MSc Programme

Large-scale Data

The MSc Programme leverages cities such as Birmingham, London and New York as living laboratories and the strength of our academic and industrial partnerships to create a unique data-driven educational experience.

The goal of WISC’s MSc Education Proramme is to provide students with the ability to use large-scale data to understand and address real-world challenges in the urban context.

MSc in Communications and Information Engineering: This new flagship Warwick-based MSc teaches a unique combination of electronic engineering and data analytics, with the aim of applying classroom knowledge to real-world challenges in the urban context.

MSc in Data Analytics: The Warwick MSc in Data Analytics is a new course that taps into the pulse of contemporary computer science. The knowledge taught is aimed at addressing real-world challenges related to big data analysis, informatics and urban science. 

MSc in Urban Informatics and Analytics: This new interdisciplinary MSc responds to the demand for specialists in urban science with both theoretical understanding and practical analytic skills. It provides the training to critically engage with urban and social data, allowing a deeper understanding of the science of cities and how one can utilise that knowledge to make cities better and safer places to live.

All courses have a unique international flavour. When taken as part of the EPSRC CDT, they are operated as part of Warwick’s collaboration with CUSP and students will have the opportunity to participate in practical industry- and city-related projects in London and New York.

Course Structure

MSc in Communications and Information Engineering

The course comprises leading electronic engineering and computing modules, including: communication networks, system modelling and simulation, advanced wireless systems, data analytics and signal processing. Coupled with these are urban science modules. The taught component is followed by a dissertation project in the third term, which offers the opportunity to apply the knowledge to urban challenges with industrial and civil partners.

MSc IN Data analytics

The course comprises a choice of cutting-edge computer science modules, including: data analytics, optimisation, data mining, machine learning, and wireless sensor networks. Students also have the opportunity to undertake several optional modules from topics including computing security, micro-sensor/systems technology and dynamic web-based systems. The dissertation project in the third term is typically undertaken with industry or city partners and allows students to gain experience of practical, multi-disciplinary research.

MSc IN urban informatics & ANALYTICS

The course comprises core modules on urban data and urban science, as well as a selection of leading modules in computer science (including data analytics, data mining and social informatics), quantitative social sciences (including complexity, big data, quantitative methods) and digital culture (including concepts of digital, digital objects, digital methods).  The dissertation project in the third term builds on these modules, offering the apparatus to transform city-scale data into knowledge, capitalizing on emerging developments in big data and in interdisciplinary solutions to tackle the world's urban challenges.

All courses are designed so that they can be taken as part of the EPSRC CDT in Urban Science; those students on this stream will have the opportunity to conduct projects in collaboration with students in New York. The CDT variants begin with a week-long cohort building programme and immersion in the dynamics of city agencies, city operations, and the CUSP intellectual community. Students are also required to complete an experiential, London-based, week-long Data Dive, in which they will work in multidisciplinary teams to solve a real-world data-science problem facing a city agency or industry partner. Students will collect and analyse data, formulate and test solutions, and devise a solution strategy. The project is an invaluable opportunity to contribute to high-impact research leading to improvements in urban data science across the globe.