Master of Science in Healthcare Data Science

Program Director (Data Science): Yolanda Gil, PhD
Program Co-Director (Biomedical Engineering): Brent J. Liu, PhD

The Master of Science in Healthcare Data Science is a cross-disciplinary joint degree program offered by the Viterbi School of Engineering and the Keck School of Medicine. Students will complete a core set of courses to provide a foundation in data science and health and choose electives to optimize their preparation for their preferred career path and unique professional opportunities. Data science for addressing healthcare needs is an increasingly important area for creating novel devices, advancing biomedical research, and developing innovative processes that require integrative approaches linking data systems, analytics, business processes, and decision support.  

The curriculum is designed to be accessible to students with any background, including students with a biomedical background and no computer science knowledge as well as students with a computer science background and no biomedical knowledge.  Students with undergraduate degrees in computer science, engineering, science or mathematics will acquire the necessary knowledge to analyze health data with diverse sources and purposes and can request to replace introductory data science courses with more advanced ones.  Students with undergraduate degrees in biology, biochemistry, and other sciences will acquire formal and practical data science skills and can request to substitute introductory courses in health with more advanced ones.  There is no requirement of prior knowledge of programming or computer science, as the curriculum is designed with special introductory courses that are accessible to students with diverse backgrounds.

Students will learn a range of data science skills such as developing scalable data systems, using state-of-the-art software and infrastructure for data science, designing data analyses with statistical methods, applying machine learning and data mining techniques, designing effective visualizations, and working in multi-disciplinary data science teams. On the health side, students will be integrated into teams working with medical students in healthcare settings as well as courses on clinical workflow and medical technology systems such as image acquisition systems and other healthcare informatics systems.

All information contained here is summarized from the USC Catalogue and is considered non-official. For all rules, regulations, procedures, and outlines, please see the current academic year USC Catalogue. The USC Catalogue supersedes all other publications.

Current students follow degree requirements in effect for the academic year they began their studies at USC.  If you are a current student, please refer to your STARS report or the appropriate USC Catalogue for your year.  Students seeking to advance their catalogue year to follow updated curricula may contact their department advisor.

Published on July 19th, 2018

Last updated on August 30th, 2022