LFU:online

Be able to apply appropriate tools from  a toolbox full of modern statistical methods to problems in atmospheric and cryospheric sciences.

What is statistical learning?

The bare essentials of probability

Linear regression

Classification

Resampling methods

(Linear) model selection and regularization

Splines and generalized additive models

Trees, forests, and boosting

Unsupervised learning: principal component analysis and clustering

Deep learning

blended learning: screencasts and slides with short quizzes for personal feedback; applying material from screencasts to concrete problems (at home) and discussing them in class

quizzes, homework, final exam

James et al.: An Introduction to Statistical Learning

Hastie and Tibshirani: The Elements of Statistical Learning

D.S. Wilks: Statistical Methods in the Atmospheric Sciences

in English