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Data Analytics in R – Advanced Topics

Veranstaltungsdaten

Do you already work with R occasionally to 1) process and manipulate your data, 2) conduct statistical analysis or 3) 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 be able to use fast and intuitive methods to bring (big) data into shape by using popular packages like data.table
  or 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 and become familiar with more effective loop structures.
• You will be able to apply some advanced programming principles and techniques (e.g. functional programming, debugging)
  to boost the performance of your code.
• You will know how to use the full potential of RStudio projects and get an overview on important packages for data analytics
  (e.g. DataExplorer, stringr, forcats, caret).

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

November 14, 2020, 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 October 30, 2020
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.

This course is expected to take place on february 20, 2020 as an online course.