SMU Environmental Science

A good part of science work is handling data. Do you know what to do with data? If not, this would be a good course to take - ENVS 4432 Data Science in the Environment.

Data science, including skills such as database management, data manipulation, mapping, data visualization and interpretation, data ethics, coding, and statistical analysis, is increasingly important in environmental science. Students in this course work with ecological data collected in the field at the beginning of the course to develop skills in data science and learn to use the programming language R. Class sessions focus on active and hands-on learning.

Note: Data will be collected in the field on Monday (September 1) and Tuesday (September 2) (two 7.5 hour days) to allow analysis of the collected dataset throughout the semester and additionally allow students to gain field ecology skills. Classes 1.5 hrs. and lab 3 hrs. per week.

SMU Science

NEW FORMAT - Environmental Pattern Analysis (ENVS 4460)

Asynchronous lectures/Synchronous labs
Prerequisites: 60 credit hours include one of ENVS 2310, ENVS 2400, and GEOG 2306

Students focus on theory and practical methods for characterizing the structural and dynamic features relating to environmental systems. Practical applications include environmental systems related to rivers, lakes, coastal areas, fisheries, forests, ecosystems, underground mineral distribution, atmospheric variables (wind, temperature), and pollution. Classes 3 hrs. and lab 3 hrs. per week.

SMU Science