由于科技的发展，导致与管理决策相关的资料，正以一种惊人的速度被不断累积。作为网际网络、电子商务、电子银行、销售点设备、条码阅读机及智慧型机器等创新的副产品，电子资料的获取，已经变得廉价而且普及。

这些资料通常被储存于资料仓储和资料超市中，并特别准备为管理决策提供支援。资料探勘是一个快速成长的领域，其主要任务在发展相关技术以协助管理者对这些数据库进行智能化的运用。而资料探勘在信用评级、诈欺揭发、营销数据库、客户关系管理及股票投资市场等方面的一些成功应用亦已经被揭示。资料探勘领域已经从统计学及人工智能领域演变发展出来。

本课程将检视那些在这两个领域中新诞生，并被证实从应用的角度上，对于模式的辨识和预测具有价值的方法。我们将会了解那些应用，并透过简单易用的软件及案例，提供亲自动手操作资料探勘算法的机会。

Data that has relevance for managerial decisions is accumulating at an incredible rate due to a host of technological advances. Electronic data capture has become inexpensive and ubiquitous as a by-product of innovations such as the internet, e-commerce, electronic banking, point-of-sale devices, bar-code readers, and intelligent machines. Such data is often stored in data warehouses and data marts specifically intended for management decision support. 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, customer relationship management, and stock market investments. 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.