查詢教學大綱與進度

教學大綱與進度

課程基本資料：

學年期課號課程名稱階段學分時數修教師班級人撤備註

109-1 278237 大數據分析 1 3.0 3 ★ 王正豪
陳俊豪管理外國學生專班
資財所 42 1 ◎IMBA&IMFI&資財所

學年期	課號	課程名稱	階段	學分	時數	修	教師	班級	人	撤	備註
109-1	278237	大數據分析	1	3.0	3	★	王正豪陳俊豪	管理外國學生專班資財所	42	1	◎IMBA&IMFI&資財所

教學大綱與進度：

教師姓名陳俊豪

Email chchen6814@gmail.com

最後更新時間 2020-06-14 01:40:46

課程大綱本課程介紹大數據在各個領域決策制定的應用，課程內容包括大數據分析與應用、大數據管理、大數據分法與策略、資料探勘介紹、資料探勘方法、大數據平台、大數據行銷實務、大數據個案分析、期末專題製作與報告。學生可以經由多個案例學習大數據的應用實務、目前技術與未來發展方向。 This course explores the rapidly developing fields of big data for the efficiency of decision making in various fields. The topics are about basic concepts of data manipulations, analytic, and communications which are including: introduction to big data; basic knowledge of data mining; special topics of big data in business Analytics, and data analytic project. The course will help students careful consideration of what is desired from big data, how big data analytic to add value to business, etc. Students can gain a strong data science knowledge set and techniques via in-depth case studies, most current readings and experiences, and most current and future technology exploration.

課程進度 Topic I: Association Analysis Week 1: Introduction to Association Analysis Week 2: Advanced Association Analysis and implementation Topic II: Clustering Analysis Week 3: Introduction to Clustering Analysis Week 4: Advanced Clustering Analysis and implementation Topic III: Classification Week 5: Introduction to Classification and implementation Topic IV: Project Demonstration Week 6: Project Demonstration

評量方式與標準 Attendance：30％ Mark of usual：30％ Project Presentation: 40%

使用教材、參考書目或其他 【遵守智慧財產權觀念，請使用正版教科書，不得使用非法影印教科書】

使用外文原文書：否
Python for Finance (Analyze Big Financial Data, Yves Hilpisch, O'Reilly Media, 2014. Deep Learning, Ian Goodfellow, Yoshua Bengio and Aaron Courville Data Mining : Concepts and Techniques, 3/e (Hardcover), Jiawei Han, Micheline Kamber, Jian Pei, 2011.

課程諮詢管道

備註

教師姓名	陳俊豪
Email	chchen6814@gmail.com
最後更新時間	2020-06-14 01:40:46
課程大綱	本課程介紹大數據在各個領域決策制定的應用，課程內容包括大數據分析與應用、大數據管理、大數據分法與策略、資料探勘介紹、資料探勘方法、大數據平台、大數據行銷實務、大數據個案分析、期末專題製作與報告。學生可以經由多個案例學習大數據的應用實務、目前技術與未來發展方向。 This course explores the rapidly developing fields of big data for the efficiency of decision making in various fields. The topics are about basic concepts of data manipulations, analytic, and communications which are including: introduction to big data; basic knowledge of data mining; special topics of big data in business Analytics, and data analytic project. The course will help students careful consideration of what is desired from big data, how big data analytic to add value to business, etc. Students can gain a strong data science knowledge set and techniques via in-depth case studies, most current readings and experiences, and most current and future technology exploration.
課程進度	Topic I: Association Analysis Week 1: Introduction to Association Analysis Week 2: Advanced Association Analysis and implementation Topic II: Clustering Analysis Week 3: Introduction to Clustering Analysis Week 4: Advanced Clustering Analysis and implementation Topic III: Classification Week 5: Introduction to Classification and implementation Topic IV: Project Demonstration Week 6: Project Demonstration
評量方式與標準	Attendance：30％ Mark of usual：30％ Project Presentation: 40%
使用教材、參考書目或其他	【遵守智慧財產權觀念，請使用正版教科書，不得使用非法影印教科書】使用外文原文書：否 Python for Finance (Analyze Big Financial Data, Yves Hilpisch, O'Reilly Media, 2014. Deep Learning, Ian Goodfellow, Yoshua Bengio and Aaron Courville Data Mining : Concepts and Techniques, 3/e (Hardcover), Jiawei Han, Micheline Kamber, Jian Pei, 2011.
課程諮詢管道
備註