High Performance Computing with Data Science

University of Edinburgh


Off Campus


This programme aims to provide students with in-demand (for both a wide range of industries and academic disciplines) skills and knowledge of the techniques and technologies underpinning parallelism and High Performance Computing (HPC). HPC is the use of powerful processors, networks and parallel supercomputers to tackle problems that are very computationally or data-intensive.

The flexible structure ensures students acquire core principles required before proceeding to their choice of more advanced topics and allows students to take on the programme at their own pace. You can study to an MSc, Postgraduate Diploma, Postgraduate Certificate or Postgraduate Professional Development level (further information in the Programme Structure section, below).

You can exit at the end of 1-2 years with PgCert High Performance Computing with Data Science.

You can exit at the end of 2-4 years with PgDip High Performance Computing with Data Science.

You can exit at the end of 2 years with PgProfDev High Performance Computing with Data Science.

Entry Requirements

A UK 2:1 honours degree, or its international equivalent, in a relevant subject such as computer science and informatics, physics, mathematics, engineering, biology, chemistry and geosciences..

You must also be a competent programmer in at least one of C, C++, Python, Fortran, or Java.

Your application will also be considered if you don’t have formal programming training (for example, if you are primarily self-taught), or if you have a 2:2 honours degree with high marks in computational courses.

Start Date



Postgraduate Master's



Study Method

Distance and Flexible learning

Course Length

3-6 years


College of Science and Engineering



SCQF Level



Career Area

Computing and ICT

Career Sectors

Computer Skills

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