MSc Mathematics and Data Science

Overview

The field of Data Science has seen rapid growth in recent years, with vast amounts of data now being generated by major companies and service providers.

At the same time, it’s recognised that there’s a shortage of qualified analysts, both in the UK and globally, to make the most of this data. Crucially, there’s now a shortage of mathematics graduates with the data analysis skills needed to meet the demands of industry.

Yet, there is a recognised shortage of qualified analysts, both in the UK and globally, to make the most of this data. In particular, the demand is for graduates who can both manage the data (the computing skills), and analyse the data to extract patterns, build models and make predictions (the mathematics skills). It is only with these analytical skills can the full value of data be extracted.

The COVID-19 pandemic has shown the importance of combining Data Science and Mathematics, with governments around the world being guided by predictions from mathematical models. Our MSc is one of the first courses to link these two key areas, making it uniquely positioned to help you meet this demand.

The course will provide you with a strong foundation in the mathematical analysis of data-driven systems and help you develop your computing skills, including Artificial Intelligence and Machine Learning, to apply the techniques you learn on a large scale. You’ll learn the techniques used to approach data using computational analysis and understand the mathematics underpinning these techniques. The key outcome of this course is to ensure you are confident in your skills before you contunue your career. Students can also exit with PGCert and PGDip awards.

Course objectives

The aim of the course is to teach you the techniques for approaching data sets using computational analysis, and to help you understand the mathematics underpinning these techniques.

On successful completion of the MSc Mathematics and Data Science, you'll be able to:

• analyse and solve real-world problems using different mathematical and computational approaches
• expand mathematical methods to approach more complex problems
• be competant in industry-relevent programming languages, including R, Python and Matlab
• demonstrate skills in data analytics, machine learning and Artificial Intelligence (AI)
• analyse small and large-scale data sets using mathematical and computational approaches
• be confident in your own research and data science skills through real-life based projects