All Courses
On this page you can find all the courses and tracks offered by the Utrecht Summer School. Detailed information is published on all individual course pages.
11 course(s) found
AI-Aided Systematic Reviewing
Online course
Please note: this course is almost fully booked!
More and more researchers rely upon Systematic Reviews: attempts to synthesize the state of the art in a particular scientific field. However, the scientific output of the world doubles every nine years. In this tsunami of new knowledge, there is not enough time to read everything – resulting in costly, abandoned or error-prone work. Using the latest methods from the field of Artificial…
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Psychodiagnostics: Theory and Skills Training ONLINE
Online course
This summer, Utrecht University offers you a 'bridging' course in psychodiagnostics, in order to overcome deficiencies in psychodiagnostics and assessment for entering the master course Clinical Psychology. This summer course focusses on familiarizing oneself with theoretical backgrounds of psychodiagnostics, practicing skills necessary to master all stages of the diagnostic process (intake, formulating a diagnostic question, formulating…
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Introduction to JASP and (Bayesian) Hypotheses Evaluation - Free for employees of the Faculty Social Sciences of Utrecht University (FSS-UU)
Since 2018 the first year bachelorstudents of the Faculty of Social and Behavioral Sciences of Utrecht University learn to work with JASP and how to (Bayesianly) evaluate hypotheses using JASP. The course is tailored to lecturers and researchers who want to learn what the bachelor students of FSBS learn about JASP and (Bayesian) hypotheses evaluation (and a little bit more). This course is applied, hands-on, and build around concepts and not…
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Introduction to Structural Equation Modeling using lavaan (E-Learning Course)
In this e-learning course, we will cover the basics of structural equation modeling (SEM) using the R package lavaan. Participants will learn how to interact with the lavaan software and how to run common types of SEMs (e.g., path models, confirmatory factor analyses, latent regression models, multiple group models) using lavaan. No prior knowledge of lavaan is necessary, but some experience with R and SEM (although not strictly required) is…
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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 generalisations of linear regression (e.g., multilevel modelling, SEM, neural networks, GLM, survival analysis). In this course, students will learn how to apply linear regression techniques in R. We will cover (multiple) linear regression, categorical predictor…
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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 basic missing data theory, methods for exploring/quantifying the extent…
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Introduction to Python
If you are looking for a powerful programing 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 widely use it in many scientific areas for data exploration. This workshop is an introduction to the Python programming language and in particular is geared towards people new to the language and who may, or may not, have experience with other programming…
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Introduction to R
This workshop will introduce students to the R statistical programming language. R is a completely free and open-source programming language and environment for statistical analysis. In this course, students 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 visualisation in R. We will also cover basic statistical analyses such as t…
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Text Analysis with Python
This course introduces the basic concepts of text analysis in Python. In this course, 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 strongly practical hands-on focus, and participants will gain experience in using text mining on real data.
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Cognitive Neuropsychology: From Patients to Functional Models
As an advanced training in Cognitive Neuropsychology, the course aims to teach PhD students how to collect and interpret patient data in order to test cognitive theories and build cognitive models. The emphasis will be on 'doing research'. Candidates will get an acquaintance with standard neuropsychological testing, will be shown examples of patients cases, case statistics and will build, run and analyse their own experiment. A special training…
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Structural Equation Modelling in Mplus
If you expect to work with the software Mplus, this course can help you to get started! This online course is a compact 1-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 structural equation models in…
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