Course
| code | IS465 |
| credit_hours | 3 |
| title | Data Mining |
| arbic title | |
| prequisites | IS273 |
| credit hours | 3 |
| Description/Outcomes | Data mining is a rapidly growing field that is concerned with developing techniques to assist managers to make intelligent use of these repositories. A number of successful applications have been reported in areas such as credit rating, fraud detection, database marketing, and customer relationship management. The field of data mining has evolved from the disciplines of statistics and artificial intelligence. This course will examine methods that have emerged from both fields and proven to be of value in recognizing patterns and making predictions from an applications perspective. We will survey applications and provide an opportunity for hands-on experimentation with algorithms for data mining using easy-to- use software and cases. |
| arabic Description/Outcomes | |
| objectives | 1. Understand data mining basic concepts, applications and techniques.
2. Acquire hands-on experience with key components of data mining by using industrial commercial application packages.
3. Use recent data mining software to create business intelligence solutions to meet real world needs.
4. Gain experience of doing independent study and research.
5. Write survey papers about a narrow topic. |
| arabic objectives | |
| ref. books | Ramesh Sharda , Dursun Delen, Efraim Turban, Business Intelligence: A Managerial Perspective on Analytics., Prentice Hall. |
| arabic ref. books | |
| textbook | Jiawei Han, Micheline Kamber, and Jian Pei, Data Mining: Concepts and Techniques, Morgan Kaufmann. |
| arabic textbook | |
| objective set | |
| content set | |
| course file |
4_IS465_IS465 - Data Minning.pdf |