Spatial Data Science in Healthcare
** available as of 06/15/2026
** available as of 06/15/2026
This course is a comprehensive introduction to spatial data analysis and visualization using programming languages (R or Python). Modules will cover core concepts and practical applications of spatial data handling within these tools. The content is structured to progressively build knowledge, starting from basic principles and advancing to more complex analytical techniques.
Outcomes: 1) Differentiate various spatial data formats and structures, including vector and raster data; 2) Demonstrate proficiency in importing, processing, and managing spatial datasets using programming languages, ensuring data integrity and analytical readiness; 3) Produce informative, aesthetically compelling visualizations of spatial data to effectively communicate spatial insights; 4) Interpret spatial patterns, relationships, and trends using statistical methods to derive meaningful conclusions.
Outcomes: 1) Differentiate various spatial data formats and structures, including vector and raster data; 2) Demonstrate proficiency in importing, processing, and managing spatial datasets using programming languages, ensuring data integrity and analytical readiness; 3) Produce informative, aesthetically compelling visualizations of spatial data to effectively communicate spatial insights; 4) Interpret spatial patterns, relationships, and trends using statistical methods to derive meaningful conclusions.