Biomedical Sciences are the technological disciplines that aim to explore methods to obtain, produce, reveal or produce information related to understand, model, monitor, diagnose, combat problems in human and/or animal bodies. Machine learning in biomedical technology is relatively new field of scientific research area and engineering technology application field, its growing rate is so fast that it is put into lower education levels than graduate level. In this work, educational contributions of senior year electrical and electronics engineering student projects will be discussed. After supervising four undergraduate student graduation projects, done by total of six students, it is concluded that the undergraduate electrical and electronics engineering average student is ready to apply deep learning techniques to biomedical sciences with restricted budget conditions, internet resources, available computational infrastructure and credit-hour load from the other courses leading graduation. Moreover, a student is already aware of and is ready to fully consider his professional work obligations health, safety, manufacturability, sustainability, economy direct or indirect effects to society, ethics, and environment.

Keywords - Biomedical Engineering, Deep Learning, Artificial Intelligence, ECG, ACS, Biology

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