About the course
Introduction to EEG and Artificial Intelligence is a beginner-friendly microcourse designed to provide a foundational understanding of electroencephalography (EEG) and its growing role in modern AI-driven applications. The course introduces the principles of EEG signal acquisition and explains how electrical activity recorded from the brain can be analyzed to gain insights into cognitive and neural processes. Learners will explore the major EEG frequency bands and their significance, understand essential signal pre-processing techniques used to remove noise and artifacts, and gain an overview of feature extraction methods that transform raw EEG recordings into meaningful representations. The course also introduces key machine learning and deep learning approaches used for EEG analysis, highlighting their applications in brain-computer interfaces, cognitive state monitoring, neuroscience research, and healthcare technologies. By the end of this course, participants will have a clear understanding of the EEG analysis pipeline—from brain signal acquisition and processing to AI-based interpretation—and will be equipped with the foundational knowledge needed to explore advanced topics in neurotechnology, computational neuroscience, and biomedical artificial intelligence.
