Courses open for registration

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.

This is a refresher course. The level is that of a second course in Statistics. We will refresh basic knowledge of Probability, Statistical Inference (Estimation and Testing), t-tests, simple cases of Regression and ANOVA, Experimental Design, Nonparametric Tests, and Chi-square Tests. Some time is reserved to discuss statistical problems of the participants.

This 3 half-day programme supports postdocs in identifying and tackling challenges that have come up as result of a crisis and how to stay in a positive flow of work and life.

This is a course on the soils of the world and their assessment. It will provide an introduction to the soils of the world and their diversity, their main forming factors, classification and management. The course will include lectures and hands-on exercises. It will make use of the facilities of the World Soil Museum.

This course introduces methods and software for management, analysis and mapping of soil type and soil properties within the R environment for statistical computing. The course alternates between lectures and computer exercises and covers a variety of subjects, such as geostatistics, machine learning for soil mapping, soil functional mapping, proximal soil sensing, quantification of uncertainty, sampling for mapping and soil map validation.

During this four-week online course, the participants become acquainted with different resilience concepts and their application from an interdisciplinary perspective. Accordingly, we will address how resilience theory can be used to tackle fundamental and societal issues from a socio-economic and bio-physical perspective and will provide a critical reflection on the relevance, use, and applicability of the concept of resilience. We invite you to participate!

In this workshop, participants will learn the principle of tidy data, how to transform and combine datasets using the tools from the tidyverse and how to generate advanced visualization with the ggplot2 package. The course will be a combination of lectures and practicals.

In this module we continue with Regression, ANOVA, and ANCOVA, set in the general framework of Linear Models. We look at topics like parameter estimation and interpretation, checking model assumptions, regression diagnostics, analysis of unbalanced designs and multiple comparisons.

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.

In this course, the participant will be provided with both the basic understanding of the principles of multivariate methods and the skills needed to use those methods in his/her own work. The course consists of lectures and computer practicals using RStudio.

In this course, you will learn how to model patterns and structures contained in data, and evaluate data-driven models, i.e. models that learn directly from observations the phenomena under study. Participants are encouraged to bring their own problems in class and analyse data from their own research.

In this module we discuss how to analyse data for which the assumption of independence is violated. So: Do you have a nested experimental set-up? Or repeated measurements? Or weight of the same animal over time? Or pseudo-replication? Then, you are likely to need Mixed Models. In this course, you will learn all about it!

Modelling is a crucial part of today's science. Among other things, models are used for assessing sensitivity of systems to disturbances or changes in external factors, and for predictions of future system states. This course provides an introduction to modelling with a focus on systems analysis using dynamic simulation models.

In this third edition of the European Forestry course, organised under the flag of the Euro League for Life Sciences (ELLS), we aim to shed light on the current management strategies of European forests, and how to adjust these to become climate-smart. There is much variation in forest management across Europe, at least in part based on differences in ecology, economics, social perceptions, ethics and morality towards forests and the resources and services they provide. The idea of this course is to bring PhD candidates and postdocs from various countries and cultural backgrounds, and working in different scientific disciplines but related to European forests, together in a professional on-site training course. The course will be organised at the BOKU training centre “Traunkirchen” in Austria. This venue is perfect for this course, as it sits in a location that is surrounded by forests that are managed in a varied way, so as to provide excellent learning experiences for the participants. A travel subsidy is available for PE&RC PhD candidates.

In this course, some of the concepts that underlie the optimization of spatial sampling will be introduced. These include methods to ensure good spatial coverage by a sample, methods to select an optimal grid spacing for geostatistical mapping and complex methods of combinatorial optimization. The course takes place in hotel "De Bosrand" in Ede and includes accommodation.

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.

In this workshop, participants will learn the principle of tidy data, how to transform and combine datasets using the tools from the tidyverse and how to generate advanced visualization with the ggplot2 package. The course will be a combination of lectures and practicals.