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INTRODUCTION TO TEXT MINING

LIS 501
Course Description

Introduces computational methods and tools for processing, analyzing, and understanding text data. Topics include text data preparation and preprocessing, models of text content and meaning, exploratory text analytics, text classification, information extraction from texts, ethical issues in natural language processing (NLP), and related applications in information sciences and other fields. Develops practical skills to design and implement text mining solutions using popular NLP tools and programming packages.

Prerequisites

Junior standing and Satisfied Quantitative Reasoning (QR) A requirement or graduate/professional standing

Satisfies

This course does not satisfy any prerequisites.

Credits

Not Reported

Offered

Not Reported

Grade Point Average
2.89

-19.63% from Historical

Completion Rate
77.78%

-17.59% from Historical

A Rate
44.44%

-39.86% from Historical

Class Size
27

-24.1% from Historical

Cumulative Grade Distribution

Instructors (2026 Summr)

Sorted by ratings from Rate My Professors

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