Advanced Machine Learning

In many disciplines, the amount of available data and the computing capacity are growing rapidly. This enables the application of machine learning methods on tasks previously being reserved for humans. The format is designed to align with the participants’ main study and or professional activities. The teaching and learning approaches are team and discussion oriented and designed to develop practical competency. The CAS is structured in six modules: Review of machine learning, practical methodology and applications (Block module), Deep networks (Block module), Advanced Models I (Block module / Lago Maggiore), Selected topics on machine learning, Philosophy and Ethics of extended cognition and artificial intelligence (Lectures and Seminars), Advanced Models II (Block module Mürren).

• A university degree and basic knowledge of mathematics, statistics, programming, machine learning and professional or research experience in the field of data analysis are required for admission to the course. The required basic knowledge is based on the level of an introductory lecture as part of an undergraduate master’s degree. The program management specifies these requirements.
• Exceptions to the admission requirements can be approved by the program management “sur Dossier”. For people without a university degree, they can impose additional requirements for admission to ensure that they can successfully complete the course.

CHF 9'900.- (Full pension hotel accommodation is included in the CAS fee)
Employees and students of the University of Bern: CHF 6'900.-