The following subjects are studied (this is a non-exhaustive list):

• Basics of Optimization
• Linear regression and the method of least-squares
• Maximum Likelihood Estimation
• Statistical Classification Techniques (Logistic Regression/Discriminant Analysis)
• Clustering (K-means/Model-based)
• Neural Networks
• Bias-Variance decomposition of prediction error and model selection
• Bagging and Boosting/Model averaging techniques
• Support Vector Machines

There will be a computer lab with R, a free software environment for statistical computing and graphics.

http://www.cs.uu.nl/education/vak/lfd