| Kurzkommentar |
The main objetive of this seminar is to teach the students with the ability to solve common problems in big data processing using Open Source programing languages (python) and Geodata Libraries (OGR, GDAL). The seminar will start by providing an introduction into basic scripting techniques (execute scripts, building loops, using lists), and will later use these techniques to solve complex, yet in modern geodata science common, processing tasks.
Students will have to submit (nearly) weekly labs, and the MAP will be constituted of a complex programing problem. Students of all MSc-levels are welcome, yet the class is, because of the workload, recommended for people close to, or already in, their MSc-Thesis. The class will be taught in the PC-pools using departmental infrastructure, but students are welcome to bring their own equipment (e.g., laptop).
As the class is centered around the application of large amounts of geospatial data, it is strongly recommended for all class participants to have at least some experience with the two most common types of geodata - shapefiles, and rasterfiles - for example through basic GIS classes. |
| Kommentar |
The main objetive of this seminar is to teach the students with the ability to solve common problems in big data processing using Open Source programing languages (python) and Geodata Libraries (OGR, GDAL). The seminar will start by providing an introduction into basic scripting techniques (execute scripts, building loops, using lists), and will later use these techniques to solve complex, yet in modern geodata science common, processing tasks.
Students will have to submit (nearly) weekly labs, and the MAP will be constituted of a complex programing problem. Students of all MSc-levels are welcome, yet the class is, because of the workload, recommended for people close to, or already in, their MSc-Thesis. The class will be taught in the PC-pools using departmental infrastructure, but students are welcome to bring their own equipment (e.g., laptop).
As the class is centered around the application of large amounts of geospatial data, it is strongly recommended for all class participants to have at least some experience with the two most common types of geodata - shapefiles, and rasterfiles - for example through basic GIS classes. |
| Zielgruppe |
The format of the class and the programming problems to be solved require an understanding of general data types used in geographic research, such as shapefiles or rasterfiles. As such, the class is ideal for Geography students. External students, e.g., from other departments and/or universities, are welcome as well - though it would be recommended for these students to have at least some background in Geographic Information Systems. |
