This course delves into machine learning and data mining techniques tailored for environmental challenges, using data from ground observations, satellites, and models. Covering both supervised and unsupervised methods, students will learn to analyze and interpret complex environmental data through hands-on exercises and projects. By the end, participants will possess the skills to apply these techniques to real-world environmental issues and contribute to resource preservation. The class materials were inspired by SYS6018, a course taught by Dr. Michael D. Porter at the University of Virginia.