DASC 32103 — Statistical Learning
is a course providing an in depth look at the theory and practice of applied linear modeling for data science: including model building, selection, regularization, classification and prediction. Students will gain hands-on experience using statistical software to learn from data using applied linear models. Corequisite: DASC 32003 . Prerequisite: DASC 21103 , DASC 25904 , ( DASC 310H3 or DASC 31003 ), (( MATH 30103 and STAT 30043 ) or ( INEG 23104 and INEG 23203 )), and student must be a DTSCBS major. (Typically offered: Spring)
Prerequisites: DASC 21103, DASC 25904, DASC 31003, MATH 30103, STAT 30043, INEG 23104, INEG 23203