基本素養 Basic Literacy

□ 倫理道德觀
學生應具備良好倫理道德觀
Ethic
Students should possess ethic.
■ 國際觀
學生應具備良好的國際觀
Global Awareness
Students should possess a global perspective.
□ 社會責任
學生應具備正確之社會責任
Social Responsibility
Students should possess socialresponsibility.

核心能力 Competence

■ 口語表達/ 簡報能力
學生應具備良好之口語表達及簡報能力
Oral Communication/ Presentation
Students should be able to communicate effectively verbally and in presentation.
□ 寫作能力
學生應具備良好之寫作能力
Written Communication
Students should be able to communicate effectively in writing.
□ 創新能力
學生應具備創造及創新之能力
Creativity and Innovation
Students should demonstrate creativity and innovation skills.
■ 解決問題能力
學生應具備解決問題之能力
Problem Solving Skills
Students should be able to solve strategic problems.
■ 分析能力
學生應具備良好的分析能力
Analytical Skills
Students should demonstrate analytical skills.
■ 領導能力
學生應具備良好領導能力
Leadership
Students should demonstrate leadership skills demanded of a person in authority.
□ 批判能力
學生應具備良好的批判能力
Critical Thinking
Students should possess critical thinking skills.
■ 專業技能
學生應具備良好的專業態度與技能
Values, Skills & Professionalism
Students should possess the necessary skills and values demanded of a true professional.
■ 資訊科技能力
學生應具備資訊科技能力
Information Technology
Students should possess information technology skills.
□ 管理能力
學生應具備良好的管理能力
Management Skills
Students should possess management skills.

課程概述 Course Description

本課程針對主要資料探勘概念及方法技術進行介紹。主要涵蓋主題包括: 資料探勘演算法及方法，如關聯分析、分類分析、群落分析，並介紹資料探勘興起中之趨勢與技術(如網路資料探勘、生物醫療資料探勘及安全)課題。
In this course, preliminary data mining concepts and techniques are introduced. Topics covered are: Data mining algorithms and methods including association analysis, classification, cluster analysis, as well as emerging applications and trends in data mining (such as Web data mining, biomedical data mining and security).

課程學習目標 Course Objectives

  • Understand basic data mining & knowledge discovery concepts
  • Understand data mining algorithms and methods
  • Apply different data mining techniques to solve problems
  • Use specific software tools for data pre-processing

    • 課程進度 Progress Description

    進度說明 Progress Description
    1Introduction to data-analytic thinking
    2Introduction to Data Mining
    3Data Mining: Data
    4Exploring Data
    5Classification: Basic Concepts, Decision Trees, and Model Evaluation
    6Classification: Basic Concepts, Decision Trees, and Model Evaluation
    7Classification: Alternative Techniques
    8Classification: Alternative Techniques
    9Association Analysis: Basic Concepts and Algorithms
    10Association Analysis: Basic Concepts and Algorithms
    11Association Rules: Advanced Concepts and Algorithms
    12Association Rules: Advanced Concepts and Algorithms
    13Cluster Analysis
    14Cluster Analysis
    15Text Mining
    16Text Mining
    17Term Project Presentation
    18Term Project Presentation
    　以上每週進度教師可依上課情況做適度調整。The schedule may be subject to change.

    課程是否與永續發展目標相關調查
    Survey of the conntent relevant to SDGs

    本課程與SDGs相關項目如下：
    This course is relevant to these items of SDGs as following:
    • 健康與福祉 (Good health and Well Being)
    • 工業、創新與基礎建設 (Industry Innovation and infrastructure)
    • 責任消費與生產 (Responsible consumption and production)
    • 氣候行動 (climate action)

    有關課程其他調查 Other Surveys of Courses

    1.本課程是否規劃業界教師參與教學或演講? 否
    Is there any industry specialist invited in this course? How many times? No
    2.本課程是否規劃含校外實習(並非參訪)? 否
    Are there any internships involved in the course? How many hours? No
    3.本課程是否可歸認為學術倫理課程? 否
    Is this course recognized as an academic ethics course? In the course how many hours are regarding academic ethics topics? No
    4.本課程是否屬進入社區實踐課程? 否
    Is this course recognized as a Community engagement and Service learning course? Which community will be engaged? No