Health Data Science - BS







The Bachelor's Program in Health Data Science is an innovative and interdisciplinary degree designed to provide a robust understanding of how data analytics, statistics, and machine learning can help address pressing public health challenges. In this program, students learn how to manage, analyze, and interpret complex health data and gain a strong foundation in public health principles, health policy, and population health. They study how to apply data science tools and methodologies to real-world public health issues such as epidemic tracking, health disparities, disease prevention, health promotion, and health services planning. This program combines epidemiology, biostatistics, health informatics, machine learning, and data ethics modules. Graduates are well-equipped to work in diverse settings such as public health departments, healthcare organizations, non-profit research institutions, and government agencies, where they can play pivotal roles in data-driven public health initiatives.

The BS in Health Data Science students develop exceptional analytical skills to take full advantage of the rapidly increasing public health, biomedical, and environmental data, and through diverse data integration and analyses, they can make powerful predictions for public health and biomedical outcomes. With these skills, our BS HDS students are uniquely prepared for professional admissions in fields such as 

  • Public Health
  • Biotechnology
  • Pharmaceutical industry
  • Allied Health
  • Government
  • Business 
  • Health Education
  • Health Services Administration
  • Law
  • Medicine, Nursing, and other health professions
  • Graduate programs in health data science, bioinformatics, biostatistics, computational biology, genomics, etc.


Examples of potential job roles:

Healthcare Data Scientist, Clinical Research Analyst, Healthcare Quality Analyst, Health Informatics Specialist, Healthcare AI Researcher, and Genomic Data Analyst.

A few examples of questions students will be able to answer as BS HDS graduates:
  • What are the key factors influencing patient readmission rates?
  • How can we identify patterns in patient health records to predict disease progression?
  • How can we analyze population health data to identify disease trends and patterns?
  • What statistical methods can be used to assess the effectiveness of public health interventions?
  • Can we develop predictive models to anticipate the spread of infectious diseases?
  • How can we leverage data analytics to optimize resource allocation in healthcare organizations?
  • What strategies can be employed to improve patient outcomes and reduce healthcare 
  • How can we develop algorithms for medical image analysis and disease detection?
  • Can we create interactive dashboards or visualizations to monitor population health trends?

See the HDS Program Guide and Undergraduate Handbook for more information and program policies.


TEAM Milken logo

Join T.E.A.M Milken!  T.E.A.M. Milken is open to all GWSPH undergraduate majors. Our goal is to provide individualized support to students so you will thrive at GW and be prepared to launch your public health career.

Per GW policy, undergraduate students may not take courses on-line during the fall or spring semesters. 

University General Education Requirements - all concentrations
Bachelor of Science in Health Data Science - Must Fulfill the Following Degree Requirements

General Education: 20 credits
Health Data Science Core (see program curriculum): 56-57 credits
Health Data Science Electives (pre-approved or approved by advisor): 10 credits
General Electives (to be chosen with advisor): 33-34 credits


Students must take on the approved Communications classes to meet the Gen Ed Communications requirement. See Program Guide for details.

Health Data Science Core Courses - all concentrations
Required Core HDS Courses – 57 credits
Programming and Data Processing

PUBH 4201 or CSCI 1011 or CSCI 1012 | Practical Computing (3 credit)
PUBH 4202 or CSCI 1112 | Bioinformatics Algorithms and Data Structures (3 credit)

Data Science

PUBH 1142 | Introduction to Health Data Science  (3 credits)
PUBH 1242 | Health Data Mining (3 credits)
PUBH 2242 | text mining/natural language processing (3 credits)
PUBH 3242 | Health Data Visualization (3 credits)


MATH 1231 | Calculus 1 (3 credits)
MATH 1232 | Calculus 2 (3 credits)


BISC 1111 | Biology: Cells & Molecules (4 credits)

PUBH 2110 or BISC 1112| Biology: Organisms or Public Health Biology (4 credits)

Probability and Statistics

PUBH 2142 | Introductory Biostatistics (3 credits)
TBD or STAT 4157 | Introductory Probability (calculus based) (3 credits)
TBD or  STAT 2118 or STAT 2183 | Regression Analysis or Applied Statistical Methods (3 credits)

Public Health

PUBH 1010 | First Year Experience in Public Health (1 credits)
PUBH 1101 | Introduction to Public Health and Health Services (3 credits)
PUBH 3131 | Introductory Epidemiology (3 credits)

PUBH 3199 | Research Methods in Public Health (3 credits)
PUBH 3136 or PUBH 3151 | Ethics in Public health or Health Law (3 credits)
PUBH 4199 | Independent Study (capstone project) (3 credits)

NOTE:  Students must earn a minimum of a C- in each Health Data Science core course, and earn a minimum GPA of 2.0 in the Health Data Science core to graduate.




Guided Electives - all concentrations

Number of credits vary by concentration shown in Concentrations Tab

Guided Electives-  the courses provided on the Guided Electives list have been identified as highly relevant to the BS in Health Data Science.  Each concentration indicates a minimum number of credits that must be selected from this approved list of 'guided elective' courses.  See Concentration TAB and program guide for more information.

For the most up to date list of program courses and program requirements, please reference the program guide or click the button below for EXNS and SPH course descriptions.


Non-Academic Requirements

Professional Enhancement

Students in GWSPH programs must participate in eight hours of Professional Enhancement. These activities may be Public Health-related lectures, seminars, or symposia related to your field of study.

Professional Enhancement activities supplement the rigorous academic curriculum of the SPH degree programs and help prepare students to participate actively in the professional community. You can learn more about opportunities for Professional Enhancement via the Milken Institute School of Public Health Listserv, through departmental communications, or by speaking with your advisor.

Students submit a completed Professional Enhancement Form to the Office of Student Records which is required documentation to be cleared for graduation.

Collaborative Institutional Training Initiative (CITI) Training

All students are required to complete the Basic CITI training module in Social and Behavioral Research.  This online training module for Social and Behavioral Researchers will help new students demonstrate and maintain sufficient knowledge of the ethical principles and regulatory requirements for protecting human subjects - key for any public health research.

Academic Integrity Quiz

All Milken Institute School of Public Health students are required to review the University’s Code of Academic Integrity and complete the GW Academic Integrity Activity.  This activity must be completed within 2 weeks of matriculation. Information on GWSPH Academic Integrity requirements can be found here.

Student Expectations and Policies

 Students are responsible for reviewing, understanding, and following the policies and requirements as outlined in the Undergraduate Student Handbook ( the University’s Bulletin (


Pre-Medical Professional

The Bachelor of Science (BS) in Health Data Science with Pre-Medical Professional Concentration program offers students the chance to acquire knowledge and skills in data science, statistics, machine learning and public health.

Concentration Requirements

BISC 1112 | Biology II (4 credits)
CHEM 1111 | General Chemistry I (4 credits)
CHEM 1112 | General Chemistry II (4 credits)
CHEM 2151/2153 | Organic Chemistry I (4 credits)
CHEM 2152/2154 | Organic Chemistry II (4 credits)
BISC 3261 or CHEM 3165 | Introduction to Biochemistry (3 credit)
PHYS 1011 or 1021 or 1025 | General Physics I (4 credits) 
PHYS 1012 or 1022 or 1026 | General Physics II (4 credits)

PSYC 1001 or SOC 1001 | Psychology or Sociology (3 credits)



124 Credits | TOTAL- Pre-Medical Professional Concentration

Guided Electives: the courses provided on the Guided Electives list have been identified as highly relevant to the BS in Health Data Science curricula.  A minimum of 9 credits are required to be selected from this approved list of 'guided elective' courses for the Pre-medical Professional concentration. 

General Electives: 18 additional credits can also be chosen from the Guided Elective list, or any other undergraduate course at the University, except LSPA designated courses.

For the most up to date list of program courses and program requirements and approved guided electives,  please reference the program guide.

Incoming freshman and external transfer students may apply directly to the major through GW admissions. Prospective GW students should review the undergraduate admissions page ( for details about the process. Internal transfer students accepted into the program matriculate in the semester following admission. We will accept transfers from students with a GPA of 2.75 or higher. Students should use the internal transfer form found on the Registrar’s website: The internal transfer application deadline is October 15th in the fall semester and February 15th in the spring semester. Students follow the prescribed curriculum effective in the year that they matriculate into the BS in Health Data Science program.


Dr. Ali Rahnavard, Program Director 

Dr. Juan Klopper

Dr. Qing Pan

Dr. Pramita Bagchi 

HERE is the complete list of DBB faculty