: This course is designed to introduce business school students to natural
language processing (NLP), which is a field of artificial intelligence. NLP, or computational
linguistics, studies approaches and provides tools for analyzing and understanding human
language. NLP is ubiquitous as we use many of its applications in our everyday living; from
sentence autocompletion to virtual agents and assistants. With the abundance of readily
available textual data, NLP approaches are becoming important tools for performing advanced
analysis and research in finance.
In this course we will cover a wide range of NLP topics which include: language models, text
classification, tagging, dependency parsing, topic modeling, word embeddings, transformers,
coreference resolution, named entity recognition, and sentiment analysis. We will also cover
various machine learning approaches used in NLP which include neural networks.
Throughout the course students will learn about the problems and challenges that NLP
addresses and the algorithms to solve them. With a series of guided lab sessions students will
gain practical experience in implementing the learned methods in Python. At the end of the
course students will be able to implement the knowledge gained in their own research work.
Division: Finance