Data Analytics MSc

Course overview

Entry requirements

  • One of the following:
    A minimum of a lower second class honours BSc degree in a highly numerate discipline. Equivalent overseas degree recognised by Aston University
  • For international applicants:
    An official academic transcript, with an official English translation, of your university grades to date. Applicants whose first language is not English will be required to provide evidence of an English language qualification. See below for more information.
  • Full entry requirements
    See entry requirements for full details
More information

Key dates

  • Start Date
    September/October 2020
  • Open Days
    Our next Open Day is taking place on:
    Saturday 23rd November

Opportunity to gain a masters qualification through independent study

Full support of internationally-recognised academic staff in machine learning and data science

Close links with industry

A high level of expertise in an in-demand area will enhance your global employability prospects

Course Summary

This programme provides students with an in-depth and high level of scientific knowledge and understanding of data science that is applicable to industry, with the option to focus on specific areas of interest through their choice of a research project. It enables students to develop an informed and critical appreciation of recent scientific and industrial developments in data science and analytics. This course is delivered through a combination of tutorial-based learning and self-directed study.

Entry Requirements and Fees

Duration of programme: 1 year full-time: six months of taught modules on campus and a six month individual project. 
Start date:


Intake: Up to 25 per year




UK/EU: £9,350 (2020/21 fee)


International: £16,700 (2020/21 fee)




Entry Requirements

One of the following:


  • A minimum of a second class Honours Degree from a UK academic organisation.

  • Equivalent overseas degree recognised by Aston University.


As well as:


  • Two professional references – at least one must be from an academic referee

  • A completed application form.


For International Students:









Applicants with extensive work experience:




We recognise the value of extensive professional experience. If you do not have the academic qualifications, but have extensive and relevant professional experience and a proven ability to succeed, we would welcome your application.




The information contained on this website details the typical entry requirements for this course for the most commonly offered qualifications. Applicants with alternative qualifications may wish to enquire with the relevant admissions teams prior to application whether or not their qualifications are deemed acceptable. For less commonly encountered qualifications this will be judged on a case-by-case basis in consultation with the academic admissions tutor.

Course Outline

Throughout the programme you will create and implement data analytics algorithms using advanced computational skills and appraise the likelihood of successful implementation of these algorithms. The critical analysis and evaluation of the methodology and techniques related to data science will also be undertaken. The techniques will be employed to solve relevant problems in data analytics. You will devise a research project based in a chosen area and apply the knowledge of data analytics gained on the programme to produce high quality independent work, resulting in a dissertation.

As the programme is designed as a mix of tutorial-based learning and self-directed study, this provides you with an excellent opportunity to develop your own independent research skills.

Please note the learning hours on this programme are limited to tutorials, online activity, reading, other independent study and reflection on assignment feedback.

Subject Guide and Modules

15 credit modules:

  • Statistical Machine Learning,
  • Specialist Research Skills and Techniques,
  • Algorithmic and Computational Mathematics,
  • Understanding Data,
  • Probabilistic Modelling,
  • Data Science Programming,
  • Artificial Neural Networks,
  • Network Science

60 credit module:

  • Research Project
Learning, Teaching and Assessment

This Masters in Data Analytics is designed to be a mix of tutorial based teaching and self-directed study, whereby you will be supplied with the relevant learning material and then will look to discuss your understanding and application of your learning in scheduled tutorials.

The learning hours will be limited to tutorials, online activity, reading, other independent study and reflecting on assignment feedback.

The taught modules will be assessed via coursework and the project via a dissertation and a viva examination.

Teaching staff

Postgraduate Programme Director: Dr S Jain

More teaching staff:


Contact us

Tel: +44 (0)121 204 4910

Email: ask@aston.ac.uk


Register your interest