CS 3530 - Natural Language Processing

3 unit(s)

This class will provide students with background and training in basic programming and computational methods to gain the skills necessary to apply natural language processing (NLP) techniques to a wide variety of data sets. In this course, students will learn how computers process human language, explore common NLP techniques, and apply them to real-world tasks like sentiment analysis, text classification, and chatbots. In addition, students will learn the theory, practice, and ethics of data collection and use. No prior programming experience is required.

Satisfies: GE Area UD-2

Course Learning Outcomes List
Students will:

Be able to explain the basic principles behind natural language processing (NLP);
Be able to use key NLP techniques, including data preparation, text classification, sentiment analysis, and named entity recognition;
Be able to use Python tools to apply NLP to real-world problems (PLO #1.2);
Be able to find data, work in a team to use techniques learned in class to process the data, and present their findings; and,
Explain the ethical challenges and biases of NLP models, their impact on society, as well as issues surrounding the collection and representation of data.

Schedule of Classes | University Bookstore