The Master of Science in Urban Informatics (MSUI) degree couples comprehensive data analytics skills with an understanding of the big questions faced by cities in the 21st-century city. This cutting-edge program is built upon a unique cross-college initiative, which offers comprehensive state-of-the-art training in the core skills of data analytics—including quantitative analysis, data mining, machine learning, and data visualization. Urban informatics students supplement training in these foundational skills with a specialized sequence of courses that address how data and technology are being used to tackle key social, infrastructural, and environmental challenges.
By combining a theoretically informed perspective of cities with advanced skills in accessing, managing, analyzing, and communicating insights from large complex, datasets, graduates are a part of the next wave of urban professionals ready to lead in the public, private, and nonprofit sectors. Given the continuous growth in urban data and technology, these professionals are essential to shaping the future of urban areas around the globe.
This program provides a uniquely integrated urban and informatics degree with a substantial experiential education component. The focus throughout is on practical application, and students have multiple opportunities to apply what they are learning.
The master's program offers an optional cooperative education experience (co-op) to eligible students. Co-op education is central to both the Northeastern experience and to the College of Social Sciences and Humanities experiential liberal arts framework. Northeastern’s signature co-op ecosystem provides qualified master's students with six-month work experiences in businesses, nonprofits, and government agencies across the United States. Graduate students take their work from campus learning spaces, apply their knowledge outside of the classroom, and then bring knowledge and skills gained in community learning spaces back to our campus learning spaces during the cocurricular experiential integration course.
Please review the tuition and fee page as credit costs differ depending on the college in which the course resides.
CSSH Graduate Programs General Regulations
Academic Standing/Progress
Students in the program are monitored for academic progress. Those students whose grade-point average (GPA) falls below a 3.000 are notified by and meet with the director of academic programs. They are counseled that if their GPA does not rise to a 3.000 or higher, they run the risk of not graduating and are advised on strategies for improvement. For all other matters, please see the Universitywide Academic Policies and Procedures.
Complete all courses and requirements listed below unless otherwise indicated.
Core Requirements
Course List | Code | Title | Hours |
| DA 5020 | Collecting, Storing, and Retrieving Data | 4 |
| or DA 5030 | Introduction to Data Mining/Machine Learning |
| or PPUA 7237 | Advanced Spatial Analysis of Urban Systems |
| INSH 5301 | Introduction to Computational Statistics | 4 |
| INSH 5302 | Information Design and Visual Analytics | 4 |
| PPUA 5263 | Geographic Information Systems for Urban and Regional Policy | 4 |
| PPUA 5262 | Big Data for Cities | 4 |
Optional Co-op Experience
Course List | Code | Title | Hours |
INSH 6964
and EESH 6000 | Co-op Work Experience
and Professional Development for Co-op | 0 |
Electives
Course List | Code | Title | Hours |
| 13 |
| Urban Theory and Science | |
| Ecological Economics | |
| Economic Analysis for Policy and Planning | |
| Practicum | |
| Capstone in Public Policy and Urban Affairs |
| Urban Informatics Portfolio | |
Program Credit/GPA Requirements
33 total semester hours required
Minimum 3.000 GPA required
