Introduction to Data Mining

4 credits

This course mainly focuses on introducing current methods and models that are useful in analyzing and mining real-world data. It will cover frequent pattern mining, regression and classification, clustering, and representation learning. All participants should be comfortable with programming, and with basic optimization and linear algebra. Prerequisites: (DSC 40B or CSE 12) and (DSC 80 or CSE 15L or CSE 29) and (MATH 180A or MATH 180B or MATH 181A or MATH 183 or MATH 186 or CSE 103 or ECE 109 or ECON 120A or MAE 108). Students may not receive credit for DSC 148 and CSE 158 or CSE 158R. Restricted to students within the data science or business data science major. All other students will be allowed as space permits.