Master of Science in Environmental Data Science

Program Director (Data Science): Yolanda Gil, PhD

Program Co-Director (Environmental Studies): John Heidelberg, PhD

Program Associate Director (Environmental Studies): Jessica Dutton, PhD

The Master of Science in Environmental Data Science is an interdisciplinary program offered jointly between the USC Dornsife College of Letters, Arts and Sciences and the USC Viterbi School of Engineering.

Data science technologies can complement interdisciplinary analyses of complex environmental issues in the emerging field of environmental data science to address societal and research challenges in climate change, water and air pollution, policy analysis, terrestrial and aquatic ecosystem management, and biodiversity among others.

The USC Master of Science in Environmental Data Science will provide students with the knowledge and skills to:

  • Work at the intersection of interdisciplinary fields of environmental science and data science to ensure environmental sustainability and resilience
  • Leverage data to form and frame relevant questions in environmental management and sustainability, identify patterns, and make actionable insights to understand and protect Earth’s natural resources
  • Identify data needs to address environmental problems, and develop data science systems that access, integrate, and analyze the necessary data to create more integrated understanding of the challenges and potential solutions
  • Efficiently integrate new sources of data that reflect human processes to understand their impact in the environment and to design possible interventions to improve outcomes
  • Use data science techniques to gain new insights for environmental challenges

The program prepares students for a range of professional paths in research and environmental data management that aligns with skills requirements for positions in such areas as:

state and federal government natural resource regulation, academic research, environmental consultation and non-profit environmental advocacy, restoration planning, conservation and wildlife management, remote sensing specialists, and corporate responsibility and monitoring.

The curriculum is designed to be accessible to students with any background, including students with a public policy background and no computer science knowledge as well as students with a computer science background and no public policy knowledge.  Students with undergraduate degrees in computer science, engineering, science or mathematics will acquire the necessary knowledge to analyze health data with diverse sources and purposes, and can request to replace introductory data science courses with more advanced ones.  Students with undergraduate degrees in environmental studies, biology, Earth sciences, and related sciences will acquire formal and practical data science skills, and can request to substitute introductory courses in environmental studies with more advanced ones.  There is no requirement of prior knowledge of programming or computer science, as the curriculum is designed with special introductory courses that are accessible to students with diverse backgrounds.

Students complete a core set of courses to provide a foundation in data science and public policy, and choose electives to optimize their preparation for their preferred career path and unique professional opportunities. Students will learn a range of data science skills such as developing scalable data systems, using state-of-the-art software and infrastructure for data science, designing data analyses with statistical methods, applying machine learning and data mining techniques, designing effective visualizations, and working in multi-disciplinary data science teams.  Students will gain a foundation in the central theories, concepts and principles of natural sciences and how to leverage data to form and frame relevant questions in environmental management and sustainability, identify patterns, and make actionable insights to understand and protect Earth’s natural resources.  At the start of the program, students will be offered specific opportunities in problem-based learning in partnership with the USC Wrigley Institute for Environmental Studies.

Throughout their course work, students will assemble a digital portfolio that will allow help them demonstrate their capabilities and skills for the job market.  Students will also have ample opportunities to be involved in practical environmental data science projects on campus.  Upon graduation, students will have both foundational and practical skills for a successful career in environmental data science.

A minimum of 32 units are required for completion of this degree.