This elective is designed to provide students with a broad introduction to Natural Language Processing, which is one of the subfields of artificial intelligence as it relates to the interaction between machines and the (natural) languages of humans. This course explores the different approaches used to process and analyze natural language data (texts). We will look at the more practical aspects of NLP and how it is implemented in various applications/activities such as topic modeling, parts-of-speech tagging, sentiment analysis, spam classification, and machine translation.

This course is grounded on a combination of hands-on exercises and individual and group submissions. Each session will explore several new concepts, implementations, and a use case that may make use of them. Note that the order of these topics and assignments may change.