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課程名稱 |
電子化企業
E-business |
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開課學期 |
111-2 |
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授課對象 |
管理學院 資訊管理學系 |
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授課教師 |
陳靜枝 |
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課號 |
IM5029 |
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課程識別碼 |
725 U3370 |
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班次 |
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學分 |
3.0 |
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全/半年 |
半年 |
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必/選修 |
選修 |
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上課時間 |
星期二7,8,9(14:20~17:20) |
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上課地點 |
管二研六 |
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備註 |
與陳文賢合授
總人數上限：10人 |
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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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課程概述 |
Under the influences of globalization and digitalization, E-Business is the most important topic that all the companies are learning and constructing. This class is designed to introduce students to the important topics in E-Business. The course is divided into two sessions: big data analytics and MRP/ERP. A business visiting tour is included in the lecture to show the students the problems and solutions existing in the current IT industry. |
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課程目標 |
In the first half session of the class, important topics of big data analytics such as Association rules, Cluster analysis, KNN, Naïve Bayes, Decision trees, SVM, AI, and Deep Learning, etc. will be introduced and thoroughly discussed. The students will learn not only the theories and techniques used to solve related problems, but also the real-world applications that adopt these concepts. In the second half session of the class, the course will include the introduction and classification of the production and manufacturing industries, the overview of manufacturing resource planning, demand management, Bill of Material, shop floor control, and IT technology used in production industry. |
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課程要求 |
A list of different business cases related to big data analytics is given at the first half of the class. Participating case discussion in the class. Each student prepare 1~2 pages to class participation. Form a team with 2 students. Each team will select one case related to big data analytics and will prepare a report regarding the selected case. In the second half session of the class, the instructor will assign a case to all teams of the students. Turn in the digital report through NTU COOL on 5/30. Final exam will be take-home and open-book. Each student will send the answer of the final exam through NTU COOL on 6/6. Homework will be assigned through the semester. No late homework will be accepted. Students must turn in their own homework.
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預期每週課後學習時數 |
4 hours |
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Office Hours |
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指定閱讀 |
陳文賢, “大話數據科學”， 北京清華大學出版社，2020年7月。
Manufacturing Resource Planning with and introduction to ERP, SCM, and CRM by Khalid Sheikh. |
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參考書目 |
Enterprise Resources Planning and Beyond—Integrating Your Entire Organization by G. A. Langenwalter.
Integrating ERP, CRM, Supply Chain Management, and Smart Materials by D. N. Chorafas. |
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評量方式
(僅供參考) |
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No. |
項目 |
百分比 |
說明 |
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1. |
Class Participation |
10% |
Participating case discussion in the class. Each student prepare 1~2 pages to class participation. |
2. |
Case Report |
20% |
Form a team with 2 students. Each team will select one case related to big data analytics and will prepare a report regarding the selected case. Each team will prepare a 10~15 minutes presentation. Turn in the digital report through NTU COOL on 3/28. |
3. |
2nd Half Homework |
10% |
Homework will be assigned through the semester. No late homework will be accepted. Students must turn in their own homework. However, students may work together in preparing their homework. It is strongly advised that students understand and do all phases of their homework assignments and not rely on the expertise of others. |
4. |
Project Presentation |
30% |
In the second half session of the class, the instructor will assign a case to all teams of the students. Form each team with 2-5 persons. Each team will prepare a 30 minutes presentation and a less than 20 pages report to show how they solve the problem related to this case. Turn in the digital report through NTU COOL on 5/30. |
5. |
Final Exam |
30% |
Final exam will be take-home and open-book. No discussion is allowed among students when answering the exam questions. Cheating will result in severe penalty. Each student will send the answer of the final exam through NTU COOL on 6/6. |
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針對學生困難提供學生調整方式 |
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上課形式 |
以錄影輔助 |
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作業繳交方式 |
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考試形式 |
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其他 |
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週次 |
日期 |
單元主題 |
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第1週 |
2023/02/21 |
Introduction of the class and Big Data and Data Science (大數據與數據科學) |
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第2週 |
2023/02/28 |
Day off (228 Memorial Day) |
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第3週 |
2023/03/07 |
Association rules and Cluster analysis (關聯分析與聚類分析) Case: Titanic, Iris |
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第4週 |
2023/03/14 |
Model evaluation and KNN (模型評估與近鄰法) Case: Boston House price |
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第5週 |
2023/03/21 |
Midterm case report: ITC eChoupal and Zara |
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第6週 |
2023/03/28 |
Business Visiting Tour |
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第7週 |
2023/04/04 |
Day off (Spring Break) |
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第8週 |
2023/04/11 |
Industrial and Manufacturing Typologies and Their Characteristics |
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第9週 |
2023/04/18 |
Bill of Material (BOM) and Inventory Management |
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第10週 |
2023/04/25 |
Shop Floor Control |
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第11週 |
2023/05/02 |
SOM (Sales Order Management) and POM (Purchase Order Management) |
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第12週 |
2023/05/09 |
An overview of Manufacturing Resource Planning (MRP II) |
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第13週 |
2023/05/16 |
An overview of Manufacturing Resource Planning (MRP II) |
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第14週 |
2023/05/23 |
An Introduction to Enterprise Resource Planning |
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第15週 |
2023/05/30 |
Project Presentation |
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第16週 |
2023/06/06 |
Turn in the Final Exam |
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