Fundamentals of ecology; Basic computer knowledge; Basic statistical knowledge

The course aims at introducing the student to the discipline of ecological Informatics, as an interdisciplinary field that bridges computer science, data science, and ecology.

Practical course introducing to the application of statistical, mathematical, and machine learning techniques to analyze complex environmental data and forecast ecosystem dynamics

Lectures during which the students will be tutored in the use of R codes provided by the lecturer

Final exam consisting in the creation of R codes for the analysis and visualization of ecological data

1) Ecological informatics: an introduction; 2) managing ecological data: project data management planning, scientific databases for environmental research, creating and managing metadata, protecting data for long-term use; data discovery; 3) analysis, synthesis and forecasting of ecological data: two examples on inferential modelling of population dynamics and GIS-based data synthesis and visualization

Friedrich Recknagel, William K. Michener (2018) Ecological Informatics - Data Management and Knowledge Discovery. Springer