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The Master of Science in Healthcare Data Science is a cross-disciplinary joint degree program offered by the Keck School of Medicine and the Viterbi School of Engineering. Students must be admitted by both the Viterbi School of Engineering and the instructor of the Topics in Health, Technology and Engineering course.
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. Large amounts of health data are becoming available across all components of the healthcare ecosystem – big data is becoming the norm. Advances in data acquisition, storage, processing and interpretation are blurring the boundaries between traditional health care provision and into mobile devices and the Internet of Things. As more personal health data are collected, there are more opportunities for disease prevention and monitoring. As life expectancy grows, there is increasing demand for devices and services that support independence and quality of life. From health organizations to startups, there is unprecedented demand for healthcare data science professionals with clinically-grounded experience relevant to current health system needs.
The USC Master of Science in Healthcare Data Science will provide students with the knowledge and skills to:
- Understand the requirements and techniques to manage health and healthcare process data collected by healthcare providers and organizations, use it to improve patient care, and analyze it to improve the business processes in and between hospitals, insurance companies, public health agencies, and other components of the healthcare ecosystem
- Understand the use of data science in clinical research and translational medicine
- Understand the design and development of personal devices and mobile apps to collect health data and to monitor health-related variables
- Understand the use of emerging technologies in data science and their application to health and healthcare delivery processes
- Gain direct experiences in finding and articulating challenges in healthcare settings that can be met through integrative engineering solutions
Upon graduation, students will have not only data science skills but will be uniquely qualified to join and lead data science teams at health companies and healthcare provider organizations, perform data analytics in health-related startups and tech companies, and develop emerging technologies revolving around health data.
The degree consists of a set of required core courses in both data science and healthcare supplemented by electives chosen from more focused courses in data science and health. On the data science side, students will learn about artificial intelligence (particularly machine learning and semantic data models), data management, privacy, and data visualization. On the health side, students will be integrated into teams working with medical students in healthcare settings. Capstone, real-world projects will motivate elective choices and enable students to acquire practical experience with a data science project based in a healthcare service setting.
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.
A minimum of 32 units with an overall cumulative GPA of at least 3.0 is required for the Master of Science in Healthcare Data Science. Students should consult with an academic adviser prior to registering for any classes. For course descriptions, please visit this page. To apply, please visit this page.
International Students: This program is eligible for the OPT STEM extension.
Please Note: Requirements for graduation, course offerings, course availability, track offerings and any other degree requirements are subject to change. Students should consult with an academic advisor prior to registering for any classes.
- A minimum of 32 units is required for the general M.S. in Healthcare Data Science degree
- Required courses: 20 units
- Data Science Elective Course: 4 units
- Health Elective Course: 4 units
- A minimum cumulative GPA of 3.0 is required for graduation