We are happy to announce that the JASP team will offer a week of workshops in Amsterdam this summer. In this blogpost we’ll highlight the third of four workshops: “A Crash Course in Machine Learning with JASP“. This one-day workshop takes place on Wednesday August 26th 2026, and can also be attended online.
The main purpose of this workshop is to familiarize participants with key concepts in machine learning, assisted by the machine learning module in JASP (for a quick impression see the blogposts here, here, here, and here). The workshop covers popular machine learning techniques such as k-nearest neighbors (KNN), random forests, and boosted regression trees. The techniques are then applied to concrete data sets. Additionally, the workshop explains how machine learning models, once trained, can generate predictions for new data sets. The workshop is designed to provide an accessible introduction to machine learning in JASP, emphasizing its user-friendly interface and powerful analytical capabilities. Through a combination of hands-on exercises and guided discussions, participants will learn how to implement, interpret, and evaluate machine learning models with ease. A preliminary program is available on the workshop website.
At the end of this workshop, participants should have the knowledge to confidently apply the machine learning techniques in JASP to new data sets, interpret the output, and report the results. This workshop is relevant to anybody who desires an accessible introduction to machine learning. No background in statistics or computer programming is required.
Participants should bring a laptop with the latest version of JASP installed. Plenary sessions will be given by Don van den Bergh and Koen Derks.
NB. A 50% discount is available for students and faculty from JASP “Gold” Educator Institutions. The present list includes the Universiteit van Amsterdam, M&S/Faculty of Social Sciences/Utrecht University, and Nyenrode Business University.
References
- Hastie, T., Tibshirani, R., Friedman, J. H., & Friedman, J. H. (2009). The elements of statistical learning: Data mining, inference, and prediction (2nd ed.). New York: Springer.
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