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課程名稱 |
資管博士論壇一
Im Ph.d. Forum (Ⅰ) |
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開課學期 |
105-1 |
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授課對象 |
管理學院 資訊管理學研究所 |
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授課教師 |
黃明蕙 |
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課號 |
IM8026 |
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課程識別碼 |
725 D3150 |
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班次 |
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學分 |
1 |
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全/半年 |
半年 |
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必/選修 |
必修 |
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上課時間 |
星期五6,7(13:20~15:10) |
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上課地點 |
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備註 |
本課程中文授課,使用英文教科書。上課教室：管一102。與莊裕澤合開
限本系所學生(含輔系、雙修生) 且 限博士班
總人數上限：20人 |
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Ceiba 課程網頁 |
http://ceiba.ntu.edu.tw/1051IM8026_ |
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課程簡介影片 |
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核心能力關聯 |
核心能力與課程規劃關聯圖 |
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課程大綱
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為確保您我的權利,請尊重智慧財產權及不得非法影印
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課程概述 |
This class will invite scholars and researchers in the IS and related fields as well as executives and managers from the industry to share their knowledge and experiences on issues related to information management, information technologies, innovation, entrepreneurship. Each talk will last for about 90 minutes, followed by a 20-minute question & answering session. |
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課程目標 |
This course is to acquaint the students with trends and/or practical developments in the field of MIS. Every week there will be a guest speaker, most likely professional academics or successful enterprise leaders, giving a talk on a selected topic. Students are strongly encouraged to express their opinions. Their written critique and response will heavily determine the final grades. |
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課程要求 |
Each student is required to
attend all talks. Students are required to attend all talks arranged for this course. Students will be failed for the course if you miss more than two talks.
never be late for classes and leave earlier. This is how we show our respect and courtesy to our invited speakers.
actively participate in question & answering sessions. To encourage students to participate in question & answering sessions, TA will record your level of participation in question & answering sessions, which serves as the basis for your score on “participation in question & answering sessions.”
write reports (1 pages) for 7 talks of your own choice. Each report of a talk is due at the beginning of the next class meeting following the talk. Late submissions will NOT be accepted. Plagiarism is a serious violation and may result in failing the course and/or being reported to the University.
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預期每週課後學習時數 |
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Office Hours |
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指定閱讀 |
待補 |
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參考書目 |
待補 |
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評量方式
(僅供參考) |
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週次 |
日期 |
單元主題 |
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第5週 |
10/14 |
資料科學往前看－從大數據到人工智慧
http://www.iis.sinica.edu.tw/~swc/talk/data_science_overview.html |
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