At the end of this course, the students; 1) Learn Data Mining in Business. 2) Learn Data Mining Processes and Knowledge Discovery. 3) Understand Database Support to Data Mining. 4) Apply several algorithms of data mining techniques.
MODE OF DELIVERY
Face to face
PRE-REQUISITES OF THE COURSE
No
RECOMMENDED OPTIONAL PROGRAMME COMPONENT
None
COURSE DEFINITION
Data Mining in Business ; Data Mining Processes and Knowledge Discovery: Database Support to Data Mining; Overview of Data Mining Techniques; Cluster Analysis ; Regression Algorithms in Data Mining; Neural Networks in Data Mining; Decision Tree Algorithms; Linear Programming-Based Methods; Business Data Mining Applications; Market-Basket Analysis; Text and Web Mining.
COURSE CONTENTS
WEEK
TOPICS
1st Week
Data Mining in Business ;
2nd Week
Data Mining Processes and Knowledge Discovery: Database Support to Data Mining;
3rd Week
Overview of Data Mining Techniques;
4th Week
Cluster Analysis ;
5th Week
Regression Algorithms in Data Mining;
6th Week
Neural Networks in Data Mining;
7th Week
Decision Tree Algorithms;
8th Week
Mid-term
9th Week
Linear Programming-Based Methods;
10th Week
Business Data Mining Applications;
11th Week
Market-Basket Analysis;
12th Week
Text and Web Mining.
13th Week
Text and Web Mining.
14th Week
Text and Web Mining.
RECOMENDED OR REQUIRED READING
1. Turban E., Sharda R., Delen D., Decision Support and Business Intellegence Systems, 9/E, ISBN:9780132453233, Pearson, 2011 2. Olson D., Shi Y., Introduction to Business Data Mining, ISBN: 0072959711, McGraw Hill, 2007
