In this two-week course, students will learn a variety of natural language processing methods for analyzing and extracting meaning from text data. The course will start with an introduction to text data, including text preprocessing and exploratory methods. The topics that follow will include machine learning models used for topic modeling, clustering, classification, sentiment analysis, and word embeddings. Students will also be introduced to web scraping. Considerations to both long and short texts of various subject matter. Class examples will be demonstrated primarily in R. This course assumes a bachelors-level background in Statistics or related field and knowledge of R or Python; no prior knowledge of text analysis is assumed.
1 course hour
Instructor: Robyn Ferg