— Environmental Data Science

Prerequisites & course information

Course Description: Programming with environmental data using R. Understanding data types, loops, branching and functions. Reproducible workflows and version control to import, organize, explore, analyze and visualize environmental data. Data science terminology and approaches. Common data sources used in environmental science and policy. Learning Activities: Lecture 2 hour(s), Laboratory 6 hour(s). Grade Mode: Letter. General Education: Science & Engineering (SE). Learning Activities: Lecture 2 hour(s), Laboratory 6 hour(s). Grade Mode: Letter. General Education: Science & Engineering (SE).