Chemistry 348 - Using Data Science to Find Hidden Chemical Rules

Chemists have always been interested in understanding patterns in their data. The scientific method uses observations to create theories and models to understand physical phenomena. Data science algorithms allow us to find unexpected patterns in chemical data. New chemical theories can be developed using a combination of data from either experiment or simulation, algorithms and physical insight. This class uses the case method providing three challenge problems to find hidden chemical rules from large chemical data sets through algorithms and physical insight. There will be lectures on the physical/chemical problems, the data sets, and the possible algorithms to consider before the teams of students tackle these problems. The teams will write papers on their findings and use the peer review process to improve their papers.

Prereq: MATH-102 and either any Chemistry or any Computer Science class.