Advanced Health Data Science, Post-Baccalaureate Certificate (Beginning Fall 2026)
The Advanced Health Data Science Post-Baccalaureate Certificate is a 9-credit graduate-level program designed to provide focused, high-impact training in advanced analytical methods, predictive modeling, and applied health data science. The certificate is tailored for professionals and graduate-level students seeking to enhance their technical skills in health data science without committing to a full degree program, making it an ideal option for those in clinical, academic, or public health roles who need specialized training to keep pace with data-driven innovations in healthcare.
All courses included in the certificate are currently offered as part of the Master of Science in Health Data Science at Saint Louis University. By offering a flexible, stackable credential that can serve as a standalone qualification or a gateway to the full master’s degree, the program meets current workforce demands while enhancing SLU’s reputation as a leader in mission-driven, equity-focused health data science education.
Admission Requirements
- Complete Application form
- Transcripts from most recent degree(s)
- Résumé or curriculum vitae
- GRE Not Required
- Graduates will apply appropriate methods to analyze large, numeric non-numeric data, both real and AI-generated.
- Graduates will effectively communicate the results of analyses of both numeric and non-numeric data, both real and AI-generated.
- Graduates will demonstrate an understanding of ethical aspects of real and AI-generated data.
| Code | Title | Credits |
|---|---|---|
| HDS 5230 | High-Performance Computing and Health Artificial Intelligence | 3 |
| HDS 5430 | Health Image Processing and Deep Learning | 3 |
| HDS 5530 | Natural Language Processing and Large Language Models in Healthcare | 3 |
| Total Credits | 9 | |
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 5430 | Health Image Processing and Deep Learning | 3 |
| HDS 5230 | High-Performance Computing and Health Artificial Intelligence | 3 |
| HDS 5530 | Natural Language Processing and Large Language Models in Healthcare | 3 |
| Credits | 9 | |
| Total Credits | 9 | |
For more information about this program, contact:
Department of Health and Clinical Outcomes Research
hcorgrad@health.slu.edu