- Program Overview
- Application Information
- Tuition & Fees
- Career Outcomes
- DEN@Viterbi - Online Delivery
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As of September 7, 2021, the GRE exam is not required.
The Master of Science in Spatial Data Science is a cross-disciplinary joint degree program offered by the Viterbi School of Engineering and the Dornsife College of Letters, Arts and Sciences.
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 data science 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 Data Science 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 their architecture, security, integrity, management and scalability;
- Understand how spatial data can be acquired and used to support various forms of analysis, modeling and geo-visualization in large data environments; and
- Understand how artificial intelligence, machine learning, and data mining can be used to augment the typical geographic information science (GIS) concepts and workflows to intelligently mine data to provide enterprise-centric solutions for a variety of societal challenges and issues spanning the public, private and not-for-profit sectors.
Upon graduation, students will have not only data science skills but will be uniquely qualified to lead data science teams in companies and organizations working with geolocated information, conducting data analytics in startups and tech companies with location-based data, and getting involved with emerging technologies revolving around spatial data.
Students complete a core set of courses to provide a foundation in information engineering, spatial analysis and 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 science, the role of the analyst and/or data scientist and the domains where spatial data science 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 course work, students will assemble a digital portfolio of work product that 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 at least a year of calculus is required for admission.
The curriculum is designed to be accessible to students with any background, including students with a spatial sciences background and no computer science knowledge as well as students with a computer science background and no spatial sciences knowledge. Students with undergraduate degrees in computer science, engineering, science or mathematics will acquire the necessary knowledge of spatial sciences through the curriculum, and can request to replace introductory data science courses with more advanced ones. Students with undergraduate degrees in spatial sciences, geography, or social sciences will acquire formal and practical data science skills, and can request to substitute introductory courses in spatial sciences with more advanced ones.
A minimum of 32 units with an overall cumulative GPA of at least 3.0 is required for the Master of Science in Spatial Data Science. Students should consult with an academic adviser prior to registering for any classes. For course descriptions, please visit this page. To apply, please visit this page.
International Students: This program is eligible for the OPT STEM extension.
Please Note: Requirements for graduation, course offerings, course availability, track offerings, and any other degree requirements are subject to change. Students should consult with an academic advisor prior to registering for any classes.
- A minimum of 32 units is required for the MS in Spatial Informatics
- A minimum cumulative GPA of 3.0 is required for graduation
Published on July 6th, 2017
Last updated on September 8th, 2021