- An overview on the ETER data structure. Users should get familiar with the ETER data structure in order to be able to choose the right data.
- Different options of importing ETER data into R. ETER data can be imported via (previously exported) csv files or via API. The training will elaborate on both options, their pros and cons and differences in data manipulation.
- Data preparation. An important part of doing data analysis is the manipulation of data for user’s needs. The training will cover the necessary steps of data preparation before getting started with data analysis.
- Examples from the ETER project. Some analysis done in the ETER project in previous years will be reproduced in the course.