Data mining is a very important field that is concerned with developing techniques to assist managers to make intelligent use of data 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.
IS -132 CRs
Ramesh Sharda, Dursun Delen and Efrain Turban, Business Intelligence and Analytics: Systems for Decision Support, Pearson.
| content serial | Description |
|---|
| 1 | Introduction to Decision Support Systems |
| 2 | Introduction to Business Intelligence |
| 3 | Decision-Making Process |
| 4 | DSS Capabilities, Structure and Classifications. |
| 5 | Modeling for Management Support System |
| 6 | Modeling For Management Support System (Cont.) |
| 7 | Data Mining for Business Intelligence. |
| 8 | Data Mining for Business Intelligence (cont.) |
| 9 | Artificial Neural Networks for Data Mining |
| 10 | Artificial Neural Networks for Data Mining (cont) |
| 11 | Data Warehouses and Its Role In Decision Support |
| 12 | Data Warehouses and Its Role In Decision Support (cont) |
| 13 | Intelligent Support Systems (Cont.) |
| 14 | Intelligent Support Systems (Cont.) |
| 15 | Revision |
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