INFO 2950 - Introduction to Data Science

(MQR-AS, SDS-AS)

Fall. 4 credits. Letter grades only.

Prerequisite: MATH 1710 or equivalent, CS 1110 or CS 1112, or permission of instructor. Information Science majors must complete this class prior to their senior year.

M. Wilkens.

Teaches basic mathematical methods for information science, with applications to data science. Topics include discrete probability, Bayesian methods, graph theory, power law distributions, Markov models, and hidden Markov models. Uses examples and applications from various areas of information science such as the structure of the web, genomics, social networks, natural language processing, and signal processing. Assignments require python programming.