114年第1學期-5512 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：1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，開設學校：清華大學（陳宜欣），同步遠距上課時間：星期一 9:00~12:00，開放大三以上修習，英文授課，遠距課程

參考書目

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