Two courses are required for the certificate program
- Introduction to Data Structures and Algorithms in Python (PQHS 413)
- Computing in Biomedical and Health Informatics (PQHS 416)
You then select two courses from one of the following concentrations
- Health Informatics
- Clinical Research Informatics
- Bioinformatics
If you are interested in a 15-credit certificate, then you will select one additional elective from any of the concentrations or another elective in consultation with your academic advisor. A 15-credit certificate will appear on a Case Western Reserve transcript.
Courses in the concentrations are listed below. For complete descriptions, download the Biomedical & Health Informatics Certificate PDF.
Health Informatics
- CRSP 401 (3 Credit Hours) 鈥� Introduction to Clinical Research Summer Series OR PQHS 431 (3 Credit Hours) 鈥� Statistical Methods I
- PQHS 471 (3 Credit Hours) 鈥� Machine Learning & Data Mining
- EBME 473 / SYBB421 (3 Credit Hours) 鈥� Fundamentals of Clinical Information Systems
- HSMC 412 (3 Credit Hours) 鈥� Lean Service Operations
- HSMC 420 (3 Credit Hours) 鈥� Health Finance
- HSMC 456 (3 Credit Hours) 鈥� Health Policy and Management Decisions
Clinical Research Informatics
- CRSP 401 (3 Credit Hours) 鈥� Introduction to Clinical Research Summer Series OR PQHS 431 (3 Credit Hours) 鈥� Statistical Methods I OR MPHP 405 (3 Credit Hours) 鈥� Statistical Methods in Public Health
- PQHS 471 (3 Credit Hours) 鈥� Machine Learning & Data Mining
- PQHS 515 (3 Credit Hours) 鈥� Secondary Analysis of Large Health Care Data Bases
- EBME 473 / SYBB 431 (3 Credit Hours) 鈥� Fundamentals of Clinical Information Systems
- MPHP 458 / PQHS 458 (3 Credit Hours) 鈥� Statistical Methods for Clinical Trials
- MPHP / PQHS 468 (3 Credit Hours) 鈥� The Continual Improvement of Healthcare: An Interdisciplinary Course
Bioinformatics
- PQHS 451 (3 Credit Hours) 鈥� A Data-Driven Introduction to Genomics and Human Health
- EECS / SYBB 459 (3 Credit Hours) 鈥� Bioinformatics for Systems Biology
- PQHS 471 (3 Credit Hours) 鈥� Machine Learning & Data Mining