Health Data Science (Certificate)
Degree Offered: Certificate
Program Leadership:
John Kornak, PhD, Program Director
Thomas Hoffmann, PhD, MA, Associate Program Director
Admissions Inquiries:
Eva Wong-Moy, Graduate Affairs Manager
Program Description
The Certificate in Health Data Science (CiHDaS) is one-year program, ideal for those already working in the biomedical or pharmaceutical industries, focused on applying data science, biostatistics, machine learning, and epidemiological thinking in clinical research settings.
The CiHDaS program is intended for:
- Quantitative science learners interested in studying data science with a focus on biomedical applications.
- Numerically able biomedical scientists interested in applying data science methods in clinical, epidemiological and biological sciences.
Data science and biostatistical tools are increasingly necessary to accommodate the growing emphasis on precision and evidence based-medicine, the widespread analyses of electronic health records, and the improved capabilities to collect and store massive datasets.
We also offer a Master’s of Science in Health Data Science (MiHDaS) as a two-year program that includes a capstone research project, teaching and industry experience.
Admission Requirements
- Bachelor’s degree (BA/BS) or the equivalent from an accredited institution in a quantitative or biomedical science, or related field, with a minimum grade point average of 3.0.
- In addition to meeting the same admission requirements domestic students must meet, international applicants must also demonstrate proficiency in English. There are two ways to meet this English language proficiency requirement, which are outlined on the Graduate Division’s International Admission Requirements webpage. Please note that the Health Data Science program minimum internet based TOEFT iBT score is 100.
- Transcripts
- Three letters of recommendation
- Resume or curriculum vitae
- Statement of Purpose
- Personal History Statement
Learning Outcomes
To complete the program, scholars must satisfy program objectives, which are to:
- Learn a broad set of data science research methods and the techniques needed for the application of data science across biomedicine applications and research.
- Gain understanding of key issues that are particularly pertinent to the health sciences and evidence-based medicine, such as bias, confounding, interpretability, and causality.
- Plan and implement one or more health-related data science analysis projects.
- Analyze, interpret, and present data science research results.