This certificate prepares clinicians, health care managers, statisticians, epidemiologists, computer programmers, data analysts, and other professionals in analysis of complex health care data, including data extracted from electronic health records, claims data, and consumer generated data. Since electronic health records and related data repositories are becoming increasingly more massive, the certificate emphasizes topics related to big data analysis. Data mining, propensity scoring, and other advanced analytic techniques covered in the certificate can handle complex problems typically found in observational data: large, multidimensional and multi-type data sets, with many confounding issues and noise. These techniques can be computationally efficient on large scale analysis and intelligent in predicting an outcome.

This certificate qualifies for Title IV Federal Financial Aid.


Applicants must hold a bachelor's degree from a an institution of higher education accredited by a Mason-recognized U.S. institutional accrediting agency or international equivalent and must have a minimum of a 3.0 GPA to be considered. Applicants must meet the admission standards and application requirements specified in Graduate Admissions  and must apply using the online Application for Graduate Admission. The application process is competitive, and applications are considered for the fall and spring semesters. For application deadlines and detailed application requirements, refer to the College of Public Health Admissions website.


For policies governing all graduate certificates, see AP.6.8 Requirements for Graduate Certificates.

Banner Code: PH-CERG-HIDA

Certificate Requirements

Total credits: 18

This certificate may be pursued on a full-or part-time basis.

Students must complete at least 18 credits of required courses with a grade of B or better.  The course content and syllabi are also available at the program website and by contacting

Required Courses

Students must complete six of the following:18
Computational Tools in Health Informatics
Health Care Databases
Advanced Statistics in Health Services Research I
Health Data Integration
Statistical Process Control in Healthcare
Health Data Visualization
Data Mining in Health Care
Radiology Informatics
Comparative Effectiveness Analysis using Observational Data
Advanced Health Data Mining
Total Credits18