Stochastical Modelling and Computional Data Science

Heriot-Watt University


Edinburgh Campus


This programme is for students looking to gain mathematical, computational, and analytical skills that enable them to analyse large data sets to support decisions and conclusions under uncertainty. This is an area of science and technology that is attracting significant research efforts and that will continue to grow for the foreseeable future, as more and more industries adopt data-driven and data-centric approaches.

This MSc is a new programme designed in collaboration between both the School of Mathematical and Computer Sciences and the School of Engineering and Physical Sciences. It consists of two coherent and distinctive streams; The first and more theoretical stream will build the student knowledge on the stochastic aspects of data science (Stream SM : Stochastic Modelling and data science) The second and more applied stream will build the student knowledge on the computational aspects and engineering applications (Stream CDSE : Computational Data Science and Engineering).

It is important to note that students will only be able to study one of these streams. For more information on the streams choosing from:

Stochastic Modelling and Data Science or Computational Data Science and Engineering

Entry Requirements

A good Honours degree (first or second class), or its non-UK equivalent, from a recognised British or overseas university. The degree can be from various disciplines, ranging from mathematics and engineering, to physics and computer science, provided that it provides a solid background in mathematics.

Start Date



Postgraduate Master's



Study Method

Full time

Course Length

12 months


School of Mathematical and Computer Sciences


Computer Science

SCQF Level



Career Sectors


Chemistry and Materials Science

Food Science and Technology

Mathematics and Statistics


Science General