Data Mining for Business Analytics
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Overview
Description
Data Mining is the process by which useful information is extracted from large amounts of data. This course is designed to provide students with the necessary tools and techniques to perform data mining and business analytics. The topics will include essentials of data management, data preparation and examination, data clustering or segmentation techniques, and model development using binary trees, regression methods, neural networks and other ad-hoc methods. In addition to model development, students will learn about model assessment and validation, as well as predictive analytics using those models. Emphasis will be placed on careful presentation of quantitative aspects of data mining and business analytics, as well as on applications to large data. Students will be expected to implement these techniques on big-data case studies throughout the semester.Prerequisites: CIS 9000 or CIS 9001 and STA 9708.
Career
Graduate
Credits
Value
3
Max
3
Min
3
Course Count
1
Number Of Credits
3
Number Of Repeats
1
Repeatable
No
Contact Use
Yes
Generate Attendance
No
Left Use
Yes
Present Use
Yes
Reason Use
Yes
Tardy Use
Yes
Template Override
No
Time Use
Yes
Attendance Type
Class Meeting
Auto Create
No
Code
LEC
Instructor Contact Hours
3
Default Section Size
30
Final Exam Type
Yes
Include in Dynamic Date Calc
No
Instruction Mode
In Person
LMS File Type
Blackboard CourseInfo 4
Name
Lecture
OEE Workload Hours
0
Optional Component
No
Preferred Room Features
Academic Scheduling
Workload Hours
3