Advanced Programming in R

Do you already work with R occasionally to:

• Perform manipulation and follow-up processing of your data?
• Conduct statistical analysis beyond the scope of basic spreadsheet applications?
• Visualize the results derived therefrom in preparation for meaningful publications?

If the answer to at least one of these questions is “yes” and you want to make your R workflows more efficient, then this advanced R course could be for you!

Intended Learning Outcomes

• You will have an overview of various methods to bring (big) data into shape (e.g., by using popular packages such as data.table and dplyr).
• You will be able to create publication-quality graphics from only a few lines of code.
• You will be able to speed up your workflow using parallelization.
• You will be familiar with the use of effective loop structures beyond the scope of regular—and very slow!—for-loop constructs by including the parallelizing of computationally demanding tasks and utilizing the extensive connectivity between R and C++.
• You will be able to use the principles of functional programming to boost the performance of your functions.
• You will know how to use the full potential of R Studio projects.

Didactic Methods

Presentation, practical exercises, trainer input

Requirements 

Basic familiarity with R is required. You are further requested to bring a laptop with the latest versions of R, RStudio, and Git installed for use in the workshop. If you are using Windows, Rtools should to be installed; if you are a macOS user, install Xcode. Should you have technical questions, the instructors will be happy to provide installation assistance.
Proficiency in English at the B2 level of competency is required.

Date

September 28, 2019, 9 am–5 pm

Target group

Doctoral candidates and postdocs from all disciplines

Modalities

Maximum number of 10 participants
Internal 25 EUR
External 75 EUR

Registration

At mara.lnw@uni-marburg.de, deadline September 13, 2019
We kindly ask you to confirm your registration to make it binding. You may cancel your registration up to twelve days before the beginning of the course without providing specific reasons. Thereafter, you will be required to pay the attendance fee even if you do not attend the course.

Referierende

Dr. Matthias Duschl,
Dr. Daniel Lee

Veranstalter

MArburg University Research Academy (MARA)
Doctoral Program for Life and Natural Sciences