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 3

    0.5

    Xenia Wietlisbach

    Introduction to R

    R

    introductory

    Feb 4

    0.5

    Martin Huber

    Predictive and Causal Machine

    Learning in R

    R

    intermediate

    Feb 

    5-6

    1.0

    Christian Kauth

    Data Analytics with Julia

    Julia

    introductory

    Feb 7

    0.5

    Christian Kauth

     Machine Learning with Python - from Zero to Hero

    Python

    intermediate

    Feb

    10-11

    1.0

    Christian Kauth

    Deep Learning with Python - from Tabular to Mutlimedia

    Python

    advanced

    Feb

    12-14

    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, 2025.

  • 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

    (3 Feb) 

    CHF 220

    Block 1:

    KNIME course

    (3 Feb) 

    CHF 330

     

    Block 2: 

    R courses

    (4-6 Feb) 

    CHF 550

    Block 2: 

    R courses

    (4-6 Feb) 

    CHF 880

     

    Block 3: 

    Julia course 

    (7 Feb) 

    CHF 220

    Block 3: 

    Julia course 

    (7 Feb) 

    CHF 330

     

    Block 4: 

    Python courses 

    (10 -11 Feb) 

    CHF 410

    Block 4: 

    Python courses 

    (10 -11 Feb)

    CHF 610

     

    Block 5:

    (12-14 Feb) 

    CHF 550

    Block 5:

    (12-14 Feb) 

    CHF 880

     

    Block 4 & 5

    (10-14 Feb) 

    CHF 670

    Block 4 & 5

    (10-14 Feb) 

    CHF 1030

     

    All courses:

    (3-14 Feb) 

    CHF 1100

    All courses:

    (3-14 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 27, 2025. 

  • 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

Further Information

  Mrs Karin Lötscher

Secretary