OM 420 - Predictive Business Analytics

★ 3 (fi 6)(EITHER, 3-0-0)

Faculty of Business

Application of predictive statistical models in areas such as insurance risk management, credit risk evaluation, targeted advertising, appointment scheduling, hotel and airline overbooking, and fraud detection. Students will learn how to extract data from relational databases, prepare the data for analysis, and build basic predictive models using data mining software. Emphasizes the practical use of analytical tools to improve decisions rather than algorithm details. Prerequisite: MGTSC 352 or OM 352.

Fall Term 2021

Lectures

LECTURE A1 (49490)
Capacity: 18
2021-09-01 - 2021-12-07
MW 11:00 - 12:20 (CL 1-30)

Primary Instructor: Ilbin Lee
LECTURE A2 (49492)
Capacity: 25
2021-09-01 - 2021-12-07
MW 14:00 - 15:20 (BUS B-18)

Primary Instructor: M. Hosein Zare

Winter Term 2022

Lectures

LECTURE B1 (67628)
Capacity: 20
2022-01-05 - 2022-04-08
MW 11:00 - 12:20 (BUS B-18)

Fall Term 2022

Lectures

LECTURE A1 (34193)
Capacity: 18
2022-09-01 - 2022-12-08
MW 11:00 - 12:20 (TBD)

LECTURE A2 (34194)
Capacity: 25
2022-09-01 - 2022-12-08
MW 14:00 - 15:20 (TBD)

Winter Term 2023

Lectures

LECTURE B1 (42557)
Capacity: 20
2023-01-05 - 2023-04-12
MW 11:00 - 12:20 (TBD)