The M.Sc. in Environmental Data Science at USC combines data science methods with environmental science to help you analyze real-world environmental problems. You’ll learn to work with large datasets, spatial data, and risk models while applying these skills to sustainability and environmental decision-making.
The Master of Science in Environmental Data Science at the University of Southern California equips students with the skills necessary to address pressing environmental challenges through data-driven solutions. This program combines the principles of data science with environmental science, enabling students to analyze complex datasets and apply their findings to promote sustainability and informed decision-making in environmental contexts.
The curriculum is designed to provide a comprehensive understanding of both data science techniques and their applications in environmental settings. The program typically spans 12 months, comprising core and elective courses:
Core coursework includes:
Electives: You will select two elective courses (totaling 8 units) from a list of approved offerings to deepen your expertise in areas of interest.
Capstone/thesis: Clarification on whether a thesis, capstone project, or non-thesis option is required for program completion should be confirmed with the university.
Specific academic prerequisites, including GRE, GMAT, or GPA requirements, are not publicly detailed for this program. Prospective students are encouraged to verify any additional entry requirements directly with the university.
Graduates of the M.Sc. in Environmental Data Science can expect to find diverse career opportunities in various sectors, including government agencies, non-profit organizations, and private industry. With expertise in data analysis and environmental science, alumni will be well-equipped to contribute to sustainability efforts and inform policy decisions that address environmental issues.
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