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.
| Section | Capacity | Class times | Instructor(s) |
|---|---|---|---|
| 20 |
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 (TR)
12:30 - 13:50
BUS B-18
|
Primary Instructor: Maryam Hasanzadeh Mofrad
|
| Section | Capacity | Class times | Instructor(s) |
|---|---|---|---|
|
LECTURE A01
(30619) |
25 |
2024-05-06 - 2024-06-12 (MW)
14:00 - 16:50
BUS B-18
|
Primary Instructor: Bo Han
|
| Section | Capacity | Class times | Instructor(s) |
|---|---|---|---|
|
LECTURE A01
(49387) |
40 |
2024-09-03 - 2024-12-09 (MW)
11:00 - 12:20
A 109
|
|
|
LECTURE A02
(49388) |
40 |
2024-09-03 - 2024-12-09 (MW)
14:00 - 15:20
BUS B-18
|
|
| Section | Capacity | Class times | Instructor(s) |
|---|---|---|---|
|
LECTURE B01
(71699) |
30 |
2025-01-06 - 2025-04-09 (MW)
11:00 - 12:20
A 109
|
|
|
LECTURE B02
(77905) |
40 |
2025-01-06 - 2025-04-09 (TR)
12:30 - 13:50
A 109
|
|