113年第1學期-5514 資料探勘與應用 課程資訊

評分方式

評分項目	配分比例	說明
Two assignments	20
One short presentation	10
One project	25
One exam:	35
Class participation (in or after class)	10

教育目標

Data mining serves as a crucial field that leverages advanced algorithms to reveal hidden, yet invaluable insights buried within extensive datasets. These algorithms are drawn from a multitude of areas such as machine learning, artificial intelligence, pattern recognition, statistics, and database systems, working together to facilitate a deeper understanding and analysis of data. This course is designed to equip you with the foundational knowledge and hands-on experience needed to delve into the expansive world of data mining. Whether you are looking to enhance your skill set or embark on a new career path, this course will serve as a stepping stone to achieving your goals. The curriculum encompasses a range of topics that will introduce you to the core concepts and techniques prevalent in the field of data mining. These include:  Association Rules: Understand the principles behind identifying rules that highlight relationships between seemingly independent data in a database.  Clustering: Learn about grouping a set of objects in such a way that objects in the same group are more similar to each other than to those in other groups.  Classification: Gain knowledge on the procedures for identifying the predefined class of a new observation.  Text Mining: Equip yourself with the skills needed to analyze and interpret large collections of text data to extract meaningful information.  Data Mining Applications: Explore the various practical applications of data mining across different industries and sectors.

基本資料

選修課，學分數：3-0
上課時間：一/2,3,4[遠距課程]
修課班級：共選修3,4,碩博1,2
修課年級：3年級以上
選課備註：教育部補助臺灣大專院校人工智慧學程聯盟，清華大學開設之主導課程，遠距課程，英語授課，上課時間：9：00-12：00。

參考書目

Pang-Ning Tan, Michael Steinbach, Vipin Kumar, Introduction to Data Mining, Addison Wesley