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 be a competent programmer in at least one of C, C++, Python, Fortran, or Java and should be familiar with mathematical concepts such as algebra, linear algebra and probability and statistics.

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 and/or additional relevant work experience.

Start Date

September, Flexible


Postgraduate Master's



Study Method

Distance and Flexible learning

Course Length

3-6 years


College of Science and Engineering



SCQF Level