface between 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.
Top career destinations for this programme
- Gulf International Bank, Quantitative Analyst, 2011
- Alchamatics, Director, 2011
- Markit, VP of Fixed Income Department, 2011
- Cognitive Match, Researcher, 2011
- UBS, Trader, 2010
Scientific experiments and companies now routinely generate vast databases and machine learning and statistical methodologies are core to their analysis. CSML graduates have been in high demand for PhD positions across the sciences. There is a considerable shortfall in the number of qualified graduates in this area internationally. In London there are many companies looking to understand their customers better and have therefore hired CSML graduates. Similarly CSML graduates now work in companies in, amongst others, Germany, Iceland, France and the US in large-scale data analysis. The finance sector is also particularly interested in CSML graduates, having hired several recently.
Miss Rebecca Martin
T: +44 (0)20 7679 0481
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