Master of Science in Precision Health

Curriculum

Earn your Master of Science degree in Precision Health in as little as one year. The program consists of 10 courses, including a summer capstone project. Coursework covers the foundations of precision health, including epidemiology and population health, bioinformatics, biostatistics, and inclusion and equity in precision health. Additionally, all students will develop expertise in an area of concentration: data science, clinical research, or entrepreneurship in medicine. The curriculum encompasses three components:

6 core courses + 3 concentration courses + 1 capstone course

Core Courses

Six core courses are required of all students.

  • Principles of Precision Health
  • Applied Precision Health
  • Clinical Epidemiology
  • Healthcare Data Sciences I (previously Introduction to Biostatistics)
  • Healthcare Data Sciences II (previously Applied Regression Analysis)
  • Introduction to Biomedical Informatics 

Capstone

All students will complete a capstone project that puts into practice the knowledge and skills learned during the program. Students will work with a faculty mentor who will provide guidance and feedback throughout the capstone experience. The capstone class will provide instruction on project design and management, literature reviews, research and referencing, and writing and presentation. The final project may be research-based or applied, depending on the student’s interests and career objectives. A final presentation will complete the capstone project. 

*Please note that the courses listed above are representative. Course offerings and titles may change from year to year. 

Concentration-Specific Courses

Each concentration requires three courses. The courses listed below are representative; other electives may be possible with approval from the instructor and Program Director.

Data Science track
Machine Learning and Artificial Intelligence in Precision Health Research
Computational Biology: A Machine Learning Approach
Computer Programing for Population Health
Causal Inference in Machine Learning
Machine Learning and Large-scale Data Analysis

Clinical Research track
Introduction to Clinical Trials
Computer Programming for Population Health
Pharmacogenetics and Pharmacogenomics
Epidemiologic Methods

Entrepreneurship track
Innovation in Healthcare Practice
Innovation within the Constraints of the U.S Healthcare System
Launching a Bioscience Venture
Healthcare Entrepreneurship 

 

Selective MsPH Capstone Titles

  • The impact of Race, Age, Gender, and Income on Postoperative Complication Outcome in All of US.
  • Reproductive and Genetic Factors Associated with Female Lung Cancer: A Case-Control Analysis Using the All of US Cohort Study
  • Exploring Minor Allele Variants Modulating the Risk of Sexually Acquired HIV-1: Implications for Precision Health Interventions
  • Analyzing the Connection Between Periodontitis and Rheumatoid Arthritis
  • Link genetic, environmental. clinical, SDOH, financial data to understand which medication will be effective in patients with migraine/headaches

Timeline

A full-time course load is 3 courses per quarter (autumn, winter, spring), plus the capstone class in summer quarter. Students attending full-time can complete the program in on year. Part-time arrangements may also be available.

 

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