Current course offerings

Please Note: Course profiles marked as not available may still be in development.

Course description

The data revolution in biology requires researchers to handle large amounts of data. Such data often come in complex structures that need to be manipulated before they can be visualised and analysed. In the first part of this course, students will learn how to obtain and navigate large biological data sets, identify inherent structures within them, understand the limitations of data collection and their implications for subsequent analyses. They will get acquainted with multivariate techniques for data exploration and state-of-the art machine learning approaches for pattern identification and classification. Students will also learn how to use High Performance Computer platforms, and how to collaborate efficiently with other analysts in solving common goals. In the second part of the course, students will apply these skills in the context of spatial ecology, i.e. the study of how individuals and species are distributed in space and how these distributions are shaped by abiotic factors and interactions between organisms. Students will learn how to analyse data sets obtained from advanced spatial ecology techniques such as remote sensing and how to integrate ecological and genetic data, thus furthering their understanding of spatial processes by including the demographic history and historical relationships amongst populations.

Archived offerings