340.626.79
Introduction to Text Analytics Methods for Public Health Research
Location
Internet
Term
Summer Institute
Department
Epidemiology
Credit(s)
3.5
Academic Year
2026 - 2027
Instruction Method
Online Synchronous (at least one synch session/week)
Start Date
Monday, June 8, 2026
End Date
Friday, June 19, 2026
M, Tu, W, Th, F, 8:30 - 11:50am
Auditors Allowed
No
Available to Undergraduate
No
Grading Restriction
Letter Grade or Pass/Fail
Course Instructor(s)
Contact Name
Frequency Schedule
One Year Only
Resources
Prerequisite
No prerequisites for this course.
Enrollment Restriction
This course is not restricted.
Provides practical skills for analyzing unstructured text data in public health. Teaches how to clean, structure, and extract meaningful information from text using text-analytics methods, along with an introduction to Natural Language Processing and AI tools. Emphasizes hands-on coding and applies text-derived insights to epidemiologic research.
Learning Objectives
Upon successfully completing this course, students will be able to:
- Prepare and preprocess unstructured text data for use in public health and epidemiologic analyses.
- Apply core text-analytics methods to extract meaningful information from textual sources such as surveys, clinical notes, and public-facing data
- Use introductory Natural Language Processing and AI tools to enhance text analysis and support public health research questions.
- Integrate text-derived features into analytic workflows using reproducible coding practices.
Upon successfully completing this course, students will be able to:
Methods of Assessment
This course is evaluated as follows:
- 20% Participation
- 40% Assignments
- 40% Project(s)