The aim of this course is to equip students with theoretical and practical knowledge on methods for spatial data acquisition and exploration, while helping them to develop critical thinking for method selection. In this course, you will use algorithmic thinking and programming skills to find, retrieve, store, and explore various geospatial datasets. In scientific research, significant time and effort goes into acquiring, understanding, and cleaning the data before the actual analysis begins. Maps and diagrams are not only used to present the final results, but also to verify and explore the data during the whole data processing process phase. After this course, you will have a good overview of acquisition and exploration of geospatial data principles and methods and be able to select the most appropriate data acquisition and exploration methods as well as working environment (among R, Python, C++ etc).