課程資訊
課程名稱
製造數據科學
Manufacturing Data Science 
開課學期
111-1 
授課對象
學程  商業資料分析學分學程  
授課教師
李家岩 
課號
IM5055 
課程識別碼
725 U3660 
班次
 
學分
3.0 
全/半年
半年 
必/選修
選修 
上課時間
星期五2,3,4(9:10~12:10) 
上課地點
管二103 
備註
商業資料分析學分學程課程。
限學士班三年級以上
總人數上限:70人 
 
課程簡介影片
 
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課程概述

MDS course supports students learning how to apply artificial intelligence (AI), machine learning, data science (DS) techniques to improve the effectiveness and efficiency of the manufacturing systems. MDS integrates the knowledge domains of the information, engineering, and management. Encourage students to solve the real problem systematically using the design of analytics, from descriptive, diagnostic, predictive, prescriptive to automating, for successfully enhancing decision quality.

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課程目標
1. Learn the statistical learning and optimization methodologies for intelligent manufacturing systems
2. Create a prototype model to solve the problem in real setting related to manufacturing or service systems
3. Develop the research skills and prepare a analytical project report 
課程要求
1. It's better to have prerequisite courses: (1) probability and statistics; (2) operations research
2. Python programming skills
3. Students need to read literature and develop analytical model for term project 
預期每週課後學習時數
 
Office Hours
 
指定閱讀
待補 
參考書目
Hastie, T., R. Tibshirani, and J. Friedman (2009), The Elements of Statistical Learning: Data Mining, Inference, and Prediction, 2nd ed., Springer.
Hillier, F. S., Lieberman, G. J. (2010), Introduction to Operations Research, 9th ed., McGraw-Hill, New York.
Hopp, W. and M. Spearman (2011), Factory Physics, 3rd ed., Waveland Press.
Montgomery, D. C. (2013), Introduction to Statistical Quality Control, 7 ed.: John Wiley & Sons, Inc.
Nahmias, S. (2008), Production and Operations Analysis, 6th ed., McGraw-Hill/Irwin.
Pinedo, M. L. (2016), Scheduling: Theory, Algorithms, and Systems, 5th edition, Springer-Verlag New York. 
評量方式
(僅供參考)
   
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