Machine Learning (ML) and Artificial Intelligence (AI) methods have transformed multiple application domains in the past few years. The impact on computer vision and natural language processing are some of the most visible. However, their usefulness and impact in other sciences is only being explored now.
In this two-day course, offered by the Data Science Laboratory, we will provide an overview of ML/AI methods with a focus on their applications to the sciences within the University of Copenhagen. We will also demonstrate a few concrete examples that can provide clearer impressions of the abilities of these methods. The main objective of this course is to expose teachers to ML/AI methods, so that they can co-create modules in their courses that use relevant ML/AI methodology for their domain. The integration of well-thought course modules will enable students to appreciate the strengths and weaknesses of ML/AI methods within their line of study.
The course is primarily aimed at researchers and teachers at UCPH (incl. PhD students), who are engaged in some form of teaching at the university.
After the two-day course, a subset of the participants can work with the course teachers to co-create domain specific ML/AI teaching modules.