Module 1: AI and ML Fundamentals
In this block module, you will approach basic AI and ML concepts from a historical, cultural, aesthetic, and technical perspective in order to perform machine learning.
Module 1 is a block seminar in presence.
Module 2: Neural Networks
In this second block module, you will learn about different neural networks and explore common applications in art and other creative practices.
Module 2 is a block module in hybrid format.
Module 3: AI for sound
This module comprises you learning about common sound patterns, how to collect and represent sound data, train models with them, generate new patterns with the trained models, and get an overview of the common AI sound applications in art and other creative practices. The module runs weekly for a month
Module 4: AI for Imaging
In this module you will learn how to process and generate images using deep learning and convolutional neural networks. The module runs weekly for a month in hybrid format.
Module 5: AI for Movement/Sensing: Real time interaction
In this block, you will focus on deep learning for generating data from movement and vice versa. We will also consider real-time interactions and the loops thereby generated.
This is a block module in presence
Module 6: AI for Natural Language
In this block module, you will learn basic natural language processing techniques using with deep learning, as well as common applications in the art and other creative fields.
Module 6 traditionally takes place in the beautiful historic hotel Regina in the ski resort of Mรผrren (Bernese Oberland), only about two hours by train from Bern. Accommodation in the hotel with full board is included in the CAS fee.
All modules
The duration of all modules corresponds to approximately 20 classroom hours each and module work (expected workload 30 hours), with each complete module qualifying for 2 ECTS points. The expected workload for the CAS final Project is 120 hours for 4CTS. The main tools and languages used are Python and libraries such as TensorFlow ad PyTorch. Other tools may be used with limited support from the teaching staff. Computational resources are at disposal if necessary.
If there are free places, modules can be attended individually.