Natural Language Processing

This class on natural language processing (NLP) will cover issues such as topic modeling, text summarization and classification, sentiment analysis, large language models, and automatic scoring of a students written response, including essay scoring. NLP provides essential methods for dealing with large amounts of text data created when sourcing information from the web and other large text corpora. Practical exercises in this class will help improve student awareness around fairness, bias, and human-centered data science by providing students with opportunities to learn and apply methods for dealing with large amounts of real-world text data. The techniques taught in this class will help to improve the accuracy and fairness of predictions made by machine learning models and can also help to improve the interpretability of those models.