The interdisciplinary Graduate Certificate in Urban Informatics is offered through a collaboration between the the College of Social Sciences and Humanities’ School of Public Policy and Urban Affairs and the College of Computer and Information Sciences. The curriculum is comprised of the four foundational data analytics courses in urban informatics. The certificate enables students to obtain a specific set of tools for utilizing and presenting data on various aspects of city planning and policymaking, and to effectively communicate the potential of new initiatives. Certificate credits can be applied to the MS in Urban Informatics.
The Graduate Certificate in Urban Informatics is offered in a hybrid format*, a combination of online and on-campus instruction. This flexible format is designed to accommodate students’ busy schedules while providing opportunities to interact with faculty and classmates on campus and through discussion boards and other technology. Classes benefit from Northeastern’s signature experiential learning program, drawing on each student’s professional experiences to make real-world connections.
*Boston main campus only.
The Graduate Certificate in Urban Informatics is a 12-credit hour, 4-course program. Credits transfer to the MS in Urban Informatics program.
Big Data for Cities
The course focuses on investigating the city and its spatial, social, and economic dynamics through the lens of data and visual analytics. In this workshop class, the students work with large public datasets such as citizen call data, U.S. census data,, and other sources including social media to learn about visual and statistical methods for analyzing and applying the lessons from large urban data sets. Students should expect to gain a critical understanding of data-structures, collection methodologies, and their inherent biases; to acquire a methodical approach for rigorous analysis and inference; and to develop strategies for communicating the results in an urban policy setting.
Urban Theory and Science
This design/theory class focuses on urban infrastructural networks in the context of urban sensing and participatory technologies. The goal is to understand urban infrastructure as a complex socio-technical system that has to be approached from multiple perspectives – including social, political, ecological and cultural. Students will analyze a particular system (including communication, waste and sanitation, transportation), and develop concepts for its improvement. To inform the design process, the course offers a theoretical perspective on infrastructural studies with a focus on urban technologies, using key texts from the domain of Science and Technology Studies (STS), Ubiquitous Computing, Urban Interaction Design, and Urban Informatics. In all, students will gain insight into how scientific and technological ‘fixes’ for urban policy problems interact with social and political systems. As well, students will develop theoretically informed research projects based upon established research design strategies that lead them to the proposals for urban infrastructural improvements.
GIS for Urban Policy
This course provides basic spatial analytic skills and introduces students to some of the urban social scientific and policy questions that have been answered with these methods. It covers introductory concepts and tools in geographic information Systems (GIS) and database management through the use of proprietary and open source software packages. The course also introduces students to the process of developing and writing an original policy-oriented spatial research project with an urban social science focus. Through this project, students have the opportunity to combine the data science skills gained earlier in the program with spatial analytic techniques that are especially useful in urban-scale analyses.
Specialized Skills Course (Choose 1): Advanced Spatial Analysis of Urban Systems
This course builds on the skills developed in GIS for Urban Policy in order to give students advanced skills for analyzing urban systems (including social, built, and natural systems). Students complete a series of small-scale projects based upon current data and policy challenges within cities and focused on spatial statistical analysis, cartography, advanced modeling, spatial network analysis, and 3D visualization skills. Students will employ these skills to develop an original research project that analyzes how at least two systems (social, built, natural) interact within urban space. Students choose between this course and Dynamic Modeling for Environmental Investment and Policy Making.
Specialized Skills Course (Choose 1): Dynamic Modeling for Environmental Investment and Policy Making
This course introduces students to the theory, methods, and tools of dynamic modeling for policy and investment decision making with special focus on environmental issues. The course makes use of state-of-the-art computing methods to translate theory and concepts into executable models, and provides extensive hands-on modeling experience. Topics include discounting, intertemporal optimization, dynamic games, and treatment of uncertainty. Throughout this course, students learn to set up their own models of urban, economic and environmental systems; develop computer models that solve systems of simultaneous equations which may contain nonlinearities, time lags, and random variables; conduct sensitivity analyses of computer models; explore a system’s dynamics under a wide range of what-if scenarios; use dynamic modeling to guide their own research, organize available data, and streamline the collection of new data; use dynamic modeling to generate group consensus about the structure and behavior of nonlinear dynamic systems; and learn how to transfer insights and skills from one discipline to solve problems of another discipline. Students choose between this course and Advanced Spatial Analysis Urban Systems.