Automated Data Processing with R

Upon the completion of this module, you will have the fundamental skills in R programming as a basis for more advanced methods like Geospatial Data Analysis (is covered by the module “Spatial Statistics” in the MSc program) and Machine Learning. Specific learning contents are

• R IDE and R interpreter
• Simple data types and operators
• Variable declaration and libraries
• Data Structures (vectors, matrices etc.)
• Spatial data structures (simple feature and raster objects)
• Control structure (i.e. conditions and loops)
• Definition of custom functions
• Manipulating tabular data using ‘dplyr’
• Read and write data
• Vector and raster data manipulation
• Plots and maps
• R Markdown notebooks

Core UNIGIS modules 1-3 or equivalent understanding of GIS, data modeling, data structures and data acquisition. Prior experiences with scripting languages is a plus. If you are not sure whether you qualify, please contact martin.loidl@plus.ac.at.

This is an exclusively english language module, hence any kind of communication with the module lecturer should be in English. A discussion forum is maintained in Moodle in order to support efficient module instruction. You are requested to submit all your questions related to this module to this forum only. The lecturer will check all incoming comments on a regular basis. He will answer your questions or provide you with pointers for solving your problems. The module is delivered in form of an instructed self-study that is based on an explorative learning process. Theoretical concepts are complemented with practice oriented examples demonstrated with help of multimedia elements. Upon completion of the module students are requested to evaluate the module, which is a part of our quality assurance.

R, RStudio (IDE)

The assessment in this module is based on a 20 to 30 minute online discussion of assignment solutions. Assignment solutions must be submitted in written format to the Dropbox within the required time period. If assignments are submitted late, the lecturer is not obligated to grade them.