國立中山大學 105學年度第2學期 課程教學大綱

National Sun Yat-sen University 105Academic year Course syllabus

中文名稱
Course name(Chinese)

資料探勘與知識發現

課號
Course Code

MIS545

英文名稱
Course name(English)

DATA MINING AND KNOWLEDGE DISCOVERY

課程類別
Type of the course

講授類

必選修
Required/Selected

選修

系所
Dept./faculty

資訊管理學系碩士班

授課教師
Instructor

李偉柏    

學分
Credit

3

課程大綱Course syllabus

         Data mining and knowledge discovery are essential in decision support. They are crutical to predict future trends and to support decision-making. Data mining techniques can be categorized as calssification, clustering, association rules, sequential patterns, time-series patterns, and link analysis. They have been applied to many applications successfully. This course introduces related techniques and their applications in a wide scope.









課程目標 Objectives

         This course introduces some important issues and useful techniques in data mining and knowledge discovery to students. It aims to help students to deepen understanding of data mining and knowledge discovery, and to apply relevant methods and techniques to design and implement systems to solve real world problems.









授課方式 Teaching methods

         lecture, discussion, presentation









評分方式﹝評分標準及比例﹞Evaluation (Criteria and ratio)等第制單科成績對照表 letter grading reference

        
1.homework25%
2.midterm exan15%
3.final exam15%
4.project45%

參考書/教科書/閱讀文獻 Reference book/ textbook/ documents
〔請遵守智慧財產權觀念,不可非法影印。教師所提供之教材供學生本人自修學習使用,不得散播及做為商業用途〕
No copies for intellectual property rights. Textbooks provided by the instructor used only for self-study, can not broadcast or commercial use

        
序號作者書名出版社出版年出版地ISBN#
1Pang-Ning Tan, Michael Steinbach, and Vipin KumarIntroduction to Data MiningAddison-Wesley2012
2Jiawei Han and Micheline KamberData Mining: Concept and TechniquesMorgan Kauffman Publishers2013

每週課程內容及預計進度 Weekly scheduled progress

        
週次日期授課內容及主題
12017/02/20~2017/02/26Overview of Data Mining and Knowledge Discovery
22017/02/27~2017/03/05Data Preprocessing
32017/03/06~2017/03/12tool course
42017/03/13~2017/03/19Predictive Modeling: Classification (I)
52017/03/20~2017/03/26Predictive Modeling: Classification (II)
62017/03/27~2017/04/02Predictive Modeling: Classification (III)
72017/04/03~2017/04/09Data Clustering (I)
82017/04/10~2017/04/16Data Clustering (II)
92017/04/17~2017/04/23mid-term exam
102017/04/24~2017/04/30presentation
112017/05/01~2017/05/07Link Analysis: Association Rules (I)
122017/05/08~2017/05/14Link Analysis: Association Rules (II)
132017/05/15~2017/05/21Advanced Topics and Applications (I)
142017/05/22~2017/05/28Advanced Topics and Applications (II)
152017/05/29~2017/06/04Advanced Topics and Applications (III)
162017/06/05~2017/06/11project demo/presentation
172017/06/12~2017/06/18project demo/presentation
182017/06/19~2017/06/25final exam

課業討論時間 Office hours

         時段1:
時間:星期二14:00-16:00
地點:管4075-2
時段2:
時間:星期四14:00-16:00
地點:管4075-2

系所學生專業能力/全校學生基本素養與核心能力 basic disciplines and core capabilitics of the dcpartment and the university

        
系所學生專業能力/全校學生基本素養與核心能力課堂活動與評量方式
本課程欲培養之能力與素養紙筆考試或測驗課堂討論︵含個案討論︶個人書面報告、作業、作品、實驗群組書面報告、作業、作品、實驗個人口頭報告群組口頭報告課程規劃之校外參訪及實習證照/檢定參與課程規劃之校內外活動及競賽課外閱讀
※系所所學生專業能力
1.具備資訊倫理的能力           
2.具備溝通能力V          
3.具備解決資訊管理問題之能力V          
4.具備資訊管理之專業知識           
5.具備國際觀           
※全校學生基本素養與核心能力
1.表達與溝通能力。           
2.探究與批判思考能力。V          
3.終身學習能力。           
4.倫理與社會責任。           
5.美感品味。           
6.創造力。           
7.全球視野。           
8.合作與領導能力。           
9.山海胸襟與自然情懷。           

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