DSCI 496M. Data Science for the Environment. 4 Credits.
This course equips students with practical skills to collaboratively and reproducibly analyze, visualize, summarize, and test hypotheses using key data types related to the environment. Participants will engage with spatial data (raster and vector), temporal data (e.g., climate records), species occurrence data, and species-interaction datasets. Through hands-on exercises, students will develop coding expertise to handle these datasets effectively within reproducible workflows. Multilisted with BI 496M.
Requisites: Prereq: one from DSCI 101, BI 430, BI 471, ERTH 418, GEOG 495.
Equivalent to: BI 496M