ENVST-325 Environmental Data Science

This course will focus on the application of statistical programming for big data associated with ongoing environmental issues. Students will gain experience in statistical programming throughout the entire data life cycle including data management and provenance, analysis, visualization, and communication. Students will learn the fundamentals of applying statistical modelling and machine learning for making predictions and inferences for environmental data. Students will also learn considerations of data science that are unique to environmental data including spatial, temporal, ethical, and justice concerns. Environmental topics will include climate change, pollution, natural disasters, and agricultural impacts.

Maximum Enrollment

15

Credits

1

Prerequisite

Must have taken ENVST 206 or an introductory statistics course in math or an applied discipline such as economics.