COURSE CURRICULUM

The Master of Engineering in Biomedical Engineering Data Science at Rensselaer requires a total of 30 credits, structured to provide both foundational knowledge and specialized skills in biomedical data science. The core curriculum includes six courses: BMED 4500 – Advanced Systems Physiology (4 credits), BMED 6420 – Engineering Mathematics for Data Science (3 credits), BMED 6470 – Biostatistics for Life Science (3 credits), BMED 6480 – Biomedical Data Science (4 credits), BMED 6490 – Artificial Intelligence for Biomedical Applications (3 credits), and BMED 6980 – Data Science Project or an additional Data Science elective (4 credits), which together ensure a balance of theoretical, computational, and practical skills. In addition to the core courses, students select three electives from a broad range of offerings spanning biology, computer science, economics, electrical and computer systems engineering, industrial and systems engineering, information technology and web science, mechanical and aerospace engineering, and management. Elective options include courses such as BIOL 6410 – Sequence Analysis, CSCI 6100 – Machine Learning from Data, ECSE 6850 – Introduction to Deep Learning, ISYE 6010 – Applied Regression Analysis, ITWS 6440 – Big Data Policy, and MGMT 6600 – Data Analytics, among others, allowing students to tailor their learning toward areas like molecular modeling, computer vision, AI, economic data analytics, and data governance. This combination of core and elective courses equips graduates with the skills needed for data-driven problem solving in biomedical engineering and related fields.