The goals of this course are twofold: 1) providing a working knowledge of basic data science methods used for temporal and spatial analysis of atmospheric and oceanic data, to turn the data into clear insights via a computer program, 2) develop skills to work in a group and explain data science techniques to an audience with a broad range of expertise. The course covers: probability distributions and statistical indices; hypothesis testing; linear and multilinear regression; an intro to machine learning; an intro to Gaussian processes. This �learning-by-doing� course is recommended for senior level students. Formerly offered as a special topics course.
