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”, and “Knime”. “Python” and “R” 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







    Martin Huber

    Data Analytics and Machine

    Learning with Applications in KNIME



    introductory (no programming required)

    Feb 6


    Christian Kauth

    Machine Learning with Python -
    from Zero to Hero 



    Feb 7-8


    Christian Kauth

    Deep Learning with Python



    Feb 9


    Madleina Caduff

    Introduction to R



    Feb 10


    Martin Huber

    Predictive and Causal Machine

    Learning in R



    Feb 13-14


    Helge Liebert

    Text analysis in R



    Feb 15-17


  • 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).

  • Credits

    Successful participation in the courses (and 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 (6 Feb) CHF 200

    Block 1: Knime course (6 Feb) CHF 300


    Block 2: Python courses (7-9 Feb) CHF 500

    Block 2: Python courses (7-9 Feb) CHF 800


    Block 3: R courses (10-17 Feb) CHF 600

    Block 3: R courses (10-17 Feb) CHF 900


    All courses: (6-17 Feb) CHF 950

    All courses: (6-17 Feb) CHF 1500

    *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 31, 2023. 

  • 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:

    Convid Salesianum

    Hotel aux Remparts

    Hotel du Faucon

    Hotel de la Rose