Digital Skills

Martin Gasser
Arts and Society, Cross-Disciplinary Strategies
2021S, Vorlesung und Übungen (VU), 1.0 ECTS, 1.0 semester hours, course number S03557


We will have an in-depth look at the basic ideas and problems in Machine Learning (ML) and AI by training neural networks in the web application Teachable Machine. How do we collect and prepare training data? How do we check whether the algorithm is actually learning what it is supposed to learn? What types of bias could degrade the performance of an ML algorithm, and what could be the consequences if algorithms are deployed in the real world?

Moreover, we will integrate ML algorithms with a simple interactive application in the development environment p5.js. Here, the focus will be on producing sound/musical output in response to visual cues that the algorithm will detect from a webcam video stream. We will therefore also look into the basics of sound synthesis within p5.js/JavaScript. Your creativity is welcome in this task!

This course will be held in close collaboration with „Introduction to Coding“. It is strongly recommended to attend both courses.

Examination Modalities

  • Contribution to the discussion through continuous presentation of the work in progress!
  • No absence without prior excuse!
  • Presentation of the final results!


05 March 2021, 12:45–13:30
12 March 2021, 12:45–13:30
19 March 2021, 12:45–13:30
26 March 2021, 12:45–13:30
16 April 2021, 12:45–13:30
23 April 2021, 12:45–13:30
30 April 2021, 12:45–13:30
07 May 2021, 12:45–13:30
14 May 2021, 12:45–13:30
21 May 2021, 12:45–13:30
28 May 2021, 12:45–13:30
04 June 2021, 12:45–13:30
11 June 2021, 12:45–13:30
18 June 2021, 12:45–13:30
25 June 2021, 12:45–13:30

Course Enrolment

From 01 February 2021, 09:31 to 31 March 2021, 00:00
Via online registration

co-registration: possible

Cross-Disciplinary Strategies (Bachelor): Science and Technology: Foundation

Individual courses: possible