國立勤益科技大學 企業管理系碩士班 107學年度第 2學期

■課程大綱【 尊重智慧財產權,請使用合法教科書,不得非法影印!】
部別
Department
碩士班
Master
開課代碼
Course Code
G604 授課教師
Instructor(s)
吳世光
Wu,Shung-Kung
科目名稱
Course Name
資料探勘
Data Mining
學分數
Credit
3.0 學時數
Hours
3.0
必/選修
Required/Elective
選修
Elective
開課單位
Course Department
企業管理系碩士班
Department of Business Administration
開課年級
Grade
2
開課學期
Semester
2 全程外語授課
Foreign language
Teaching entirely
否(N) 主要授課語言
Main language
國語
先修課程
Prerequisite course(s)
Statistics
優質課程類別
Course attributes
一般課程
General Courses
課程與校核心能力關聯
Core competence
專業實務能力
Professional Practice Skill
課程與系核心能力關聯
Department core competence
教科書 Textbook
Introduction to Business Data Mining /David L. Olson & Yong Shi Mcgraw-Hill/Irwin 2016 ISBN:
參考書目 Other References

Bater Makhabel (2014), Learning Data Mining with R, Packt Publishing.


評量方式 Evaluation

Participation & Home work 40%, Midterm Exam 30%, Term Project 30%


課程目標 Course objectives
This course will focus on the fundamental concepts of data mining, basic training of quantitative analysis ,and data mining analysis. Students will learn how to gather and analyze large sets of data to gain useful business understanding.
內容綱要 Course Outline

1. Introduction to Data Mining in Business

2. Data Mining Processes and Knowledge

3. Database Support to Data Mining

4. Overview of Data Mining Techniques

5. Cluster Analysis

6. Regression Algorithms in Data Mining

7. Neural Networks in Data Mining

8. Decision Tree Algorithms

9. Market-basket Analysis

10. Text and Web Mining

11. Ethical Aspects of Data Mining


備註 Note
教學進度 Course schedule

01. Introduction to Data Mining in Business

02.Data Mining Processes and Knowledge

03.Database and Data Mining 1

04.Government Open Data and Data Mining

05. Overview of Data Mining Techniques (I)

06. Overview of Data Mining Techniques (II)

07. Cluster Analysis (I)

08. Cluster Analysis (II)

09. Mid-term Exam

10.Regression Algorithms in Data Mining(I)

11.Regression Algorithms in Data Mining(II)

12.Neural Networks (I)

13.Neural Networks (II)

14. Decision Tree Algorithms (I)

15.Decision Tree Algorithms (II)

16.Market-basket Analysis

17. Text and Web Mining

18.Final Exam

自編教材 Self-compiled textbook
使用自編教材。
符合智財規範 Compliance with Intellectual property
已符合智財規範。