INST 420
Data Applications in Global Health
Explores the impact of data on global health research and practice. Identifies, analyzes and interprets health data on a global scale, and explores the distribution and utilization of data to impact public health outcomes. Topics include machine learning, geospatial analysis, data visualization and data ethics.
Topics
- machine learning
- geospatial analysis
- data visualization and data ethics
Topics explicitly listed in official catalogue description
Prerequisites & course information
Prerequisite: Minimum grade of C- in EPIB315 or INST314 ; or other upper-level statistics course. Recommended: GBHL200 , SPHL100 , or related coursework in global health, medical anthropology, or global politics and development. Restriction: Must have earned a minimum of 60 credits.
Sources
- Course catalogue ↗2026-2027
- Catalogue entry ↗
Catalogue variants
- Data Applications in Global Health · 3 Credits