Professional training
Hybrid
Participation Certificate for everybody; Take home exams to be solved until March 31, 2026. Certificate with grades.
Full Time
Regular fees: 330 - 1720 CHF
International Fees : 220 - 1100 CHF
OPEN
Karin Loetscher
The “Fribourg Winter School in Data Analytics and Machine Learning” (Feb 2-13, 2026) provides training in state-of-the-art quantitative tools for predictive and causal analysis. The winter school takes place in a hybrid format, implying that participants can attend courses either in class (face-to-face) or online (the sessions will not be recorded).
The one- to three-days-courses cover both introductory and more advanced topics, using the open source software packages “Python”, “R”, “Julia” and “Knime”. “Python”, “R” and “Julia” are among the most popular programming languages in data science and statistics, while “Knime” is a user-friendly, flowchart-based graphical interface that does not require any programming skills. Registration is available at: https://www.unifr.ch/appecon/en/winterschool/.
Many firms and organizations have recognized the value of analyzing data using quantitative tools such as regression, machine learning, and deep learning...
* for forecasting specific outcomes such as prices or sales (predictive analysis),
* for evaluating the causal impact of specific actions or policies such as offering discounts or medical treatments (causal analysis),
...thereby improving the quality of decision-making.
Among the topics covered in the various courses are
- regression techniques for multivariate statistical analysis;
- machine learning algorithms like lasso, decision trees, random forests;
- deep learning (neural networks) to analyze unstructured data like text, pictures, videos;
- causal machine learning for impact and policy evaluation.
Boulevard de Pérolles 90
1700 Fribourg , Suisse
