Data Science for Precision Health

Undergraduate Program

Precision Health is an emerging field that takes a big data approach in an attempt to precisely identify individual needs and conditions to enhance health and wellness through disease prediction and prevention. It shifts the healthcare paradigm from the traditional “reactive” approach, where a person is treated after a disease is diagnosed, to a newer “proactive” approach where disease prediction and prevention are emphasized.  IoT (Internet of Things) technology from search engines, health/fitness apps and websites, to wearable technology (i.e. Fitbit, Apple Watch) provide boundless data and endless opportunities for personalized medicine.

Career Paths

Although the use of big data in creative industries is relatively nascent, it is in high demand. There are plenty of career options for graduates with specialized training. Future occupations include, but not limited to the following:

●      Biostatistician
●      Bioinformatics scientist
●      Computational biologist
●      Bioinformatics programmer
●      Clinical analyst
●      Health informatics specialist
●      Healthcare IT project manager
●      Health informatics consultant
●      Privacy analyst
●      Healthcare data analyst

How to Apply

Learn more about admissions: take me to the admission application!


The BS in Data Science is a 125-semester credit curriculum with three major components: major requirements (77 credits), core general education courses (42 credits), and free electives (6 credits).

Major Core Courses

Mathematics, Statistics (28 Credits) and Computer Science  (21 Credits)
Code Courses Credit
DAS461 Directed Study: Career Development 2
DAS455 Senior Practicum 4
DAS451 Senior Project 4
CIS341 Cloud Computing and Big Data 3
CIS335 Machine Learning and Artificial Intelligence 3
CIS331 Data Mining 3
CIS221 Database System 3
CIS211 Introduction to Discrete Mathematics 3
CIS105 Data Structure and Algorithms 3
CIS102 Introduction to Computing 3
STA345 Nonparametric Statistics 3 (Elective)
STA341 Survival Analysis 3 (Elective)
STA335 Stochastic Processes 3 (Elective)
STA321 Design and Analysis of Experiments and
                      Quality Control
3 (Elective)
MAT207 Calculus III 3 (Elective)
STA331 Applied Regression Analysis 3
STA211 Statistical Theory and Methods 3
STA101 Principles of Probability and Statistics 3
STA205 Statistical Computing and Graphics
                      (R or SAS)
MAT106 Calculus II 3
MAT103 Linear Algebra 3
MAT105L Calculus Lab 1
MAT105 Calculus I 3
Precision Health Concentration (18 Credits)
Code Courses Credit
DAS341 Introduction to Computational Biology 3
ECO343 Health Economics 3
DAS342 Health Data Analytics 3
BMS231 Public Health & Epidemiology 3
BMS245 Introduction to Precision Health 3
BSC221 Genetics & Biotechnology 3

General Education Core

The College requires that all undergraduate students, regardless of major, complete core general education courses in nine distributions. Students of the Data Science program can meet the Quantitative Reasoning distribution requirement through their major courses. As a result, 42 general education credits from the Liberal Arts and Sciences program will be required.

Free Electives

Students are free to choose 6 credits from any college level courses offered by the College.