基本素養 Basic Literacy

領導能力
學生應具備領導其他專長同仁解讀數據的才能
Leadership
Undergraduate students should develop leadership skills required of a person in a leading position
倫理及社會責任
學生需有自我學習的的意願及能力,並積極參與活動以擴大其社交網絡
Ethic & Social Responsibility
Undergraduate students should demonstrate ethical awareness in learning and in social networking
全球化視野
同學需適時的掌握現在國際間情勢的更替,並理解全球化的趨勢
Global Awareness
Undergraduate students should possess a global perspective and an awareness of the effects of globalization

核心能力 Competence

口頭溝通及表達能力
學生應具備基本的口語表達能力,能迅速的將事情完整地表達出來
Oral Communication/ Speaking
Undergraduate students should be able to communicate effectively in speaking.
寫作表達能力
學生應具備基本的寫作表達能力,能迅速的將事情完整地表達出來
Written Communication/Writing
Undergraduate students should be able to communicate effectively in writing.
創造及創新能力
同學需要有能力依據不同型態地問題及資料將所學做有效的及創新的整合以利問題的解決
Creativity and Innovation
Undergraduate students should be able to solve strategic problems with creative and innovative approaches
解決問題能力
同學需要有能力依據不同型態地問題及資料將所學做有效的及創新的整合以利問題的解決
Problem Solving
Undergraduate students should be able to solve strategic problems with creative and innovative approaches
分析及計算能力
同學需要有能力依據不同型態地問題及資料將所學做有效的及創新的整合以利問題的解決
Analytical & Computational Skills
Undergraduate students should be able to solve strategic problems with creative and innovative approaches
價值、技巧及專業度
學生能在其工作崗位上,貢獻其所學在統計分析上之專業知識,以冀望能取得在職場上對其統計專業的認同
Values, Skills & Professionalism
Undergraduate students should acquire the skills and values required of a true professional
專業能力
學生能在其工作崗位上,貢獻其所學在統計分析上之專業知識,以冀望能取得在職場上對其統計專業的認同
Technical Skills
Undergraduate students should acquire the skills and values required of a true professional
管理技巧
學生能在其工作崗位上,貢獻其所學在統計分析上之專業知識,以冀望能取得在職場上對其統計專業的認同
Management Skills
Undergraduate students should acquire the skills and values required of a true professional

課程概述 Course Description

本課程將以實例配合統計軟體R使用,以說明各種統計方法在巨量資料分析上的應用
Introduction and application of the statistical methods and package R by some “Big Data” examples

課程學習目標 Course Objectives

  • 使同學對巨量資料分析有基本了解
  • 培養同學具備透過程式開發處理不同類型資料的基本素養
  • 教授及訓練同學機器學習、資料分析與探勘之實作能力
  • 課程進度 Progress Description

    進度說明 Progress Description
    1Introduction to Big Data Analysis
    2Machine Learning with sklearn 1
    3Machine Learning with sklearn 2
    4Data Analysis Practice: Class Balance
    5Data Analysis Practice: Missing Data Imputation
    6Data Analysis Practice: High-dimensional Data
    7Data Analysis Practice: Redundancy and Outliers
    8Data Analysis Practice: Noisy & Unlabeled Data
    9Data Analysis Practice: Massive Datasets
    10Diverse Data Analysis: Text and Natural Language
    11Diverse Data Analysis: Temporal and Spatial Data
    12Diverse Data Analysis: Graph and Multi-modal Data
    13Final Project Proposal
    14Case Study and Applications 1
    15Case Study and Applications 2
    16Case Study and Applications 3
    17Final Project Presentation 1
    18Final Project Presentation 2
     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)
    • 就業與經濟成長 (Decent work and Economic growth)
    • 工業、創新與基礎建設 (Industry Innovation and infrastructure)

    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? 是,約 1 次
    Is there any industry specialist invited in this course? How many times? Yes, about 1 times.
    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

    教師上傳大綱內容
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    1101H242300李政德--巨量資料分析.pdf