On this page you can find all the courses and tracks offered by the Utrecht Summer School. Check the course pages for more detailed information.
163 course(s) found
English Advanced 1 (B2 → B2+)
Are you looking for an in-depth, high-level course to improve your English language skills? Our Advanced course will help you to develop your language skills so that you can communicate more effectively and confidently in a wide range of work and study situations. Our interactive teaching will improve your reading, listening, speaking and writing skills. We will use vocabulary work, personal feedback, and grammar revision to ensure that you…
The Summer School on Geometry is a two-week programme featuring ten one-day mini-courses on various topics within Geometry. This is understood in a broad sense: the courses will touch on algebraic geometry, differential geometry, and algebraic topology, and will highlight interactions with fields like number theory, group theory and mathematical physics. The School is aimed at students that have completed at least two years of undergraduate…
Biostatistics for Researchers
The course provides an introduction into statistical methodology for life sciences and discusses a number of statistical techniques for practical data analysis. Concrete examples and case studies are used to apply the theory to practical situations.
Challenges in Global Health: Non-Communicable Diseases
This one-week course aims to enhance the participant's knowledge and understanding of major health challenges with a focus on chronic non-communicable diseases globally. The topics discussed range from burden of and risk factors for chronic non-communicable diseases, epidemiologic transition and globalisation, to the effects of early life environment, environmental changes on health, the intersection of communicable and non-communicable diseases…
Missing Data in R
Missing data are ubiquitous in nearly every data analytic enterprise. Simple ad-hoc techniques for dealing with missing values such as deleting incomplete cases or replacing missing values with the item mean can cause a host of (hidden) problems. In this workshop, we will discuss principled methods for treating missing data and how to apply these methods in R. We will cover some basic missing data theory, methods for exploring/quantifying the…
Regression in R
Linear regression is one of the most ubiquitous statistical methods. Most statistical techniques can be viewed as either special cases of linear regression (e.g., t-tests, ANOVA) or generalizations of linear regression (e.g., multilevel modeling, SEM, neural networks, GLM, survival analysis). In this workshop, participants will learn how to apply linear regression techniques in R. We will cover (multiple) linear regression, categorical predictor…
Chemical Safety Assessment under REACH
This four day training provides a full introduction in chemical safety assessment and offers you the opportunity to apply the theoretical framework directly in your own practice. Therefore the training involves a crash course on the first day in which a general overview of the REACH legislation, processes and the chemical safety assessment (CSA) is provided, with short interactive exercises. In the remaining part of the course the participants…
Introduction to R
This workshop introduces participants to the R statistical programming language. R is a completely free and open-source programming language and environment for statistical analysis. In this workshop, participants will learn what R is and how it differs from other statistical software packages and programming languages. They will learn the basics of data I/O, manipulation, and visualization in R. We will also cover basic statistical analyses…
Introduction to Python (online course)
If you are looking for a powerful programming language, you should learn Python, a language with a simple syntax and a powerful set of libraries. It is easy for beginners to learn Python and it is widely used in many scientific fields for data exploration. This workshop is an introduction to the Python programming language and, in particular, is geared toward people who are new to the language and who have relatively little experience with other…
Text Analysis with Python
This course introduces the basic concepts of text analysis in Python. Participants will learn how to apply text mining methods on text data and analyse them in a pipeline with machine learning and natural language processing algorithms. The course has a strong practical hands-on focus, and participants will gain experience in using text mining on real data.
Structural Equation Modelling in Mplus
If you expect to work with the software Mplus, this course can help you to get started! This course is a compact one-day workshop introducing Mplus. We will focus on preparing data for Mplus, introducing common model syntax, avoiding common mistakes, interpreting output, and dealing with common error messages. Practice exercises demonstrate multiple regression and factor analysis models, which are the basis of structural equation models in…
Introduction to Graphical Models (for Network Inference) in R: Markov random Fields and Bayesian Networks
Probabilistic graphical models (PGMs) represent the world in a simple way that humans can understand better. They are graphical representations to understand the complex relationships between a set of random variables of interest (nodes). The edges that connect these nodes show the statistical dependencies between them. PGMs have numerous applications in social and behavioral sciences, life sciences, economics, computer science, and many more…
Bayesian Hypothesis Evaluation using JASP or R
In this one-day course participants will be introduced to informative hypotheses that are alternatives for the traditional null and alternative hypotheses, and, to the Bayes factor and GORIC which are alternatives for the p-value. This course is applied, hands-on, and built around concepts and not formulas.