This course focuses on foundations, techniques, applications and algorithms for conducting predictive analytics on Web data, including webpages, social media, ‘natural language’ documents and graphs. Students will learn the practical aspects of the techniques needed to build predictive analytical systems over Web data. Today, many of these systems are applications of machine learning, including supervised and unsupervised learning. Topics include social media analysis, information retrieval (including search and indexing), natural language processing (including information extraction and entity linking), knowledge discovery, cloud, and website analytics. The class will be run as a fast-paced lecture course with lots of student participation and significant hands-on experience. As an integral part of the course each student will do a project using the research and tools covered in the class. The class will occasionally feature guest lecturers with advanced knowledge in some of the covered topical areas. Here's a copy of the syllabus used in Fall 2019.