VU Hands on Machine Learning



  • 02 March 2023–22 June 2023 Universität für angewandte Kunst in Wien, Wien, Österreich (GCP)
  • 11 March 2024–17 June 2024 Universität für angewandte Kunst in Wien, Wien, Österreich (GCP)


Machine Learning, Artificial Intelligence, Coding, Programming, Python, TensorFlow, Linear Regression, Recommender Systems


This course is the practical/experimental companion to the seminar on the theory and history of Machine Learning by Paul Feigelfeld (until 2023 by Clemens Apprich). While it is not a formal requirement to also attend this other course, we highly recommend to jointly attend both of those two courses. Ongoing course documentation:


The course features three major parts we will focus on: 1. Introduction to coding and data processing with Python 2. Implementation of several basic machine learning algorithms (Markov-chain based text generation, linear regression, K-Nearest-Neighbour classification, K-means-clustering, perceptrons and simple neural networks) 3. Project work, open experimentation and discussion: the final weeks of the course aim at defining specific (prototype) projects, which the attendees will work on either individually or in groups, as part of their final exercise in this course, as well as reflective discussions of the digital-material basis of "AI".



  • Universität für angewandte Kunst in Wien, Wien, Österreich
  • Oskar-Kokoschka-Platz 2
  • 1010 Wien
  • Österreich

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Published By: Andrea Klaura | Universität für Angewandte Kunst Wien | Publication Date: 07 September 2023, 09:40 | Edit Date: 24 May 2024, 10:23