OM 620 - 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 501.

Fall Term 2021

Lectures

LECTURE A1 (49494)
Capacity: 12
2021-09-01 - 2021-12-07
MW 11:00 - 12:20 (CL 1-30)

Primary Instructor: Ilbin Lee

Winter Term 2022

Lectures

LECTURE B1 (67602)
Capacity: 5
2022-01-05 - 2022-04-08
MW 11:00 - 12:20 (BUS B-18)

LECTURE X50 (65496)
Capacity: 25
2022-01-05 - 2022-04-08
H 18:00 - 21:00 (BUS B-18)

Primary Instructor: M. Hosein Zare

Fall Term 2022

Lectures

LECTURE A1 (34195)
Capacity: 12
2022-09-01 - 2022-12-08
MW 11:00 - 12:20 (TBD)

Winter Term 2023

Lectures

LECTURE B1 (42550)
Capacity: 5
2023-01-05 - 2023-04-12
MW 11:00 - 12:20 (TBD)

LECTURE X50 (41900)
Capacity: 25
2023-01-05 - 2023-04-12
H 18:00 - 21:00 (TBD)