Max Planck Gesellschaft
Max Planck Gesellschaft

R course: Advanced modules

Category: Skill course
Credit points: 0.2 per day

On this page... (hide)

  1.   1.  Concept
  2.   2.  Place and time
  3.   3.  What you need to prepare
  4.   4.  Agenda
    1.   4.1  The Tidyverse
    2.   4.2  Programming
    3.   4.3  Speeding up your computation
  5.   5.  Registration
  6.   6.  Participants

1.  Concept

This modular seminar addresses everybody who is interested in improving existing R skills.

There will be

  • a little theory
  • focus on technical aspects (not on interpretation)
  • time for questions and answers
  • hands-on training based on the requests you write in the comment field of the registration form. Feel free to approach us with your data

Prerequisites: Basic knowledge of a language of scientific computing: R, Matlab (exercises will be in R) which are taught in the course 'R - The basics'

Lecturer: Thomas Wutzler, Nora Linscheid, David Martini, Daniel Pabon

2.  Place and time

  • When? September 14-16, 2020, start: 9:30 am and 13:30 pm
  • Where? MPI for Biogeochemistry, lecture hall


More R… Here is a list of useful online resources to accelerate your progress.

3.  What you need to prepare

Please make sure that a recent version of R and RStudio is running on your laptop.
You can download the most recent version here: http://www.r-project.org/

RStudio is a new open-source integrated development environment that runs on all platforms. It nicely combines console, script editor, working directory, plots etc. into a an uncluttered layout that you can easily navigate. You need to have R installed before you can use RStudio as a development environment.

Please also make sure that you can access the internet via WLAN (BGC-users, if you have a BGC-account; BGC-guests, if you don't have an account)

Course material are avaialable on owncloud

4.  Agenda

4.1  The Tidyverse

  • get data in the right shape using tidyr (90 min)
  • data science using dplyr (85 min)
  • working with subsets of data using nest and map (30min)
  • graphically explore datasets using ggplot

4.2  Programming

  • Organizing your code (100 min)
    • Writing R-packages
    • Documentation using inlinedocs
    • Locating bugs: Debugging
    • R Notebook

4.3  Speeding up your computation

  • locating bottlenecks
  • vectorizing
  • linking to low level code (examples C and C++)
  • parallel computing with the parallel package

5.  Registration

Register here by August 17, 2020.

6.  Participants

COVID-19 update (August 3, 2020): the current infection protection concept states that 16 persons are allowed to be inside the lecture hall without wearing a face mask. Due to the this number of participants is now limited to 12 (plus 4 lecturers). Please note that our infection protection plan is based on the one of the City of Jena, which will be updated at the end of August. Changes might occure.



This page was last modified on August 05, 2020, at 02:42 PM

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