Text Analytics

In this course, participants learn the essentials of Text Analytics. We start by outlining the conceptual foundations. A next chapter reviews some applications of Text Analytics from our own research. Next, we discuss various text preprocessing and representation methods to convert raw text documents into a numeric representation. We then zoom into various applications of text analytics such as visualisation, concept extraction, topic modelling, document clustering and text classification. The course concludes by illustrating how the concepts taught can be implemented in R. The subjects discussed in this course are based on our own experience of doing text analytics projects for more than 10 years now.

The course provides a sound mix of both theoretical and technical insights , as well as practical implementation details. These are illustrated by several real-life case studies and examples. Throughout the course, the instructors also extensively report upon their research and industry experience .

The course features more than 4 hours of video lectures, more than 50 multiple choice questions, and various references to background literature. A certificate signed by the instructors is provided upon successful completion.

Example real-life cases of Text Analytics in R are also provided and extensively discussed.