The study of cities necessarily spans many areas, sociological, cultural, technological, political, and so forth, and the areas of citizens’ lives that data analytics may help to improve are similarly broad, including health and wellbeing, transport, environment, crime, etc. CUSP London addresses this breadth by offering two complementary MSc programmes, each covering the fundamentals of urban informatics, but each with distinct emphases, making them suitable for applicants looking to develop different skills from their degree.

The programmes are:

MSc Urban Informatics – hosted at King’s College London

MSc Urban Analytics and Visualisation  – hosted at University of Warwick


Some elements offered are common across the two programmes:

  • Practical and analytical skills in urban data science to explore, visualise and make sense of city-scale spatial data
  • Local links with agency partners in large UK cities such as London and Birmingham for
  • Individual and group projects within which students can apply the skills they’ve learnt over the programme to a domain of interest
  • A London data dive including students from both programmes, plus those from CUSP in New York, tackling an urban problem using their data analytics skills in an exploratory way over a week

Each programme has a distinct set of emphases in learning strategy and topics covered. This does not mean that one programme excludes the aspects emphasised by the other, just that there is a different focus, allowing applicants to make an informed choice between programmes.

KCL’s MSc Urban Informatics emphasises the following:

  • Ensures grounding in core data science skills, in preparation for acquiring the cities-specific expertise required to solve urban challenges
  • Case-study driven, with specialist topic modules core to the programme
  • Focus on communicating results of analysis with effect on policy
  • Access to specialist expertise and data on urban health and well-being

UoW’s MSc Urban Analytics and Visualisation emphasises the following:

  • Develops interdisciplinary methodological skills, to understand cities and for solving urban challenges
  • Focus on the application of data analytics and visualization methods for understanding the social, economic and cultural dimensions of cities
  • Provides a breadth of options allowing students to select the path best matching their particular interests
  • Access to specialist expertise and data on urban culture, resilience and spatial analysis

2019/20 Student Projects: – 

Exciting interim update from a current student:

Trust, but verify – working with administrative data

The teaching and facilities are amazing at King’s but choosing CUSP London is way more than that,  I really feel like I’m part of the community that brings together people who are eager to learn and grow. The way that CUSP London is set up has made it really easy to meet and collaborate with people from partners of CUSP, since there are a variety of events happening in CUSP such as Data Dive, Coffee Catchup and Guest Seminars. I enjoyed my time at King’s and beyond the urban analytics knowledge and data science skill-set I acquired, I was able to boost a growth mindset which is needed for a career I’m truly passionate about.” – MSc Urban Informatics Student – Zhouyue

Examples of the Student Projects for MSc Urban Informatics at King’s College London 2018/19

  • Predicting response time performance for the London Ambulance Service
  • Geospatial analysis of psychosis risk factors and clinical outcomes
  • Extending an Agent-Based Model of Distance-Based School Allocation
  • Planning the Distribution of Charge Points for Electric Vehicles
  • Predicting building and land use attributes from street configuration, hierarchy, and other contextual factors
  • Geographical and Disciplinary Differences in Collaboration Networks
  • Modelling and geographic correlation analysis of calls to the London Ambulance Service related to unconsciousness
  • Liveable Streets
  • The role of environment and accessibility in suicidality
  • Predictive models on terrorism vulnerability with local climate