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The Urban Spatial Science MSc equips students with a multidisciplinary, critical lens for analysing and shaping global urban resilience and sustainability. You’ll gain expertise in data analytics, machine learning (ML), remote sensing, and reproducible research - tools essential for understanding, monitoring and improving cities around the world. The Urban Spatial Science MSc delves into the theoretical, social, and scientific underpinnings of the modern built environment through a geospatial, data-centric approach. This Master's course emphasises a hands-on understanding of advanced technical and methodological practices in urban analytics and data-driven decision-making. You will gain expertise in mathematical, statistical, and simulation modelling computer programming spatial analysis and data visualisation. These practical skills are reinforced by broad theoretical perspectives covering demographics, economics, urban form and function, network interactions and complexity, governance and policy, planning, and urban science. At The Bartlett Centre for Advanced Spatial Analysis (CASA), students can tailor their learning through optional Term 2 pathways designed to guide them through the wide range of available modules. These pathways reflect CASA’s research strengths and are organised around four key themes: Big Data Smart Cities and Urban Policy Modelling and Simulation and Data Visualisation. In Term 1, students build a strong foundation in core concepts of urban spatial science, while Term 2 offers opportunities for deeper, specialised study. The course is deliberately interdisciplinary, drawing on expertise from geography, urban planning, computer science, physics, and the arts and humanities. Graduates of the Urban Spatial Science MSc emerge proficient in coding, data-informed urban analytics, and with a critical understanding of the limits of technology-driven ‘solutionism’. This enables them to be both technically skilled and critically reflective – able to look past the hype around smart cities, urban data science and urban science, and discern real insights. We are looking for students interested in the intersection of cities and the environment, with data science, spatial or geographic data science, and computational methods. There is no required academic background, but students with the critically informed perspectives provided by architecture, planning or geography degrees would be particularly suited to the course. We welcome applicants at any stage of their career. This programme is also available on a modular (flexible) basis, with a duration of 5 calendar years. The Degree Apprenticeship (DA) route is available with 3 academic years duration. It allows an Apprentice to study for a degree in Urban Spatial Science MSc, while continuing with employment. The degree is made up of eight taught modules, one research module and an End Point Assessment (EPA) totalling 180 credits.
