The assignment delves into the critical issue of artifact detection and removal in electroencephalography (EEG) data analysis. It examines various artifact types, such as eye blinks, muscle movements, and electrical interference, that can contaminate EEG recordings. Furthermore, it discusses strategies and tools for preprocessing EEG data to minimize these artifacts and improve the accuracy and reliability of subsequent analyses.