This course introduces students to statistical and machine learning tools for modeling unstructured data; including emails, documents, text messages, and social media data. Topics to be covered include generalized linear models, decision trees for discrete data, k-means clustering, mixture models, and topic models. The course integrates numerous case studies to demonstrate practical approaches to analyzing large unstructured collections of data. Application areas include Marketing (Yelp and Trip Advisor reviews), Human Resources (healthcare plan analysis), Social media (Twitter, YouTube, and Instagram). The course delivery will be a mix of lectures, readings with discussion, and hands-on data analysis. Prereq: DS 805.