BDA833 NLP Text Analytics

[3–0, 3 cr.]

The purpose of this course is to familiarize business school students with the artificial intelligence field of natural language processing, or NLP. Computational linguistics, or NLP, explores methods and offers resources for deciphering and analyzing spoken language. Because we use so many of NLP’s applications in our daily lives—from virtual agents and assistants to phrase autocompletion—it is widely used. NLP techniques are increasingly being used as vital instruments for conducting sophisticated analysis and research in the field of finance due to the volume of easily accessible textual data. Language models, text classification, tagging, dependency parsing, topic modeling, word embeddings, transformers, coreference resolution, named entity identification, and sentiment analysis are just a few of the many NLP subjects that will be covered in this course. We will also go over the many machine learning techniques, such as neural networks, that are applied in NLP. Students will gain knowledge of the issues and difficulties that NLP tackles, as well as the algorithms used to resolve them, throughout the course. Students will also be able to use the knowledge they have learned in their own research projects by the end of the course.