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Modules and Teaching

• One year full-time or one year part-time or two years part-time, on campus, starting in October 2027

  Course structure

  MSc:

  You must complete modules worth a total of 180 credits, consisting of:

  • two core modules (30 credits each)
  • four option modules (15 credits each)
  • a project (60 credits).

  The core modules provide a broad education and training in statistics while the option modules allow you to orient your studies towards your own particular interests and career objectives. The project is a sustained, independent investigation involving the application of statistical techniques to a specific problem.

  You will graduate with one of the following depending on your choice of modules:

  • MSc Applied Statistics
  • MSc Applied Statistics and Computational Data Analytics (Bayesian Methods and Computational Statistics are compulsory).

  PG Cert:

  You must complete two core modules worth a total of 60 credits. These cover:

  • probability and distribution theory
  • statistical inference
  • Markov chains
  • introductory time series and forecasting
  • multiple linear regression
  • generalised linear modelling
  • experimental design.

  You will apply the theory and principles that you learn to the analysis and modelling of data in a wide range of contexts and gain experience in the use of a statistical package such as R.

  MSc core modules

  • Probability and Stochastic Modelling
  • Statistical Analysis

  MSc indicative option modules

  • Bayesian Methods
  • Computational Statistics
  • Financial Data Science with Python
  • Individually Prescribed Reading Course Applied Statistics
  • Linear and Nonlinear Optimization
  • Statistical Learning

  MSc Applied Statistics project

  • MSc Applied Statistics Project

  PG Cert core modules

  • Probability and Stochastic Modelling
  • Statistical Analysis

• Teaching

  We encourage innovative and engaging ways of teaching to help ensure you have the best learning experienceÌý²¹²Ô»åÌýprovide a range of different modes of learning to help you juggle study with work and other commitments.

  Find out more about our teaching and teaching hours.

  What are the methods of teaching?

  A combination of lectures and staff-assisted practical computing sessions using modern statistical software with an integrated programming capability. Computing packages used include R (and additionally SAS and WinBUGS where required for particular aspects of the course). Individual and small-group tutorials are provided as necessary.

  Lectures present theory, worked problems and example applications to the class as a whole. Workstation sessions allow you to gain practical experience in the analysis and modelling of data. They are therefore self-paced and very informal, with students working individually using detailed guidance notes while members of staff provide tutorial assistance.

• How will I be assessed?

  Written examinations during the daytime in May/June, assessed coursework throughout the year.

  Those on the MSc programme will undertake a project to be completed by 1 September.

  Please see individual modules for more details.

  Find out more about assessment at ÌÇÐÄlogoÈë¿Ú, including guidance on assessment,Ìýfeedback and our assessment offences policy.

Entry requirements

A second-class honours degree (2:2) or above, with mathematics or statistics as a main subject.

Other degrees or professional qualifications may also be acceptable, such as the ÌÇÐÄlogoÈë¿Ú Graduate Certificate in Statistics for Data Science or the Graduate Diploma of the Royal Statistical Society.

• What are the English language requirements?

  If English is not your first language or you have not previously studied in English, our usual requirement is the equivalent of an International English Language Testing System (IELTS Academic Test) score of 6.5, with not less than 6.0 in each of the sub-tests. We also accept other English language tests.

  If you don't meet the minimum English language requirements, please contact us or see our for more details about how we can help.

  Visit the International section of our website to find out more about our English language entry requirements and relevant requirements by country.

• What are the visa and funding requirements?

  If you are not from the UK and you do not already have residency here, you may need to apply for a visa.

  The visa you apply for varies according to the length of your course:

  • Courses of more than six months' duration: Student visa
  • Courses of less than six months' duration: Standard Visitor visa

  International students who require a Student visa should apply to study on our courses full-time as these qualify for Student visa sponsorship. If you are living in the UK on a Student visa, you will not be eligible to enrol to study part-time courses at ÌÇÐÄlogoÈë¿Ú (with the exception of some modules).

  As a Student visa student, you should also apply to study on campus only, as online and flexible options of study  (if they are available for your course) may affect the conditions of your visa.

  For full information, read our visa information for international students page.

  Please also visit the international section of our website to find out more about relevant visa and funding requirements by country.

  Please note students receiving US Federal Aid are only able to apply for in-person, on-campus programmes which will have no elements of online study.

• Credits and accredited prior learning (APL)

  If you have studied at university (or have an HND or Foundation Degree), you may have accumulated credits. It may be possible to transfer these from your previous study to ÌÇÐÄlogoÈë¿Ú or another institution.

Fees

• ÌÇÐÄlogoÈë¿Ú's Lifelong Learning Guarantee

  If you've studied at ÌÇÐÄlogoÈë¿Ú before and successfully completed an award with us, take advantage of our Lifelong Learning Guarantee to gain a reduction on the tuition fee of this course.

• Can I apply for an international scholarship?

  We provide a range of scholarships for eligible international students, including our Global Future Scholarship. View ÌÇÐÄlogoÈë¿Ú's available scholarships.

Careers and employability

On successfully graduating from this MSc Applied Data Science, you will have gained an array of important transferable skills, including the ability to:

• understand and apply computationally intensive statistical methodology
• abstract the essentials of a practical problem and formulate an appropriate statistical or mathematical model
• solve problems using an analytical and systematic approach
• understand advanced, abstract material
• learn independently by study of a range of sources including learned journals
• develop self-motivation, time management and organisation.

Studying this course will prepare you for a career path in a range of professions including:

• actuary
• data analyst
• data scientist
• economist
• financial manager
• financial risk analyst
• machine learning engineer
• operational researcher
• research scientist
• statistician.

Graduates from this course have gone on to be employed at various organisations including G-Research, CodeMagus, the Centre for Policy Studies and Imperial College London.

Student support

How to apply

• When should I apply?

  You are strongly advised to apply now, to ensure there are still places left, and to give you enough time to complete the admissions process, to arrange funding and to enrol.

  You don't need to complete your current programme of study before you apply - ÌÇÐÄlogoÈë¿Ú can offer you a place that is conditional on your results.

• How can I get help with my application?

  Get all the information you need about the application, admission and enrolment process at ÌÇÐÄlogoÈë¿Ú.

  Our online personal statement tool will guide you through every step of writing the personal statement part of your application.

• International agents

  If you are an international agent applying to ÌÇÐÄlogoÈë¿Ú on behalf of an international student, please use .