Predictive Modelling and Scientific Computing

Entry requirements

A minimum 2:1 undergraduate UK Honours degree or equivalent international qualification, in an engineering, physical sciences or mathematical subject.

Please note that applicants will need post A2 Level (or equivalent) knowledge in Mathematics, covering topics such as linear algebra, calculus and analysis, including differential equations, as well as probability and statistics. This could be gained through mathematics modules taken as part of an undergraduate course. It is expected that candidates have a good understanding of these topics at the start of their MSc studies. Self-study resources and a self-assessment test covering these skills is provided at https://warwick.ac.uk/fac/sci/wcpm/pmsc/mathsinduction.

You can see how your current degree score or GPA equates to the British system in our Study pages in the Equivalent scores table.

We are willing to consider applications from students with lower qualifications on a case-by-case basis, particularly when the applicant can evidence relevant employment, practical experience or strong performance in undergraduate modules related to their proposed postgraduate course of study.

Months of entry

September

Course content

Predictive Modelling is a fusion of mathematical modelling, machine learning and scientific computing, providing a powerful new way of thinking about how to model complex systems and improve technology and design.

Enhancements in computer processing power and access to ‘Big Data’ have led to a growth in the number of applications of predictive modelling into areas as diverse as environmental science, energy, healthcare, materials engineering, food science and geology.

Our MSc in Predictive Modelling and Scientific Computing builds on our world-leading research at the Warwick Centre for Predictive Modelling. The course educates future specialists in computational science and engineering, building on students’ existing programming skills and equipping them to apply appropriate computational techniques to understand, define and develop solutions to a range of science and engineering problems, including those of national and global importance.

This course will equip graduates for further study in areas of critical science and technological significance, or for employment in a broad range of data-intensive industries where modelling, design and decision making under uncertainties is important. We have strong links with a range of potential employers.

The MSc can be studied part-time over two years to suit those in employment. PG Diploma, Certificate and Award options are also available for those who would like to take a subset of modules.