Many organizations need to analyze large amounts of text to discover useful information. For example, a company may want to monitor how the public discusses its products in social media, or a forensics team may need to discover the contents of disk drives seized by law enforcement. This course provides students with an understanding of common and emerging methods of organizing, summarizing, and analyzing large collections of unstructured and lightly-structured text ('text analytics'). The focus is on algorithms and techniques, however the course also provides an introduction to open-source software tools
This is a 6 unit course. It is offered during the second half of the Fall (Mini-2) and Spring (Mini-4) semesters.
Learning ObjectivesBy the end of the course, students are expected to have developed the following skills. Skills are assessed by the homework assignments and the final exam.
- Recall and discuss common methods of conducting exploratory and predictive analysis of text information;
- Use search engines and common open-source software to perform common methods of exploratory and predictive analysis; and
- Apply text analysis techniques discussed in class to solve problems faced by governments and companies
Faculty: Jamie Callan
Course Format: Online
Check the original course description for the most updated information.