國立中山大學 110學年度第2學期 課程教學大綱

National Sun Yat-sen University 110Academic year Course syllabus

Course name(Chinese)


Course Code


Course name(English)


Type of the course










因應嚴重特殊傳染性肺炎(武漢肺炎),倘若後續需實施遠距授課,授課方式調整如下:Since COVID-19, if distance learning is necessary, the teaching methods would adjust as follows:

         同步遠距【透過網路直播技術,同時進行線上教學,得採Microsoft Teams、Adobe connect等軟體進行】
同步遠距含錄影【透過網路直播技術,同時進行線上教學並同時錄影,課程內容可擇日再重播,得採Microsoft Teams、Adobe connect等軟體進行】


因應嚴重特殊傳染性肺炎(武漢肺炎),倘若後續需實施遠距授課,評分方式調整如下:Since COVID-19, if distance learning is necessary, the evaluation would adjust as follows:


課程大綱 Course syllabus

         本課程教學大綱已提供完整英文資訊(本選項僅供統計使用,未提供完整英文資訊者,得免勾記)【Provide information of course syllabus in English.(This is for statistical use only. For those who do not provide information of course syllabus in English, do not check this field.)】

This is an advanced analytics course of NSYSU master’s degree program in Business Analytics. Students will be introduced to the latest business data analytics tools and techniques, which include, but are not limited to, R, Apache Hadoop, Apache Spark, and H2O. In this course, we will be discussing the latest business analytics concepts and techniques along with advances of Data Science and its applications in various business fields. Background in related studies including probability & statistics, marketing research, predictive analytics, data engineering, credit risk modeling, and statistical learning, will also be reviewed.

課程目標 Objectives

Basic understanding of relational databases, SQL, data structures, probability & statistics, college-level calculus, and matrix operations are required. Familiar with at least one high-level programming language. Scientific programming language, such as R, MATLAB, Python, SAS, Julia are preferred.

授課方式 Teaching methods

         * Online Lecture
* On-site Group Discussion

評分方式﹝評分標準及比例﹞Evaluation (Criteria and ratio)等第制單科成績對照表 letter grading reference

4.Final Project20%

參考書/教科書/閱讀文獻 Reference book/ textbook/ documents
No copies for intellectual property rights. Textbooks provided by the instructor used only for self-study, can not broadcast or commercial use

         * F. Provost, T. Fawcett. Data Science for Business: What you need to know about data mining and data-analytic thinking”, O'Reilly Media, Inc., 2013.
* C. O'Neil and R. Schutt, Doing Data Science: Straight Talk from the Frontline,. O'Reilly Media, 2013
* G. James, D. Witten, T. Hastie, and R. Tibshirani, An Introduction to Statistical Learning: with Applications in R, 2nd edition. New York: Springer (Available free online: https://www.statlearning.com/)
* K. Hwang and M. Chen, Big-Data Analytics for Cloud, IoT and Cognitive Computing, 1st ed. Wiley Publishing, 2017.

每週課程內容及預計進度 Weekly scheduled progress

WeekDateContent and topic
12022/02/13~2022/02/19Course overview and introduction
22022/02/20~2022/02/26Introduction to Business Analytics
32022/02/27~2022/03/05Data Management I
42022/03/06~2022/03/12Data Management II
52022/03/13~2022/03/19Data Management III
62022/03/20~2022/03/26Fundamentals of Data Analytics I
72022/03/27~2022/04/02Fundamentals of Data Analytics II
82022/04/03~2022/04/09Fundamentals of Data Analytics III
92022/04/10~2022/04/16Midterm Proposal Presentation
102022/04/17~2022/04/23Statistical Learning-Introduction
112022/04/24~2022/04/30Statistical Learning-Supervised Learning I
122022/05/01~2022/05/07Statistical Learning-Supervised Learning II
132022/05/08~2022/05/14Statistical Learning-Supervised Learning III
142022/05/15~2022/05/21Statistical Learning-Unsupervised Learning
152022/05/22~2022/05/28Statistical Learning-Prescriptive Analytics
162022/05/29~2022/06/04Introduction to Scalable Data Analytics
172022/06/05~2022/06/11Final Project Presentation I
182022/06/12~2022/06/18Final Project Presentation II

課業討論時間 Office hours

         時段1 Time period 1:
時間 Time:星期三10am-12pm
地點 Office/Laboratory:管CM4057
時段2 Time period 2:
時間 Time:星期四10am-12pm
地點 Office/Laboratory:管CM4057

系所學生專業能力/全校學生基本素養與核心能力 basic disciplines and core capabilitics of the dcpartment and the university

basic disciplines and core capabilities of the department and the university
Class activities and evaluation
本課程欲培養之能力與素養 This course enables students to achieve.紙筆考試或測驗 Test.課堂討論︵含個案討論︶ Group discussion (case analysis).個人書面報告、作業、作品、實驗 Indivisual paper report/ assignment/ work or experiment.群組書面報告、作業、作品、實驗 Group paper report/ assignment/ work or experiment.個人口頭報告 Indivisual oral presentation.群組口頭報告 Group oral presentation.課程規劃之校外參訪及實習 Off-campus visit and intership.證照/檢定 License.參與課程規劃之校內外活動及競賽 Participate in off-campus/ on-campus activities and competitions.課外閱讀 Outside reading.
※系所學生專業能力 Basic disciplines and core capabilities of the department
1.具備資訊倫理與社會責任實踐的能力 1. Awareness of information ethics.           
2.具備溝通能力 2. Communication Skills.           
3.具備解決資訊管理問題之能力 3. Capabilities to solve IT-related problems.           
4.具備資訊管理之專業知識 4. Professional knowledge of information technology.           
5.具備國際觀 5. Global perspective.            
※全校學生基本素養與核心能力 Basic disciplines and core capabilities of the university
1.表達與溝通能力。 1. Articulation and communication skills           
2.探究與批判思考能力。 2. Inquisitive and critical thinking abilities           
3.終身學習能力。 3. Lifelong learning           
4.倫理與社會責任。 4. Ethnics and social responsibility           
5.美感品味。 5. Aesthetic appreciation           
6.創造力。 6. Creativity           
7.全球視野。 7. Global perspective           
8.合作與領導能力。 8. Team work and leadership           
9.山海胸襟與自然情懷。 9. Broad-mindedness and the embrace of nature            

本課程與SDGs相關項目:The course relates to SDGs items:

SDG1-消除貧窮(No Poverty)
SDG2-消除飢餓 (Zero Hunger)
SDG3-良好健康與福祉(Good Health and Well-being)
SDG4-教育品質(Quality Education)
SDG5-性別平等(Gender Equality)
SDG6-乾淨水源與公共衛生(Clean Water and Sanitation)
SDG7-可負擔乾淨能源(Affordable and Clean Energy)
SDG8-優質工作與經濟成長(Decent Work and Economic Growth)
SDG9-工業、創新和基礎建設(Industry,Innovation and Infrastructure)
SDG10-減少不平等(Reduced Inequalities)
SDG11-永續城市(Sustainable Cities and Communities)
SDG12-責任消費與生產(Responsible Consumption and Production)
SDG13-氣候行動(Climate Action)
SDG14-海洋生態(Life Below Water)
SDG15-陸域生態(Life on Land)
SDG16-和平、正義和穩健的制度(Peace,Justice And Strong Institutions)
SDG17-促進目標實現的全球夥伴關係(Partnership for the Goals)

本課程校外實習資訊: This course is relevant to internship:

The course includes internship.(For statistical use only. If the course without internship, please ignore this item.)


Internship: The required or elective courses should include credits and learning hours. Students should participate in the corporative company or institution to practice and learn the real skills. An internship certification must be handed in at the end of internship to get the credits or to fulfil the graduation requirements.