Winter School in Data Analytics and Machine Learning

Many firms and organizations have recognized the value of analyzing data based on quantitative tools like regression, machine learning, and deep learning 

• for forecasting specific outcomes such as sales or prices (predictive analysis),
• for evaluating the causal impact of specific actions such as offering discounts or running marketing campaigns (causal analysis). 

This permits improving the quality of decision making and thus increasing efficiency and competitiveness. 

The “Fribourg Winter School in Data Analytics and Machine Learning” provides training in state-of-the-art quantitative tools for predictive and causal analysis. The winter school takes place in hybrid form, implying that participants can attend courses either in class (face-to-face) or online. Please note that 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, flow-chart based graphical interface that does not require any programming skills.

Among the topics covered in the various courses are

• regression techniques for multivariate statistical analysis;
• machine and deep learning algorithms like lasso, decision trees, random forests, and neural nets;
• text analysis to extract and statistically analyze text information from websites, like sentiments about products.

• Overview of the courses

  Instructor	Course	Software	Level	Date	ECTS
  Martin Huber	Data Analytics and Machine Learning with Applications in KNIME	KNIME	introductory (no programming required)	Feb 2	0.5
  Xenia Wietlisbach	Introduction to R	R	introductory	Feb 3	0.5
  Martin Huber	Predictive and Causal Machine Learning in R	R	intermediate	Feb  4-5	1.0
  Christian Kauth	Data Analytics with Julia	Julia	introductory	Feb 6	0.5
  Christian Kauth	Machine Learning with Python - from Zero to Hero	Python	intermediate	Feb 9-10	1.0
  Christian Kauth	Deep Learning with Python - from Tabular to Mutlimedia	Python	advanced	Feb 11-13	1.5

• Participants

  The winter school is open to BA students, MA students, Ph.D. students, and academic researchers (such as post-docs and professors) at the University of Fribourg and at other universities or research institutions, as well as to employees of private companies and the public sector.

• Teaching modalities

  The working language will be English. Courses are held in a spacious lecture hall on the Pérolles campus (Boulevard de Pérolles 90, CH-1700 Fribourg) and can also be attended online. Please note that the sessions will not be recorded. 

• Examination / evaluation

  Take home exam: students obtain a dataset with several exercises to solve that need to be resubmitted in order to be graded. Without taking the exam, students can nevertheless obtain a certificate of participation (without grade).

  Take home exams to be solved until March 31, 2026.

• Credits

  Successful participation in the courses (including examinations) can be credited with up to 5 ECTS points (if winter schools are recognized by the home university/institution).

• Course fees

  BA, MA, and Ph.D. of the University of Fribourg	BA/MA/PhD students at other universities or academic researchers (e.g. post-docs, professors...) at the University of Fribourg or elsewhere	private companies and public sector
  *Flat rate for all courses:  CHF 90	Block 1: KNIME course (2 Feb)  CHF 220	Block 1: KNIME course (2 Feb)  CHF 330
  	Block 2:  R courses (3-5 Feb)  CHF 550	Block 2:  R courses (3-5 Feb)  CHF 880
  	Block 3:  Julia course  (6 Feb)  CHF 220	Block 3:  Julia course  (6 Feb)  CHF 330
  	Block 4:  Python courses  (9 -10 Feb)  CHF 410	Block 4:  Python courses  (9 -10 Feb) CHF 610
  	Block 5: (11-13 Feb)  CHF 550	Block 5: (11-13 Feb)  CHF 880
  	Block 4 & 5 (9-13 Feb)  CHF 670	Block 4 & 5 (9-13 Feb)  CHF 1030
  	All courses: (2-13 Feb)  CHF 1100	All courses: (2-13 Feb)  CHF 1720

  *Please note: Not all courses have to be attended.  

   

• Payment

  Payment is made directly via the online registration form. Please note that the registration is only complete when we have received the registration fee. The deadline for online registration and payment is January 26, 2026. 

• Location

  University of Fribourg, Boulevard de Pérolles 90, 1700 Fribourg, Switzerland. 

  How to arrive

• Accomodation

  Participants must book their accommodations themselves.

  Here are a few recommendations:

  Convict Salesianum

  Hotel aux Remparts

  Hotel du Faucon

  Hotel de la Rose