BHI 510 - Geospatial, Temporal & Network Data Science

The objective of this course is to develop an understanding and practice of geospatial, temporal, and textual data and their analysis for decision analytics and data science in healthcare, health research, and public health. The course provides methods of description, estimation, testing, prediction, and clustering developed for geospatial, temporal, and textual models. Concepts, methods, and applications are emphasized, rather than theory. Topics include spatial statistical inferences, variograms, spatial autoregressive models, time series representation, time series prediction, survival analysis, temporal clustering, spatial clustering, machine learning methods, text summarization, text classification, and text clustering.

Prerequisite: Graduate standing or instructor permission
When Offered:

Credit: 3