Handbook

This course is a graduate level overview of the applications of data science in an environmental context. Although applications and motivations will be drawn primarily from the ocean, atmospheric and climate sciences, the material covered will apply generally across various environmental and non-environmental science and industry areas.  A key distinction between this course and other data science offerings within the School of Mathematics and Statistics is an emphasis on practical real-world problems. These include practical approaches to data handling and quality control, consideration of real world examples of good and bad data science practice, the application of various statistical methods to real world data sets, the integration of statistical approaches with physically based forecast methods, and a project component involving independent exploration and exposition of cutting edge machine learning methods.