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

112-1 325088 資料科學 1 3.0 3 ★ 白敦文
邱弘緯 AI雙聯專班 13 0 碩一修，9/17，10/14，10/29，11/25，12/2，12/16

學年期	課號	課程名稱	階段	學分	時數	修	教師	班級	人	撤	備註
112-1	325088	資料科學	1	3.0	3	★	白敦文邱弘緯	AI雙聯專班	13	0	碩一修，9/17，10/14，10/29，11/25，12/2，12/16

教學大綱與進度：

教師姓名白敦文　教師諮商時間(Office Hours)

Email twp@ntut.edu.tw

最後更新時間 2023-09-25 15:37:15

課程大綱 This course explores the rapidly developing fields of big data for decision-making supports in various fields. The topics are about basic concepts of data manipulations, analytic, and communications which include: 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 is used to add value to a 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 1. Business Intelligence 2. Statistics Bckground 3. Data mining 4. Decision Tree 5. Regression 6.Artificial Neural Network 7. Clustering analytics 8. Association rules 9. Naive Bayes Analytics 10. Support Vector Machine

評量方式與標準 Reports:50% Exercise: 50%

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
Lecture slides and handouts

課程諮詢管道研究室分機(Extension): 4222
位置(Office): 宏裕科技大樓1524 (Hung-Yu Research Tech. Building)
Office hours: Sat. 18:00-19:00

Any linking problem related to MS teams, please contact TA individually.
TA:陳勝舢 Email: 54sakuramiku@gmail.com

課程對應SDGs指標

備註
All lecture slides will be provided in advance through iSchool system.
Lectures will be provided through MS teams.

教師姓名	白敦文　教師諮商時間(Office Hours)
Email	twp@ntut.edu.tw
最後更新時間	2023-09-25 15:37:15
課程大綱	This course explores the rapidly developing fields of big data for decision-making supports in various fields. The topics are about basic concepts of data manipulations, analytic, and communications which include: 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 is used to add value to a 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	1. Business Intelligence 2. Statistics Bckground 3. Data mining 4. Decision Tree 5. Regression 6.Artificial Neural Network 7. Clustering analytics 8. Association rules 9. Naive Bayes Analytics 10. Support Vector Machine
評量方式與標準	Reports:50% Exercise: 50%
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 Lecture slides and handouts
課程諮詢管道	研究室分機(Extension): 4222 位置(Office): 宏裕科技大樓1524 (Hung-Yu Research Tech. Building) Office hours: Sat. 18:00-19:00 Any linking problem related to MS teams, please contact TA individually. TA:陳勝舢 Email: 54sakuramiku@gmail.com
課程對應SDGs指標
備註	All lecture slides will be provided in advance through iSchool system. Lectures will be provided through MS teams.