Spatio-temporal Analytics and Big Data Mining MSc

Gain advanced understanding of GIScience, databases, spatial analysis, data mining, analytics and more, on this one-year MSc programme. You'll build the specialist expertise needed to analyse, represent, and model large and complex spatio-temporal datasets. This specialist MSc will train you to extract insights from large amounts of data to discover patterns and knowledge from spatio-temporal data. Teaching combines theory with extensive hands-on experience to cover the diverse facets of big data – from the principles of spatio-temporal analysis and computation guided by statistical and machine learning techniques, to space time data, parallel computing, system design, social media analysis, text mining, and programming. You'll apply your skills to real-world scenarios, to create models for social media listening, understand weather patterns, predict earthquakes, and determine global warming trends. You’ll also learn all about the ethical and social angles to big data that are needed in the working world. This “Bigger Picture” element will help you understand the context of your work, so you can go out and create and deliver projects that benefit both people and the planet. On top of learning practical skills from programming languages (R and Python) and scientific writing, there’s a big emphasis on developing transferable skills. These include communication, project management, and critical thinking – which, when coupled with your tech expertise, will make you highly sought after for roles in industries including data science, social media analysis, finance, health, telecoms, and urban planning. This programme is ideal if you want to elevate your expertise in big data to advance in a fulfilling career, or go on to further research. We welcome applications from recent graduates in engineering, architecture, physical or computational sciences, mathematics, earth sciences, physics or related fields, and from those with recent professional experience.

A minimum of an upper second-class UK Bachelor's degree in a relevant discipline (such as engineering, mathematics, computer science, environmental science, human or physical geography, geology, forestry, oceanography, or physics) or an overseas qualification of an equivalent standard. Applicants with relevant professional experience are also considered.