ES 445 Environmental Data Science
This course provides advanced experience in collecting, organizing, analyzing, and visualizing data relevant to environmental science. Types of data will include meteorological, spatial, geochemical, biodiversity, and socioeconomic. Analyses appropriate to those types of data will be conducted by way of command-line coding and GUI operations in the R, Python, and QGIS environments. This work will culminate in the drafting, revision, and presentation of the products of these analyses. Three hours lecture, three hours lab weekly. Prerequisite: CHEM 221 or instructor permission. Four credit hours.