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The application of data science to complex environmental problems has become increasingly important in evaluating large-scale environmental challenges. Data science technologies complement interdisciplinary analyses of complex environmental issues ranging over many topics such as climate change, water and air pollution, policy analysis, terrestrial and aquatic ecosystem management, biodiversity and many others. The curriculum is designed to prepare individuals to develop and use sophisticated analytical and computer-based methods to assess and protect the Earth’s natural resources. The USC Masters of Science in Environmental Data Science would provide students with the knowledge and skills to:
- Work at the intersection of interdisciplinary fields of environmental science and data science
- 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
- Understand the use of emerging technologies in data science and their application to environmental problems
- Efficiently integrate data science approaches and systems to analyze real-world environmental data
Students will gain a foundation in the central theories, concepts and principles of natural sciences while training them with data science skills that can be used for environmental problems.
The curriculum is designed to be accessible to students with any background, including students with an environmental sciences background and no computer science knowledge as well as students with a computer science knowledge and no environmental studies background. Students will acquire the necessary skills to analyze environmental data in a variety of contexts. Those with natural science backgrounds will acquire the necessary data science skills to exploit environmental data. Students with a computer science background will learn about the specific characteristics and frameworks necessary to evaluate environmental data from diverse sources and apply related analytics toward well-formulated environmental questions. At the start of the program, students will be offered specific opportunities in problems-based learning in partnership with the Wrigley Institute for Environmental Studies.
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 M.Sc. in Environmental Data Science is offered jointly by the USC Dornsife College of Letters, Arts, and Sciences Environmental Studies Program and the USC Viterbi School of Engineering Data Science Program.
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