| 課程代碼 |
1GM00H01
|
| 課程中文名稱 |
資料探勘與應用
|
| 課程英文名稱 |
Data Mining and Application
|
| 學分數 |
3.0
|
| 必選修 |
選修
|
| 開課班級 |
博研經管二甲
|
| 任課教師 |
王派洲
|
| 上課教室(時間) |
|
週五
|
第6節
|
(E0602)
|
|
週五
|
第7節
|
(E0602)
|
|
週五
|
第8節
|
(E0602)
|
|
| 課程時數 |
3
|
| 實習時數 |
0
|
| 授課語言 |
1.英語
◎全程外語教學
|
| 輔導考證 |
無
|
| 課程概述 |
Data mining programs are intended to search through data for hidden relationships and patterns in your data. This is particularly pertinent to marketing companies who want to know what made a specific group of people buy their product. It can also be very important in scientific fields such as medicine where finding correlations in groups of people who are affected by a similar disease could be very helpful. Data mining is needed to make sense and use of the rapidly growing data and is an essential field of the 21st century.
|
| 先修科目或預備能力 |
Excel, Statistics
|
|
課程學習目標與核心能力之對應
|
| 編號 | 中文課程學習目標 | 英文課程學習目標 |
|
1
|
1.be able to describe the generic characteristics of data mining
|
1.be able to describe the generic characteristics of data mining
|
|
2
|
understand the concept, procedure and technique of data mining
|
understand the concept, procedure and technique of data mining
|
|
3
|
preprocess the raw data with the related software
|
preprocess the raw data with the related software
|
|
4
|
have developed your own data mining application
|
have developed your own data mining application
|
|
5
|
analyze the business data and interpret the analysis results
|
analyze the business data and interpret the analysis results
|
|
6
|
be prepared for independent, critical study and assessment of publications about data mining
|
be prepared for independent, critical study and assessment of publications about data mining
|
|
| 就業力培養目標 |
此門課程無設定權重值
|
| 中文課程大綱 |
1.資料探勘與機器學習的簡介
2.機器學習與分類分析
3.資料的輸入：概念、範例、屬性
4.分類分析方法：決策樹
5.模式的評估
6.分群分析
7.關聯分析
|
| 英/日文課程大綱 |
1. Introduction: Machine Learning and Data Mining
2. Machine Learning and Classification
3. Input: Concepts, instances, attributes
4. Classification: Decision Trees
5. Model Evaluation and Credibility
6. Clustering
7. Associations
|
| 課程進度表 |
1.be able to describe the generic characteristics of data mining
2.understand the concept, procedure and technique of data mining
3.preprocess the raw data with the related software
4.have developed your own data mining application
5.analyze the business data and interpret the analysis results
6.be prepared for independent, critical study and assessment of publications about data mining
|
| 課程融入SDGs |
|
| 期考調查 |
| 期中考(第9週)考試方式 |
|
| 期末考(第18週)考試方式 |
|
| 其他週考試考試週次與方式 |
|
|
| 教學方式與評量方式 |
| 課程學習目標 | 教學方式 | 評量方式 |
| 1.be able to describe the generic characteristics of data mining |
課堂講授
|
口頭報告
（
期中
）
口頭報告
（
期末
）
|
| understand the concept, procedure and technique of data mining |
實作演練
|
實作
（
期中
）
實作
（
期末
）
|
| preprocess the raw data with the related software |
實作演練
|
實作
（
平時
）
|
| have developed your own data mining application |
實作演練
|
實作
（
平時
）
|
| analyze the business data and interpret the analysis results |
實作演練
|
實作
（
平時
）
|
| be prepared for independent, critical study and assessment of publications about data mining |
課堂講授
|
口頭報告
（
平時
）
|
|
| 指定用書 |
| 書名 |
Data Mining:Concepts and Techniques
|
| 作者 |
Jiawei Han, Micheline Kamber, and Jian Pei
|
| 書局 |
|
| 年份 |
|
| 國際標準書號(ISBN) |
|
| 版本 |
|
請同學尊重智慧財產權，使用正版教科書，不得非法影印，以免觸犯智慧財產權相關法令
。 |
| 參考書籍 |
|
| 教學軟體 |
|
| 課程規範 |
|