Environmental Data Science (MS)

datascience.usc.edu

Dornsife College of Letters, Arts and Sciences, Environmental Studies
Viterbi School of Engineering, Computer Science/Data Science

Program Director (Data Science): Yolanda Gil, PhD
Program Co-Director (Environmental Studies): John Heidelberg, PhD

A minimum of 32 units with an overall cumulative GPA of at least 3.0 is required. Students can complete the degree in either three or four semesters, depending on whether they take courses in the summer.

The proposed curriculum relies on existing courses currently taught at USC. The degree will consist of a set of required core and elective courses in both data science and course related to environmental studies. On the data science side, students will learn about artificial intelligence (particularly machine learning and semantic data models), data management, privacy, and data visualization. Courses in environmental studies will provide a foundation in natural resource dynamics and management, as well as today’s most pressing environmental challenges. Courses in environmental studies will provide a foundation in natural resource dynamics and management, as well as today’s most pressing environmental challenges. Capstone courses based on real-world projects will enable students to acquire practical experience applying data science to address particular environmental problems of interest.

Students with requisite programming knowledge are allowed to test out of DSCI 510 . An entrance exam will be held at three time periods: two weeks before the start of the semester, one week before the start of the semester, and during the first week of the semester. Students who pass the exam will be allowed to skip DSCI 510 , and may replace that with an elective.

For Admission Requirements, refer to Viterbi Graduate Degrees and Requirements .