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. Yet, there is a recognised shortage of qualified analysts, both in the UK and globally, to make the most of this data and to meet the demands of industry. 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. Launching in 2018, 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 focusses on the application rather than pure theory of mathematics and is assessed primarily through coursework, developing those skills which are in high demand by the data industry. The course will provide you with a strong foundation in the mathematical analysis of data-driven systems and help you develop your computing skills, from programming Python and R, to advanced techniques including Artificial Intelligence and Machine Learning, to applying the techniques you learn on a large scale. You will learn the techniques used to approach data and build models using computational analysis and understand the mathematics underpinning these techniques. Our graduates have gone on to work in financial institutions, major energy firms, sport and fitness, start-ups, NHS, Environmental agencies, the Scottish Government, as well as gone onto undertake PhDs in UK and overseas. Stirling is associated with The Data Lab, an Innovation Centre that aims to develop the data science talent and skills required by industry in Scotland. It facilitates industry involvement and collaboration, and provides funding and resources for students.
Statistical analysis techniques for small and large datasets; Developing models of real-life systems; Mathematical analysis of data networks, e.g. social media networks; Analytical and numerical optimisation approaches to real-life systems; Manipulating data and scripting in Python; Data analytics and machine learning; Cluster computing on Hadoop and Spark; Relational and NoSQL databases.
A minimum of a second class Honours degree, or equivalent, in either a mathematics (joint or single honours) or other numerate subject, e.g. physics. Other degrees will also be taken into account, if it can be shown that some mathematical study took place and you have taken and passed advanced mathematics modules in at least some of calculus, algebra, statistics and numerical analysis. Applicants without these formal qualifications but with significant and appropriate work/life experience are encouraged to apply.
Fees and funding
No fee information has been provided for this course
Additional fee information
For information on funding and scholarships, please see here: https://www.stir.ac.uk/study/fees-funding/postgraduate-loans-and-funding/
University of Stirling