EAR 400 - Machine Learning in Earth and Environmental Sciences
Syracuse University
Earth and Environmental Sciences
Data Sciences
R
a 3-credit course introducing machine learning in earth and environmental sciences
Course description
At this end of the course - Environmental Aqueous Geochemistry, students will be able to describe various concepts of programming, apply geospatial analysis and machine learning techniques to address real-world earth and environmental science questions, and interpret model outputs. The specific learning outcomes of the course are:
- Read and write data using standard formats
- Utilize modern coding environment R to perform scientific programing
- Wrangle and explore data effectively
- Perform advanced data visualization
- Write efficient code to perform earth and environmental science data manipulation and geospatial analysis
- Apply machine learning techniques to address real-world earth and environmental science questions
- Design and complete a project using real-world data
When is this taught?
EAR 400 is a newly developed course to be first offered in Spring 2025. Then I anticipate I will teach it in Spring every other year or even every year This course is taught in person.