Introductory Health Data Science, Post-Baccalaureate Certificate (Beginning Fall 2026)
The Introductory Health Data Science Post-Baccalaureate Certificate is a 12-credit graduate-level program designed to provide students with foundational knowledge and practical skills in health data science. The curriculum includes coursework in programming, data management, and basic analytics, all tailored to health-related applications. The certificate is ideal for students and professionals seeking to enter the field of health data science, build core competencies, or enhance their ability to work with health data in clinical, research, or public health settings.
All courses included in the certificate are already part of the existing Master of Science in Health Data Science program at Saint Louis University. The program is designed to support a broad and diverse student population—including non-traditional and working learners—and serves as a valuable standalone credential or a steppingstone into the full MS degree.
Admission Requirements
- Complete Application form
- Transcripts from most recent degree(s)
- Résumé or curriculum vitae
- GRE not required
- Graduates apply appropriate statistical methods at a basic level.
- Graduates will effectively communicate the results of analyses at a basic level.
- Graduates will apply appropriate data-management strategies at a basic level.
| Code | Title | Credits |
|---|---|---|
| HDS 5000 | Foundations in Health Data Science | 3 |
| ORES 5160 | Data Management and Programming in Healthcare | 3 |
| HDS 5310 | Analytics, Statistics & Visualization Methods in Health Data Science | 3 |
| HDS 5330 | Predictive Modeling and Health Machine Learning | 3 |
| Total Credits | 12 | |
Roadmaps are recommended semester-by-semester plans of study for programs and assume full-time enrollment unless otherwise noted.
Courses and milestones designated as critical (marked with !) must be completed in the semester listed to ensure a timely graduation. Transfer credit may change the roadmap.
This roadmap should not be used in the place of regular academic advising appointments. All students are encouraged to meet with their advisor/mentor each semester. Requirements, course availability and sequencing are subject to change.
| Year One | ||
|---|---|---|
| Fall | Credits | |
| HDS 5000 | Foundations in Health Data Science | 3 |
| ORES 5160 | Data Management and Programming in Healthcare | 3 |
| Credits | 6 | |
| Spring | ||
| HDS 5310 | Analytics, Statistics & Visualization Methods in Health Data Science | 3 |
| HDS 5330 | Predictive Modeling and Health Machine Learning | 3 |
| Credits | 6 | |
| Total Credits | 12 | |
For more information about this program, contact:
Department of Health and Clinical Outcomes Research
hcorgrad@health.slu.edu