Machine Learning in Environmental Science

3 credits · Nicholas School of Environment

This course provides an introduction to machine learning (ML) techniques with a focus on applications in environmental and climate science. Students will learn fundamental ML concepts and apply them to real-world environmental challenges, such as climate modeling, remote sensing analysis, and ecosystem management. The course emphasizes hands-on experience, using Python-based ML libraries such as scikit-learn and Keras to analyze environmental datasets.