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Key information
DATA SOURCE : IDP Connect

Qualification type

MSc - Master of Science

Subject areas

Informatics Urban Studies

Course type

Taught

Course Summary

Urban informatics is the study of how rich behavioural data from cities and their citizens can be collected, analysed, understood, and communicated through computation. We seek to inform improvements that can increase the wellbeing of city residents, whether by government organisations or industries involved in providing services in cities. Our Urban Informatics MSc equips students with the technical, analytical, and communication skills required to conduct effective urban data analysis, with experience of detailed case study topics and the communication of results to effect change.

The first term provides foundation modules in core data science techniques, the theories underlying the study of cities, and ways to communicate analyses so as to affect policy- making. The second term focuses on data analysis for cities, providing insight into both spatial and network analysis as well as providing more depth on data mining techniques. In term two you will also take a specialised module exploring one aspect of city life, such as air pollution or mental health, in real depth and detail. This provides a testbed for the analysis techniques learnt, enabling students to develop confidence and experience with handling urban data. In the summer term you will also engage in a substantive individual project – connected to our research interests – tackling one of a range of urban informatics topics.

The MSc in Urban Informatics equips you for future opportunities within business, government, NGOs and the third sector, where expertise in using analytics and data science to solve urban problems is increasingly essential.

Different course options

Full time | Strand Campus | 1 year | SEP

Study mode

Full time

Duration

1 year

Start date

SEP

Modules

Network Data Analysis (15 Credits)
Telling Stories with Data (15 Credits)
Urban Informatics Individual Project (60 Credits)
Introduction to Urban Analytics (15 Credits)
Spatial Data Analysis (15 Credits)
Computer Programming for Data Scientists (15 Credits)
Data Mining (15 Credits)
Statistics for Data Analysis (15 Credits)

Tuition fees

UK fees
Course fees for UK / EU students

For this course (per year)

£9,990

Average for all Postgrad courses (per year)

£5,202

International fees
Course fees for non-UK / EU students

For this course (per year)

£25,500

Average for all Postgrad courses (per year)

£12,227

Entry requirements

Students should have an upper Second Class degree in Computer Science (or related disciplines). An Upper Second in a quantitative subject containing a substantial statistical component will be also be considered, or Geography where this includes a geocomputation component. A Lower Second class degree, or degree in a different quantitative discipline (e.g. Pure Maths, Physics, Mathematical Economics, Mathematical Psychology) may be permitted if the candidate has subsequent work experience in large-scale data analysis of at least 2 years duration. Students without First or Upper Second Class degree in Mathematical Statistics or Computer Science but having relevant post- graduate experience may be interviewed to assess their level of competency.