| Title | Time | Room | Teacher |
|---|---|---|---|
| R for Data Science | 15.11.2023 09:00 - 12:00 (Wed) | TUM Graduate School: Boltzmannstraße 17, 85748 Garching bei München, Raum E003 | Dr. Stephan Haug |
| R for Data Science | 22.11.2023 09:00 - 12:00 (Wed) | online | Dr. Stephan Haug |
| R for Data Science | 06.12.2023 09:00 - 12:00 (Wed) | online | Dr. Stephan Haug |
| R for Data Science | 13.12.2023 09:00 - 12:00 (Wed) | online | Dr. Stephan Haug |
| R for Data Science | 20.12.2023 09:00 - 12:00 (Wed) | online | Dr. Stephan Haug |
Keywords:
R, data management, visualisations, tidyverse
Course Description:
In this learning-by-doing course, the participants will be introduced to how to get started in R. In particular, the course will give a guide into the tidyverse, a collection of R packages designed for data science. After introducing each topic, the participants will work on hands-on exercises.
Course aims:
- Being able to use the base R system
- Know the options available in the tidyverse
- Being able to do data management steps using dplyr
- Being able to create visualisations using ggplot2
- Know how to import data with readr
Teaching methods:
Presentation of topics, Hands-on exercises sessions
This course fits doctoral candidates in the following phase:
At the beginning of the doctorate │ during the doctorate
Participation requirements:
None.
Technical requirements:
Please bring your laptop.
Course preparation:
- install R from http://www.r-project.org
- install RStudio from http://www.rstudio.com
- check if you are able to install add-on packages by installing the (collection of) package(s) tidyverse
Additional information:
None.
What participants say about this course:
- Hands on course, lots of possibilities for exercising and learning by doing, very good support of the lecturer.
- The individual tasks to solve were helpful to learn and internalize the learned and learn some new tricks.
- The exercises were very useful and the course had a good set-up in general (room, small group, teacher helping with small bugs straight away).
Category:
Fachübergreifende Veranstaltung
Event type:
Seminar/Workshop
Organizer:
Graduate School Geschäftsstelle
Responsibility for event:
Hauptverantwortung
Format:
Hybrid
Course Language:
EN
Course Capacity (Max):
10
Course capacity (Min):
1
Duration in hours:
15
Financial contribution:
40 Euro
Trainer:
Dr. Stephan Haug
Dr. Stephan Haug is head of statistical consulting at TUM and member of the Mathematics Department. He has been teaching R courses in different variations for the TUM Graduate School since 2010.