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 course is the first part of a one-year training. In this training, through completing a data science project, we will let you know how to use data science to get an insight to markets. We will extensively collect and clean lots of on-line and off-line data, and find possible correlations among variables. Then, you have to combine your business background knowledge with these finding of correlations, and get your own insights on markets or evaluate effects of different marketing strategies. Through completing this project, we will also let you know the idea of evidence-based management. Hence, our team will provide you a basic training about coding, a training about statistical analysis software (for doing regressions), and an introduction of geographic information system (for handling spatial data). Hence, to let you be able to correctly understand or explain the relationship among variables, you need knowledge regarding statistical inference and regressions. Therefore, if you want to take this course, you need also take (or at least, audit) another course I teach in this semester, INDUSTRIAL ECONOMICS (BM625), where I will teach you how to use plenty of industrial or market data to quickly catch an insight into a market or industry. In that course, we will probably spend 1.5 months to introduce some advanced regression methods. Finally, because there is a ceiling for the number of students each teacher can guide, students who have enrolled in BM625 will have a priority to enroll in this course. Moreover, I will also divide this class into several groups. We will deal with these issue in the first week (2/25). If you are interested in this one-year training, you are advised to attend the first lecture of this course.
課程目標 Objectives
1. Understand the idea of evidence-based management. 2. Know how to use data science methods to get market insights and evaluate the effects of different marketing strategies. 3. Through exploring data about real business worlds, you can verify and enhance your business background knowledge.
1.Class Participation and Discussion:30% 2.Group Projects:70%
參考書/教科書/閱讀文獻 Reference book/ textbook/ documents
〔請遵守智慧財產權觀念,不可非法影印。教師所提供之教材供學生本人自修學習使用,不得散播及做為商業用途〕
No copies for intellectual property rights. Textbooks provided by the instructor used only for self-study, can not broadcast or commercial use
According to your projects, we will give you different books/papers/documents.
彈性暨自主學習規劃 Alternative learning periods
本門課程是否有規劃實施學生彈性或自主學習內容(每1學分2小時)
Is any alternative learning periods planned for this course (with each credit corresponding to two hours of activity)?
否:教師需於「每週課程內容及預計進度」填寫18週課程進度(每1學分18小時之正課內容)。 No:The instructor will include an 18-week course plan in the weekly scheduled progress (each credit corresponds to 18 hours of instruction)
是:教師需於「每週課程內容及預計進度」填寫16週課程內容(每1學分16小時之正課內容),並於下列欄位填寫每1學分2小時學生彈性或自主學習內容。 Yes:The instructor will include a 16-week course plan in the weekly scheduled progress (each credit corresponds to 16 hours of instruction);the details of the planned alternative learning periods are provided below (each credit corresponds to two hours of activity).
學生彈性或自主學習活動 Alternative learning periods
勾選或填寫規劃內容 Place a check in the appropriate box or provide details
時數 Number of hours
學生分組實作及討論 Group work and discussion
參與課程相關作業、作品、實驗 Participation in course-related assignments, work, or experiments
參與校內外活動(研習營、工作坊、參訪)或競賽 Participation in on- or off-campus activities (e.g., seminars, workshops, and visits) or competitions
課外閱讀 Extracurricular reading
線上數位教材學習 Learning with online digital learning materials
其他(請填寫規劃內容) Other (please provide details)
每週課程內容及預計進度 Weekly scheduled progress
週次
日期
授課內容及主題
Week
Date
Content and topic
1
2021/02/21~2021/02/27
Course Introduction and Grouping
2
2021/02/28~2021/03/06
An Introduction of R
3
2021/03/07~2021/03/13
An Introduction of R
4
2021/03/14~2021/03/20
An Introduction of R
5
2021/03/21~2021/03/27
An Introduction of Statistical Software (STATA)
6
2021/03/28~2021/04/03
Seminar: Presentation of MA Students
7
2021/04/04~2021/04/10
Seminar: Presentation of MA Students
8
2021/04/11~2021/04/17
Midterm; Meeting Suspended
9
2021/04/18~2021/04/24
Seminar: Presentation of MA Students
10
2021/04/25~2021/05/01
Seminar: Presentation of MA Students
11
2021/05/02~2021/05/08
Seminar: Presentation of Undergraduate Students
12
2021/05/09~2021/05/15
Seminar: Presentation of Undergraduate Students
13
2021/05/16~2021/05/22
An Introduction of Geographic Information System Software (QGIS)
14
2021/05/23~2021/05/29
An Introduction of Geographic Information System Software (QGIS)
15
2021/05/30~2021/06/05
Seminar: Presentation of MA Students
16
2021/06/06~2021/06/12
Seminar: Presentation of MA Students
17
2021/06/13~2021/06/19
Seminar: Presentation of MA Students
18
2021/06/20~2021/06/26
Seminar: Presentation of MA Students
課業討論時間 Office hours
時段1 Time period 1: 時間 Time:星期三1000-1200 地點 Office/Laboratory:CM4067 時段2 Time period 2: 時間 Time:星期四1000-1200 地點 Office/Laboratory:CM4067
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
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 capabilities of the department and the university
課堂活動與評量方式 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.