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Health Data Science: Frequently Asked Questions

Below we provide answers to frequently asked questions about the M.S. in Health Data Science. 

two students being instructed by a professor in front of a whiteboard.
Is work experience required?
No. While work experience can be beneficial, it is not required for admission.
How many letters of recommendation are required?
We require only one letter of recommendation. This letter can be written by a current employer, former employer, or a previous instructor.
Is it possible to finish the program in two semesters?
No. The program has been specifically designed to be taken in sequence to be completed over three or four semesters. Due to the amount of credits and requirements for the degree, finishing in two semesters is not possible.
Am I able to apply before I have completed any of the eligibility requirements (e.g., undergraduate degree, coursework, etc.)?
Yes. If you indicate on your application that the requirements will be fulfilled before the start of the program, you can apply.
Do my GRE scores need to be submitted before the application deadline?
We do not require G.R.E. scores for our M.S. in Health Data Science program.
Is the program more research or career-oriented?
The program is more career-oriented and is intended to be a terminal degree that prepares students for a career in a related field. However, the skill set learned is also beneficial for a research-oriented career or future degree.
Do you need a background in biomedicine, health or clinical sciences?
No prior biomedicine, health, or clinical sciences knowledge is required for admission. Our curriculum is focused on statistics and computing with health science applications. 
Are courses more focused on medicine because of the "health" in health data science?
No. Most courses focus on statistical and computational methods that are commonly used in the analysis of clinical data, and the courses do not require prior knowledge of health or clinical sciences.
How can I better prepare myself for the application?
Proficiency in a computer programming language, such as R. or Python, is helpful for eligibility of admission. The best way to prepare yourself is to take mathematics, statistics, and computing courses at academic institutions. You may also complement your skill set by taking additional courses online, such as EdX or Coursera. 
What constitutes as adequate statistical training?
Courses in probability and statistical inference are highly recommended but not required for admission to the M.S. in Health Data Science program.
Is academic or industry training better preparation for the application and program?
Industry training is not a requirement for admission but does show interest and experience in the field. Industry training is also not a requirement for the program but may be helpful during the program. Academic training is beneficial before starting the program. 
How is the Health Data Science program different from other data science programs?
We provide interdisciplinary training in statistics, computing and health science. Specifically, our program has a strong focus on integrating statistical inference and big data computing with solving important problems in health care. We emphasize the importance of statistical inference and scalable computational tools, and students gain a firm foundation in health science in our curriculum. Students are trained to become interdisciplinary quantitative leaders in analyzing and interpreting massive and complex data in health sciences.
What does "health data" mean, and why is it important?
Health data refers to any data that pertains to the biomedical sciences and public health. Data sets might originate from observational studies, clinical trials, computational biology, electronic medical records, health care claims, genetic and genomic epidemiology and environmental health, network health science, and many other fields.
Can I take courses in other programs at SLU?
Yes. Students can cross-register for courses at all Saint Louis University schools and colleges. However, only graduate-level courses may be taken. Please note that additional courses will not count toward credit for the degree requirements.
What is your capstone course?
This is a project-based research course that will allow students to gain practical skills in analyzing and interpreting different types of big data in health care. Each student will work with an organization of their choice and preceptor from the organization. In addition, a faculty member from the department will oversee the capstone course completion. 
What resources are available to me as a student?
There are a multitude of resources available to students, including networking opportunities, career services and research opportunities with faculty and other researchers.
Can I enroll as a part-time student? 
Students can enroll as a full-time or part-time student. 
Could I start the program in the spring semester?
Yes. We have both fall and spring entry into our program.
What opportunities await me after graduation?
Our graduates are employed as data scientists, data managers, data analysts, machine learning engineers, statisticians, software engineers, and quantitative analysts in academia, government and industry. It is also possible for students to further their education in a doctoral program in a related field.
If I pursue a career outside of health after degree completion, is the skill set transferable?
Absolutely. While many of the examples and problems in the course curriculum will center around current topics in health care, the statistical and computational skill set and tools obtained are broadly applicable to many areas of data science.
Where can I apply?

Additional information about admission requirements can be found here: 

View Application Info

What does the program cost?

Cost per credit hour is $1250. The M.S. in Health Data Science requires 30 credit hours of course work. For more information on tuition and costs, visit Student Financial Services:

View Financial Aid 

What is O.P.T. and STEM O.P.T.?

O.P.T. is one type of work permission available to certain F-1 nonimmigrant students. It allows students (except those in English language-training programs) to obtain real-world work experience directly related to their field of study.

The STEM O.P.T. extension is a 24-month extension of O.P.T. available to F.-1 non-immigrant students who have completed 12 months of O.P.T. and received a degree in an approved STEM field of study as designated by the STEM list.