Graduate Course Descriptions

The following directory lists the graduate courses which the University expects to offer, although the University in no way guarantees that all such courses will be offered in any given academic year, and reserves the right to alter the list if conditions warrant. Click on the links below for a list of courses in that subject area. You may then click “View Classes” to see scheduled classes for individual courses.

5643. Text Analytics

3.00 credits

Prerequisites: EPSY 5641. Recommended preparation: This course requires an understanding of introductory statistics and regression at the level of EPSY 5605 and EPSY 5610 as well as some prior experience with statistical programming in a language like R or Python.

Grading Basis: Graded

This course provides an applied introduction to text analytics with special emphasis on its application to education. Students will learn to use common toolkits in the Python ecosystem to analyze large-scale text data in order to generate insights into educational, cognitive, and social processes.


Last Refreshed: 28-MAR-24 05.20.12.635703 AM
To view current class enrollment click the refresh icon next to the enrollment numbers.
Term Class Number Campus Instruction Mode Instructor Section Session Schedule Enrollment Location Credits Grading Basis Notes
Spring 2024 9942 Storrs In Person Anglin, Kylie 001 Reg We 2:30pm‑5:00pm
15/20 FSB 202 3.00 Graded EPSY 5641. Recommended preparation: This course requires an understanding of introductory statistics and regression at the level of EPSY 5605 and EPSY 5610 as well as some prior experience with statistical programming in a language like R or Python