AREC380
Data Science for Environmental and Resource Economics
Prerequisite: AREC240, AREC241, AREC250, or ECON200. An introduction to principles of data science using modern, open source software tools with applications to important problems in environmental, energy and resource economics. Topics include data wrangling, exploratory data analysis and visualization, modeling, forecasting, practices for reproducible research, and communication of results.
Fall 2024
6 reviews
Average rating:
3.33
Fall 2023
6 reviews
Average rating:
3.33
Spring 2023
6 reviews
Average rating:
3.33
Past Semesters
6 reviews
Average rating:
3.33
* "W"s are considered to be 0.0 quality points. "Other" grades are not factored into GPA calculation. Grade data not guaranteed to be correct.