This is a brief introductory workshop especially aimed at those who have little or no experience working with LaTeX. There will be a theoretical and a hands-on practical part. The theoretical part covers the basics of what TeX and LaTeX are, how they compare with Office text processors, and how to get started with writing documents. The practical is a hands-on demonstration of some of the more useful features of LaTeX, such as making Gantt charts, bibliography management and automatic acronym expansion.
Machine learning plays an increasingly important role in many scientific areas, including geo-information science and remote sensing, ecology, biosystems engineering, and bioinformatics.
In this module we study how to analyse data that are not normally distributed. We look at fractions (logistic regression), counts (Poisson regression, log-linear models), ordinal data (threshold models), and overdispersion. We discuss (quasi-) maximum likelihood estimation and the deviance.
Classical statistics offers a powerful toolbox for data analysis. This toolbox, however, may not always be sufficiently flexible for modern data situations.
The aim of this course is to provide an introduction to R and R Studio. It introduces the participants to R language syntax, to enable them to write their own R code. They will also learn about R data-types and data-structures, and they will be taught how to explore the data and produce plots. The course will be a combination of lectures and practicals.
Extend participants' basic knowledge of R by teaching them more advanced programming concepts and the use of R for more complex problem solving, going beyond just statistics.
This course introduces analog serious games (e.g. board and card games, narrative games) as tools to explore and foster food system transformation and challenges the participants to design new and/or adapt existing games and test them in a final event where they can showcase their prototypes.
Input data for spatial environmental models may have been measured in the field or laboratory, spatially interpolated, derived from remotely sensed imagery or obtained from expert elicitation.
