Prerequisite: MATH115 or higher, GEOL120 or GEOL100; Junior Standing; Experience in computer programming.

How can we tell if a landform is a volcano or an impact crater, if a seismic signal is an earthquake or noise, if two dinosaurs are related to one another, if a given township contain critical minerals, and if a flood event took place last week in Maryland? In each case, the answer involves classifying geoscientific datasets. Increasingly, machine learning techniques are essential in tackling these challenges. This course will introduce you to classification and its associated methods, such as clustering, graphs, and neural networks. You'll engage in hands-on analysis of real-world datasets, discuss key publications and applications, and learn to use Python programming to solve these classification problems.