PREREQUISITES:
- MATH140
DESCRIPTION:
This is a comprehensive course designed to prepare undergraduate and graduate students for applying machine learning techniques to solve real-world problems in Earth science. It emphasizes practical solution implementation, providing students with essential handson experience using the most popular open-source analytics tools based on Python, a general-purpose programming language. The course works through all steps in machine learning, from problem specification, data analytics to analytical solution, and applies advanced statistical and analytical algorithms to uncover hidden data relationships andtransform them into predictive understanding or decision support.
This course has two overarching components: first, students will learn how to program with Python in using Scikit-learn and other major analytics toolkits; second, students will learn how to apply these machine learning tools with basic knowledge of statistics to discover robust signals underlying actual big data in the Earth science domain. These two components will be bridged with homework plus exercise assignments utilizing both analytical and programming skills to examine and interpret Earth’s climate/environment variations. These skills learned can be more generally applied to other scientific data with variations in time, space or feature.