Neural Data Science

Description

DATA489 is a one semester 15-point (0.1250 EFT) course aimed at postgraduate students who are interested in gaining skills in data science techniques applied to the neuroscience discipline (i.e. neural data science), specifically for non-invasive brain imaging with electroencephalography (EEG). The focus of the course will be to apply data science to the emerging field of computational neuroscience that aims to correlate patterns (as obtained by various Machine Learning techniques) in EEG data to thought and behavioural processes. The course is interdisciplinary and explores EEG data from a variety of perspectives. DATA489 students will learn how EEG data is pre-processed, cleared from noise/artefacts and clustered through Machine Learning techniques to understand cognitive and perceptual processes of the brain; further, you will learn how EEG signals can be used as an interface between the brain and computers/machines in the emerging field of Brain Computer Interface (BCI).