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.
| Section | Capacity | Dates + Times | Instructor(s) |
|---|---|---|---|
|
LECTURE X01
(11316) |
27 |
2022-05-09 - 2022-06-15
MW 18:00 - 20:50 (T B-39)
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Primary Instructor: M. Hosein Zare
|
| Section | Capacity | Dates + Times | Instructor(s) |
|---|---|---|---|
|
LECTURE A01
(34195) |
10 |
2022-09-01 - 2022-12-08
MW 11:00 - 12:20 (CL 1-30)
|
Primary Instructor: Ilbin Lee
|
| Section | Capacity | Dates + Times | Instructor(s) |
|---|---|---|---|
|
LECTURE B01
(42550) |
5 |
2023-01-05 - 2023-04-12
MW 11:00 - 12:20 (BUS B-18)
|
|
|
LECTURE X50
(41900) |
25 |
2023-01-05 - 2023-04-12
H 18:00 - 21:00 (BUS B-18)
|
Primary Instructor: Mohamad Soltani
|