Environmental Health Data Science

Directors: Sen Pei, 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 Science is offering an 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 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.

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
  • 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

Competencies

Upon graduation, MS students in Environmental Health Data Science will be able to:

  • Apply data science methods to solving issues in the environmental health sciences
  • Demonstrate proficiency in programming, data analysis, and machine learning
  • Identify sources of data and demonstrate the ability to clean and organize data
  • Synthesize complex environmental health challenges from a public health perspective
  • Distinguish and appropriately apply data analysis statistical tool

Course Work

The curriculum, described in the handbook, is comprised of 36 credits of required courses, including a 1.5-credit research thesis (the “Master’s essay”) to be completed during the summer, and two selectives of 6 credits. Note that even if a course is waived, students must still complete a minimum of 36 credits to be awarded the MS degree.

View Courses in the EHS MS - Environmental Health Data Science Handbook

*This program can be completed on a part-time basis. For more information, please contact Nina Kulacki(link sends e-mail).

Contact Us

Nina Kulacki, MBA(link sends e-mail)
Director of Academic Programs
Department of Environmental Health Sciences
Columbia University
212-305-3466

More information on this program.