Public Health Data Analytics Concentration
The Public Health Data Analytics concentration in the Master of Public Health (MPH) program prepares students to harness innovative and advanced analytical tools and data science techniques to address pressing public health issues. By bridging foundational public health knowledge with cutting-edge data science methodologies, students gain advanced analytical skills using modern methodologies, such as AI, Machine learning, and GIS (Geographic Information System) to manage and analyze big population datasets. Through didactic and practical experience, students will gain hands-on experience to implement data analytical skills on a variety of large and complex public health datasets and learn how to thoughtfully interpret results. Courses in this concentration address a wide variety of topics, such as rigorous public health data modeling methodologies, epidemiological data analysis with R and Python programming, and machine learning and geo-informatics methods and applications in public health. Students can also take advantage of several AI educational and practical opportunities at the Icahn School of Medicine at Mount Sinai (https://icahn.mssm.edu/about/artificial-intelligence ).
Public Health Data Analytics Concentration Competencies
Apply quantitative, logical, or computational skills to public health research.
Translate public health questions into spatial and/or statistical hypotheses.
Construct and manage public health datasets for spatial and/or longitudinal studies using statistical software.
Develop analysis strategies tailored to public-health data characteristics and assumptions using traditional or AI-based methods.
Effectively analyze, interpret, and communicate complex public health data to public health audiences.
Public Health Data Analytics Concentration Requirements
MPH 5000 (Formerly MPH 0602) Introduction to Public Health Data Modeling
2
MPH 5001 (Formerly MPH 0413) Introduction to Epidemiology Data Analysis with R and Python
3
MPH 5002 (Formerly MPH 0601) Introduction to Geoinformatics in Public Health
3
MPH 5003 (Formerly MPH 0603) Machine Learning in Public Health
3
Students must choose an additional 11 elective credits in consultation with the Concentration Director
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