Master of Science in Spatial Informatics
Geospatial data accessibility, spatial decision support systems and geospatial problem solving environments are revolutionizing most industries and disciplines, including health care, marketing, social services, human security, education, environmental sustainability and transportation. Spatial informatics professionals draw upon engineering, computer science and spatial sciences principles to solve data-intensive, large-scale, location-based problems.
The USC Master of Science in Spatial Informatics provides students with the knowledge and skills to:
- Understand and contribute toward the significant technical and societal challenges created by large location-based data environments, including architecture, security, integrity, management, scalability, artificial intelligence topics and distribution
- Understand the principles and application of informatics and geographic information science (GIS), and the goals of enterprise information intelligence and analytics
- Utilize technical, engineering and GIS skills coupled with informatics capabilities to intelligently mine data to provide enterprise-centric solutions for diverse societal issues
Students complete a core set of courses to provide a foundation in information engineering, analysis and spatial thinking with their choice of electives to optimize preparation for their preferred career path and unique professional opportunities.
Students will understand the overall field of data analytics, the role of the analyst and/or data scientist and the domains where spatial informatics skills can be applied to critical organization missions. They will understand how data management, data visualization and artificial intelligence techniques (specifically data mining and machine learning) are critical to the spatial analysis process and how these can be applied to real world challenges. Throughout their coursework, students will assemble a digital portfolio of work product which is intended to help them demonstrate their capabilities and skills for the job market.
Applicants to this program are expected to have a previous degree in science, technology, engineering, math or a related social science with at least a 3.0 overall GPA and satisfactory GRE Test results. Programming experience or a strong math background are required for admission.
A minimum of 32 units with an overall cumulative GPA of at least 3.0 is required for the M.S. in Spatial Informatics. Students should consult with an academic adviser prior to registering for any classes. For course descriptions, please visit this page. To apply, please visit the this page.
Required Courses (6 courses \ 24 units):
- Foundation (8 units, both courses required):
- Spatial Core (8 units, both courses required):
- Informatics Core (8 units, both courses required):
Spatial and Informatics Elective Courses (8 units):
- Spatial Electives (4 units):
- Informatics Electives (4 units):
- CSCI587 Geospatial Information Management (4 units)*
- ENGR596 Internship in Engineering*** (1 unit)
- INF552 Machine Learning for Data Informatics (4 units)
- INF553 Foundations and Applications of Data Mining (4 units)
- INF554 Information Visualization (4 units)
- INF555 User Interface Design, Implementation and Testing (4 units)
- INF559 Introduction to Data Management (3 units)
*SSCI582 meets the CSCI585 prerequisite for CSCI587 and must be taken before it.
**SSCI596 may be taken in addition to one of the 4-unit SSCI elective courses, but SSCI596 by itself does not fulfill the Spatial Sciences elective requirement.
***ENGR596 may be taken in addition to one of the INF or CSCI elective courses, but ENGR596 by itself does not fulfill the Informatics elective requirement.
For questions please contact Lizsl A.De Leon (Director, Student Affairs)