Master of Science: Environmental Health Data Science Degree Program

Master of Science: Environmental Health Data Science Overview

Director: Tiffany Sanchez, PhD

The field of Environmental Health Science has become increasingly dependent on the use of massive and complex data sources. Understanding how to work with, analyze, and interpret data used in the context of Environmental Health has rapidly become a highly valued, yet uncommonly taught, skill set. The Department of Environmental Health Sciences (EHS) is offering a Master of Science (MS) track in Environmental Health Data Science. The curriculum is designed to educate students in the field of environmental health and to provide the quantitative skills needed to work with and analyze these complex environmental health data sources used in the environmental health sciences, including geospatial modeling, advanced statistics, and data management.

In addition to completing rigorous coursework, students gain valuable practical experience by completing a thesis. The thesis research project is meant to apply the skills that they have learned to an environmental health issue by working with data.

MS Environmental Health Data Science Program Requirements

The Data Science track is designed to be completed in 12 months but can accommodate part-time students, who may take up to three years to complete the Master's program. 

 Students in this program will complete: 

  • 36 credits of course work (listed below)
  • A Master’s Research thesis 

Educational Goals

The Department’s Environmental Health Data Science MS degree program will prepare students to: 

  • Develop relevant programming skills in “R”  
  • Write computationally efficient code 
  • Gain a strong knowledge base in Environmental Health Science and Biostatistics  
  • Work with imperfect/real-world data sets  
  • Rigorously critique data science-based research in environmental health  
  • Develop a data science-based model to and analyze data used in environmental health

Environmental Health Careers

Graduates with a Master of Science degree in Environmental Health Data Science are well qualified for environmental health and data science careers in local and regional departments of health, federal agencies such as the NIH, EPA, FDA, CDC, private companies, non-governmental organizations, and careers in research in academia, medicine, industry, and the military.


Requirements and submission instructions can be found here. 

Prerequisites: Students from a wide range of backgrounds are acceptable candidates for this program. Applicants may have an undergraduate degree in any field, but should have some background or coursework in college mathematics, including at least a year of calculus.

Application Deadline: Priority deadline December 1, final deadline June 1 to begin studies the following fall.

Application Components: 

  • College transcript(s)
  • GRE scores (Optional)
  • A personal statement
  • Three letters of reference

Course Work

Required Courses (36 Credits):

  • *Introduction to Public Health- programming
  • P6300 Environmental Health Sciences 
  • P6370 Journal Club in Molecular Epi and Toxicology 
  • P6400 Principles of Epidemiology I 
  • P8105 Data Science I
  • P8106 Data Science II 
  • P8130 Biostatistical Methods I 
  • P8131 Biostatistical Methods II 
  • P8322 Environmental Health Sciences II 
  • P8332 Advanced Analytic Methods in EHS  
  • P9361 Master’s Thesis I
  • P9380 Advanced GIS and Spatial Analysis 
  • *3 credit Selective list I (pick 1)
  • *3 credit Selective list II (pick 1)

Program Requirements*

FALL (15 Credits)

  • P6300 Environmental Health Sciences 
  • P8105 Data Science I
  • P8130 Biostatistical Methods I
  • P6400 Principles of Epidemiology I

3 credit Selective list I (pick 1)

  • P8307 Molecular Epidemiology 
  • P8312 Principles of Toxicology 

SPRING (18 Credits)

  • P8322 Environmental Health Sciences II
  • P8106 Data Science II
  • P8131 Biostatistical Methods II
  • P9380 Advanced GIS and Spatial Analysis
  • P6370 Journal Club in Molecular Epi and Toxicology
  • P8332 Advanced Analytic Methods in EHS

3 credit Selective list II (pick 1)

  • P8326 Public Health Epigenetics 
  • P8334 Computational Toxicology 
  • P8451 Machine Learning for Epi and Public Health 
  • P8477 Epi Modeling for Infectious Disease 

SUMMER (3 Credits)

  • P9361 - Master's Essay Research I

*This program can be completed on a part-time basis. For more information, please contact Nina Kulacki.

Contact Us

Nina Kulacki, MBA
Director of Academic Programs
Department of Environmental Health Sciences
Columbia University

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