See the Teaching methods section.
Introductory course to Data Science with applications in the R programming environment. Special focus is put on understanding of basic practical programming in R, covering model evaluation, memorization methods, advanced regression techniques, and training variance reduction.
The Data Science with R I course will be followed by Data Science with R II covering clustering, text mining, support vector machines, neural networks, and networks.