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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.

Key Information

Modes and duration

  • Full-time: 1 year

Programme start date

September 2016

Tuition Fees (2016/17)

£11,090 (FT) £5,725 (PT)
£23,440 (FT) £11,670 (PT)

Application dates

All applicants
Open: 1 November 2015
Close: 17 June 2016

Entry Requirements

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: Standard

Further information can be found on our English language requirements page.

International students

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.

Select your country:

Degree Information

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 four core modules (60 credits), four optional modules (60 credits) and a research project (60 credits). Please note that not all combinations of optional modules will be available due to timetabling restrictions.

Core Modules

  • Supervised Learning
  • Statistical Modelling and Data Analysis
  • Graphical Models or Probabilistic and Unsupervised Learning

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


  • Advanced Topics in Machine Learning
  • Affective Computing and Human-Robot Interaction
  • Applied Bayesian Methods
  • Applied Machine Learning
  • Approximate Inference and Learning in Probabilistic Models
  • Bioinformatics
  • Computational Modelling for Biomedical Imaging
  • Forecasting
  • Information Retrieval and Data Mining
  • Inverse Problems in Imaging
  • Machine Vision
  • Programming and Mathematical Methods for Machine Learning
  • Selected Topics in Statistics
  • Statistical Computing
  • Statistical Design of Investigations
  • Statistical Inference
  • Statistical Natural Language Programming
  • Stochastic Methods in Finance
  • Stochastic Methods in Finance 2


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 information on modules and degree structure available on the department web site Computational Statistics and Machine Learning MSc


Scholarships relevant to this department are displayed (where available) below. For a comprehensive list of the funding opportunities available at UCL, including funding relevant to your nationality, please visit the Scholarships and Funding website.

Brown Family Bursary - NOW CLOSED FOR 2015/16 ENTRY

£15,000 (1 year)
UK students
Based on both academic merit and financial need

Computer Science Excellence Scholarships

£4,000 (1)
UK, EU students

More scholarships are listed on 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.

Top career destinations for this degree

  • Risk Analyst, Wonga (2013)
  • Research Engineer, Google (2013)
  • Data Scientist, YouGov (2013)
  • Statistical and Algorithm Analyst, Telemetry (2013)
  • Data Scientist, Harper Collins Publishers (2012)


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 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.

Student / staff ratios › 200 staff including 120 postdocs › 650 taught students › 175 research students

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.

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.

Application deadlines

All applicants
17 June 2016
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.

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
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.

Contact Information


  • Register interest in your chosen subjects
  • Receive notice of graduate open days, events and more
Register now

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