Master of Science in Spatial Data Science
Program Director (Spatial Sciences): John P. Wilson, PhD
Program Associate Director (Spatial Sciences): Susan H. Kamei, PhD
Program Co-Director (Data Science): Yolanda Gil, PhD
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. Students must be admitted by both 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.
- 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.
Students complete a core set of courses to provide a foundation in data science and spatial analysis, and choose 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.
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.
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.
A minimum of 32 units are required for completion of this degree.