Curriculum

Equip yourself with the skills to transform the healthcare system.

12 months Program

30 Credits, Full-Time or Part-Time

Focus on emerging health technologies and concepts

What You’ll Learn

The Master’s of Science in Health Informatics & Data Science (HIDS) is a STEM program that focuses on technologies and concepts on how to leverage data science, big data, artificial intelligence, and machine learning applications to improve healthcare, especially in the fields of precision medicine, population health management, and value-based care.

HIDS courses align with American Medical Informatics Association (AMIA’s) core competencies for professionals in Health Informatics. They focus on human factors engineering and usability, imaging informatics, EHR data mining, and digital health applications. The mandatory Capstone Project is an integrative experience in which students intern in an organizations and use the culmination of skills acquired through the program to analyze a real-world problem with their mentor.

Program Takeaways

  • Understand new & emerging technologies applied in healthcare
  • Gain real world project experience in the classroom & through capstone projects with industry and government agencies
  • Practice scientific inquiry, problem solving and decision-making to improve human health
  • Apply methods and skills learned in class to integrate, mine, analyze and visualize data to improve patient outcomes and reduce healthcare costs

Degree Requirements

List of core & elective courses for the degree program can be found here.

Courses

Course Schedule

Example full-time and part-time student course schedules are available.

Course Schedule

Application Process

Apply now or learn more about the required application documents, application deadlines, tuition, available financial assistance, and answers to admissions FAQs.

Why a degree in Health Informatics & Data Science?

Healthcare is generating and collecting huge amounts of data, opening an abundant amount of positions in healthcare to analyze the data.