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 | Class times | Instructor(s) |
|---|---|---|---|
| 5 |
2024-01-08 - 2024-04-12 (MW)
11:00 - 12:20
BUS B-18
|
Primary Instructor: Ilbin Lee
|
|
| 25 |
2024-01-08 - 2024-04-12 (R)
18:00 - 21:00
BUS B-18
|
Primary Instructor: Mohamad Soltani
|
| Section | Capacity | Class times | Instructor(s) |
|---|---|---|---|
|
LECTURE A01
(49389) |
10 |
2024-09-03 - 2024-12-09 (MW)
11:00 - 12:20
A 109
|
|
| Section | Capacity | Class times | Instructor(s) |
|---|---|---|---|
|
LECTURE B01
(71694) |
10 |
2025-01-06 - 2025-04-09 (MW)
11:00 - 12:20
A 109
|
|
|
LECTURE X50
(71259) |
25 |
2025-01-06 - 2025-04-09 (R)
18:00 - 21:00
BUS B-18
|
|