Spatial-Ecology provides training in open-source software for geospatial data processing. Our team members come from various professions, such as geoinformatics, quantum chemistry, neuroscience, ecology and agriculture, and have taught our course globally. This rich experience uniquely positions us to understand different perspectives and learning needs.
Our approach to teaching data analysis is unique, as it integrates multiple programming languages and other software to build workflows. With simple scripts, we demonstrate how to automate essential tasks and modify programmes to solve specific problems. We assist course trainees with analysing their own distinct data requirements, whether from the social, physical or natural sciences. We also teach the application of advanced computing methods and machine learning through a combination of these immensely valuable open source tools.
Moreover, we support the development, distribution and adoption of free and open source technology. Through these tools, our objectives are to conduct research, provide training and promote the use of digital information to benefit human well-being, the environment, and economic growth.
The Spatial Ecology wiki-based platform is offered as a resource for learning about free and open source programming for data processing.