Hacking the Matrix to Discover Patterns in Science, the Arts, and Society How can twitter-feeds reveal public opinion? Who authored the works of Shakespeare? How do you know when you have the "right" answer when analyzing data? Computational, statistical, and informatics/algorithmic methods can analyze any data that are captured in digital form, whether it be text, sequential data in general (such as experimental observations over time, or stock market and econometric histories), symbolic data (genomes), or image data. Informatics offers a means to see or discover patterns and relations without the filter of an "expert." Controversial issues such as implicit bias regarding gender, race, sexual orientation, and social status can often be revealed in an impartial way with the simplest informatics analyses, and when presented in a data mining context these problems can at last be acknowledged and addressed.
In this class, students will learn how to mine data to identify statistical anomalies or "signatures," revealing patterns and truths in a profoundly convincing way. Informatics provides a new means of analysis for many different disciplines, from the sciences to the arts and humanities. Course projects may include developing tools to predict specific genes in a genome, analyze twitter-feeds for public opinion surveying, study signals for nanopore detectors, search text for multiple meanings in the writings of Machiavelli, and determine authorship via iambic styles of different authors.




As a ConnCourse, this class will make connections across the liberal arts.

Enrollment Limit

Enrollment limited to 24 students.