★ 3 (fi 6)(EITHER, 3-0-0)
Students are introduced to the scientific process of transforming data into insight for making better marketing decisions. Topics include: data-driven problem solving; design of surveys, focus groups, and experiments; analytical techniques for primary, secondary, and qualitative data; and machine learning basics. The course is taught as an end-to-end process, starting from problem framing, data collection, method selection, model building, and deployment. Applies Excel and open-source data analysis software. Advanced students can build on this course to prepare for taking the INFORMS CAP (Certified Analytics Professional) Exam. Prerequisite: MARK 301.
LECTURE B01 (42494)
2023-01-05 - 2023-04-12
MWF 10:00 - 10:50 (BUS 4-09)
LECTURE B02 (49387)
2023-01-05 - 2023-04-12
TH 11:00 - 12:20 (BUS 4-09)
★ 3 (fi 6)(EITHER, 3-0-0)
Special studies for advanced students. Prerequisites: Registration in the Business PhD Program or permission of instructor. Approval of the Business PhD Program Director is also required for non-PhD students.
LECTURE B2 (49994)
LECTURE B1 (50138)