Program

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Course Contents: The focus of this course is on advanced R topics, such as:

  • ggplot2
  • spatial vis
  • RCPP
  • data.table
  • avoiding loops in functions
  • R packaging, incl. Roxygen and version control
  • reproducible research with knitr, pandoc, Rmarkdown, Latex
  • Visualization: ggplot2 and shiny
  • Neural nets (deep learning) with MXNet and TensorFlow
  • Webcrawling and API’s with xml2 and rvest
  • Tidyverse (dplyr, purrr, readr, %>%, etc.) with consistent API, functional programming and typing in R
  • High-performance computing and big data, with C++ and spark
  • Robust  and multivariate methods in R
  • Statistical methods for metabolomics

(Almost) Every session is accomplished with practical examples – please bring your laptop with you.

Course Schedule:

  • Monday, September 25, 2017: 09:00 – 18:00: to be announced
  • Tuesday, September 26, 2017: 09:00 – 18:00: to be announced
  • Wednesday, September 27, 2017: 09:00 – 13:00: to be announced