e-Brochure

PDF version of Computational Statistics and Machine Learning MSc

Contact details

Miss Rebecca Martin

Email: rebecca.martin@cs.ucl.ac.uk

Tel: +44 (0)20 7679 0481

Fees and funding

UK/EU 2013/14:

£10,250 (FT)

Overseas 2013/14:

£21,000 (FT)

Full details of funding opportunities can be found on the UCL Scholarships website

More information

Prospectus Entry

Computer Science

Key facts

Research Assessment Rating

80% rated 4* (world-leading) or 3* (internationally excellent)
(What is the RAE?)

The programme information on this page relates to 2013 entry. 2014 content to appear here shortly. 

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.

Degree summary

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 and is scientific coordinator of the PASCAL2 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, and 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.

See subject website for more information:

Degree structure

Availability: Full-time 1 year

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).

A Postgraduate Diploma (120 credits) is offered.

A Postgraduate Certificate (60 credits) is offered.

Core Modules

  • Supervised Learning
  • Statistical Modelling and Data Analysis
  • Either Graphical Models or

  • Plus one of:
  • Applied Bayesian Methods
  • Statistical Design of Investigations
  • PLUS ONE OF:
  • Applied Bayesian Methods
  • Statistical Design of Investigations
  • Statistical Computing
  • Statistical Inference

Options

  • Machine Vision
  • Bioinformatics
  • Information Retrieval and Data Mining
  • Forecasting
  • Stochastic Methods in Finance
  • Advanced Topics in Machine Learning
  • Evolutionary and Natural Computation
  • Inverse Problems in Imaging
  • Approximate Inference and Learning in Probabilistic Models
  • Programming and Mathematical Methods for Machine Learning
  • Stochastic Methods in Finance II
  • Advanced Topics in Statistics
  • Applied Machine Learning

Dissertation/report

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:

Entry and application

Entry requirements

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.

For overseas equivalencies see the relevant country page.

How to apply

You may choose to apply online or download application materials; for details visit www.ucl.ac.uk/gradapps

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. Those applying for scholarship funding (particularly overseas applicants) should take note of application deadlines.

Who can apply?

The programme is suitable for students with good analytical abilities, and 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 search/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 programming experience you have
  • where you would like to go professionally with your degree
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.

Career

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, and the UK has a number of very successful developers and suppliers of the technology. 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 the University of Cambridge and at the University of Chicago, USA. They also make excellent recruits for PhDs in statistics, machine learning or related areas.

Find out more about London graduates' careers by visiting the Careers Group (University of London) website:


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