Objectives

This course will introduce students to image and video analysis with deep learning and application areas within medicine and life sciences. It is also suitable for people outside the medicine/life science area as the concepts and methods themselves are not specific to this domain. The course will cover typical image analysis tasks that can be solved by deep learning models, e.g. classification, object detection, segmentation and image generation and practical applications of this. It will also go through the basic building blocks of deep learning models, typical architectures used for image analysis tasks and the steps required to train and evaluate models.

The course will mix lectures, hands-on computational exercises, Q and A sessions and research-related parts.

The first part of the course will be taught as a one week block, which counts as 1.5 ECTS. It is possible to extend this with a 4.5 ECTS optional project work over three weeks following the first block.

Dates

17 May until 21 May 2021 (for the 1.5 ECTS block). If you are unable to attend all days, you may still be able to participate in the course.

21 May until 14 June 2021 for optional 3-week project work (4.5 ECTS).

Personnel

Course organiser: Sonja Aits

Teachers: Sonja Aits, Marcus Klang

Pre-requisite/requirements

• Basic knowledge of Python
• Basic understanding of the principle of machine learning
• Basic understanding of vectors and matrices
• Standard computer/laptop with internet connection

If you lack the pre-requisites we can provide you with self-study material prior to the course. No prior knowledge in medicine and life science is required to take part in the course.

Registration

Registration form for the course "AI in Medicine and the Life Sciences – AI for image and video data"

Registration closes: 2nd May 2021