MUSA Program Requirements
The Master of Urban Spatial Analytics (MUSA) degree requires the completion of a minimum of 9 course units (CUs) over one year of full-time study.
|
Requirement |
Course Units (CUs) |
Details |
|
MUSA Courses |
5.0 |
Required foundational courses in GIS, spatial analysis, programming (JavaScript/Python), spatial statistics, AI, deep learning, visualization, and geospatial cloud computing. |
|
Urban Content Electives |
2.0 |
Courses selected from urban planning, public health, transportation, housing, sustainability, real estate, or related fields. |
|
Open Elective |
1.0 |
Student’s choice — may deepen technical skills, expand urban policy expertise, or explore another related discipline. |
|
Practicum |
1.0 |
Culminating project solving a real-world urban challenge for an external client, integrating technical skills and urban context. |
|
Summer Bootcamp |
0.0 (non-credit) |
Two online pre-program workshop covering (1) GIS and R-based spatial analysis and (2) fundamentals of statistics to ensure all students start with a strong foundation. |
Typical Course Sequence
|
Fall Semester |
Spring Semester |
|
Spatial Statistics (MUSA Required) |
Geospatial Cloud Computing or Deep Learning with Python (MUSA) |
|
Public Policy Analytics (MUSA Required) |
Capstone or Practicum |
|
Programming for Geospatial Data Science: Python or JavaScript (MUSA) |
Urban Content Course #2 |
|
Urban Content Course #1 |
Open Elective or additional Urban Content |
|
Optional: MUSA elective (AI for Urban Sustainability or Modeling Geographic Space) |
Optional: MUSA elective (Communication Class) |
