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餐旅管理學系在職專班
course information of 109 - 1 | 6860 Data Science for Business Analytics(餐旅商情分析與智慧應用)

6860 - 餐旅商情分析與智慧應用 Data Science for Business Analytics


教育目標 Course Target

本課程專為非資訊專業領域的餐旅經理人設計,希望透過本課程,讓研習者能夠對於數據分析方法建立正確清楚的基本觀念,並進一步地瞭解數據機器學習分析方法在商管領域的應用策略和相關實務案例。人工智慧與資料科學分析已成為萬眾矚目的焦點,每個領域都需要專精的數據分析人才,以及對商業情報的高度敏銳度,找出企業問題並協調組織面對,將能成為最有價值的企業高階經理人才。提升EMBA學生在人工智慧技術與巨量資料分析的技能與優勢,更可以讓學生將公司相關數據資料帶入課堂,達成學以致用的最佳發揮舞台。 內容涵蓋資料科學分析中資料的解理與如何收集,實際案例於電商顧客分群、預測電商潛在客戶、開放資料運用與視覺化、工廠製程優化、財務金融、零售行銷、社群媒體、文字分析、智慧製造等領域之發展與應用與策略布局。課程兼具學術理論與企業實務,以科技化、數位化的方式,將大數據分析的知識傳遞給所有需要的人。This course is specially designed for hotel and hospitality managers who are not majoring in information technology. It is hoped that through this course, participants can establish a correct and clear basic concept of data analysis methods and further understand the application of data machine learning analysis methods in the field of business management. Strategies and related practical examples. Artificial intelligence and data science analysis have become the focus of much attention. Each field requires specialized data analysis talents and high acumen for business intelligence. Identifying corporate problems and coordinating the organization to face them will become the most valuable of senior corporate managers. It enhances the skills and advantages of EMBA students in artificial intelligence technology and massive data analysis, and allows students to bring company-related data into the classroom to achieve the best stage for applying what they have learned. The content covers the interpretation and collection of data in data science analysis. Practical cases include e-commerce customer segmentation, prediction of potential e-commerce customers, open data application and visualization, factory process optimization, finance, retail marketing, social media, text The development, application and strategic layout of analysis, smart manufacturing and other fields. The course combines academic theory and corporate practice, and delivers the knowledge of big data analysis to all those who need it in a scientific and digital way.


參考書目 Reference Books

1.教師自行編輯講義。
2.統計學概論~大數據分析的領航員,謝邦昌編著。
3.吳萬益,2005,企業研究方法,華泰書局出版。
4.Big Data MBA.
5.資料科學的商業運用,碁峰書局。
6.統計學概論~大數據分析的領航員/謝邦昌編著。
1. Teachers edit handouts by themselves.
2. Introduction to Statistics ~ The Navigator of Big Data Analysis, edited by Xie Bangchang.
3. Wu Wanyi, 2005, Enterprise Research Methods, published by Huatai Book Company.
4.Big Data MBA.
5. Business Application of Data Science, Qi Feng Bookstore.
6. Introduction to Statistics ~ The Navigator of Big Data Analysis/Compiled by Xie Bangchang.


評分方式 Grading

評分項目 Grading Method 配分比例 Grading percentage 說明 Description
課程參與、出席率課程參與、出席率
Course participation, attendance
20
期中報告期中報告
interim report
40
期末報告期末報告
Final report
40

授課大綱 Course Plan

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Course Information

Description

學分 Credit:3-0
上課時間 Course Time:Wednesday/5,6,7[M215]
授課教師 Teacher:姜自強/陳錚中/朱惠玲
修課班級 Class:餐旅專班1,2
選課備註 Memo:
授課大綱 Course Plan: Open

選課狀態 Attendance

There're now 12 person in the class.
目前選課人數為 12 人。

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