Initiative for Life Design Innovation (iLDi)

Seminar overview

The course material covers both the theory and practice of AI technologies. Topics include “the foundations of machine learning” and “knowledge informatics”. Students learn about the foundations of AI and machine learning, including a mathematical background, through systematic learning and data mining while building their learning capacity using computers. Topics such as “natural language processing” and “computer vision” touch on language, audio and visual data, and basic mathematics, including Bayesian decision theory required for pattern recognition, and basic analysis technology such as morphological and syntax analysis. Moreover, image processing and natural language processing are learned in a practicum. In the “deep learning practicum”, students work with real data to learn about historical developments and the current status of deep learning, which some call the main player in the third AI boom. Five subjects can be completed in 90 hours, including lectures and practicum sessions.