Description
How can we use AI/ML techniques in real life? What kind of models have been used in different fields? In this course, we will introduce domain specific AI/ML applications and discuss challenges we are facing in using AI/ML in different fields. In addition, special datasets created and processed in diverse domains will be explained. This course will especially focus on fields including society, environment, health care and life science. Various types of data will be introduced such as biological imaging, spatial, or network data.
This course is a combination of lectures, practical sessions and project work. After the introductory lectures and practical sessions, students will design their own AI/ML applications.
Course Objectives
Understand and discuss applications of the most used ML/AI models in the following fields
o Time series
o Spatial databases
o Network datasets
o Human mobility data
o Text corpora
o Healthcare data
o Biological imagingApply and/or implement evaluation metrics to compare the performance of AI/ML models
Understand limitations and best practices of AI/ML models
Understand FAIR principles, ethics, algorithmic fairness, identify and discuss potential problems in different fields
Apply and compare different ML/AI models in a chosen topic
Mode of Instruction
Lectures
Practical sessions
Presentation of own work (including a written report following a template)
Registration
Application period
For application EduXchange is used, application will start on Thursday 15th of May 2025 at 13:00h.
For minor students, TU Delft, Erasmus and LDE students: Thursday 15 May 13.00h until 30 June
More information about the application procedure can be found on this website: