教學大綱 Syllabus

科目名稱:新興資訊技術發展與應用

Course Name: Development and Application of Emerging Information Technology

修別:選

Type of Credit: Elective

3.0

學分數

Credit(s)

3

預收人數

Number of Students

課程資料Course Details

課程簡介Course Description

The course objectives are the in-depth discussions on the development and application of emerging information technologies, including AI, BlockChain, Big Data Analytics, and others.

 

核心能力分析圖 Core Competence Analysis Chart

能力項目說明


    課程目標與學習成效Course Objectives & Learning Outcomes

    ※主題一: 資料分析,授課老師:莊皓鈞老師、周彥君老師

    利用數據分析與人工智慧的技術,從大量的資料中獲取有用資訊,以幫助管理者優化營運決策,是現代企業發展的重要核心。本課程將深入探討描述型、預測型和處方型分析模型的原理和不同產業的應用,包含實體和線上零售通路、半導體零組件通路、財金等領域;主要技術為統計機器學習、優化演算法、電腦模擬、資料視覺化等。

     

    ※主題二: AI授課老師:蔡瑞煌老師、郁方老師

    我們會要求(DBA)學生提出他們正在研究的新興人工智慧技術的研究問題。 學生將從有關開發和應用的深入討論中學習。 在本課程結束時,學生應:(1)獲得新興人工智慧技術的開發和應用的方法、演算法和實現的一般知識,以及(2)提交可投稿到專業/學術期刊的論文報告(working paper)

    ※主題三: 區塊鏈技術:商業創新與應用,授課老師:陳 恭老師

    本課程以深入淺出的方式介紹區塊鏈技術的內涵與商業應用的發展途徑。再透過一系列的個案探討,檢視各種區塊鏈的商業應用模式,引導學生思考區塊鏈技術的核心價值,以及對未來商業運作可能帶來的衝擊與機會。

    每周課程進度與作業要求 Course Schedule & Requirements

    教學週次Course Week 彈性補充教學週次Flexible Supplemental Instruction Week 彈性補充教學類別Flexible Supplemental Instruction Type

    ※主題一: 資料分析,授課老師:莊皓鈞老師、周彥君老師

    每周課程進度與作業要求:

    課次/日期

    課程主題

    課程內容與指定閱讀

    教學活動、上課方式

    課前要求/課後要求

    授課教師

    第1次

    Product & Consumer Analytics

    Chang et al. (2018) Will firm’s marketing efforts on owned social media payoff? A quasi-experimental analysis of tourism products. Decision Support Systems.

     

    Ascarza (2018) Retention utility: Targeting high-risk customers might be ineffective. Journal of Marketing Research.

    閱讀討論

    線性迴歸

    處方效果

    二元分類

    實務案例分享與討論

    觀看HBR迴歸分析影片

    課前閱讀論文掌握研究問題和主要發現。

    周&莊

    第2次

    Predictive & Prescriptive Analytics

    Chuang et al. (2021) Cross-item learning for volatile demand forecast: An intervention with predictive analytics. Journal of Operations Management.

     

    Senoner et al. (2022) Using explainable artificial intelligence to improve process quality: Evidence from semiconductor manufacturing. Management Science.

    閱讀討論

    XGBoost

    SHAP

    實務案例分享與討論

    課前閱讀論文掌握研究問題和主要發現。

    周&莊

    第3次

    Optimization & Simulation

    Ahire & Pekgun (2018) Harvest hope food bank optimizes its promotional strategy to raise donations using integer programming. Informs Journal on Applied Analytics.

    閱讀討論

    數學規劃

    隨機模擬

    實務案例分享   

     

     

    課前閱讀論文掌握研究問題和主要發現。課後繳報告,題目待訂定。

    周&莊

    學生學習投入時間

    每週課堂教學時數:4 小時

    每週預習/複習時數:2-4 小時

     

     

    ※主題二: AI授課老師:蔡瑞煌老師、郁方老師

    每周課程進度與作業要求:

    課次/日期

    課程主題

    課程內容與課前指定閱讀

    教學活動、上課方式

    課前作業要求/課後作業要求

    授課教師

    第4次

    人工智慧AI文章討論

    AI_ANN_AI application_2023

    Artificial Intelligence for the Real World -- Don’t start with moon shots, T. H. Davenport & R. Ronanki, HBR, Jan.-Feb. 2018

    In-depth communications and discussions as well as lecture.

     

    HW #1: Make a list of (potential and implemented) AI applications in your company or your industry

    蔡瑞煌老師

    第5次

    人工智慧AI書籍閱讀討論

    Artificial Intelligence: The Insights You Need from Harvard Business Review

    Harvard Business Review, Thomas H. Davenport, Erik Brynjolfsson, Andrew McAfee, H. James Wilson

    Pub Date: Sep 17, 2019

    Product #: 10281-PDF-ENG

    Discussion:

    1. Understanding AI and Machine Learning

    2. AI Models

    3. Adopting AI

    HW #2: Plan your pilot AI project

     

    郁   方老師

    第6次

    人工智慧AI文章討論

    State of AI report 2023

    N. Benaich and I. Hogarth. Oct. 2023

     

    AI Security

    Making machine learning robust against adversarial inputs

    I. Goodfellow, P. McDaniel, N. Papernot. CACM, Vol 61-7, 2018

     

    Robustness and Explainability of Artificial Intelligence: from technical to policy solutions.

    R. Hamon, H. Junklewitz, I.  Sanchez. (2020). 10.2760/57493. 

     

    Discussion:

    1. Facebook Case Study
    2. AI and the future of work
    3. The future of AI
    4. AI state of the art
    5. AI Security Issues

     

     

    郁   方老師

    第7次

    人工智慧AI個案討論

    SenseTime: World’s Most Valuable Artificial Intelligence Startup, Rainny Shuyan Xie, Boon-Siong Neo, Wee-Kiat Lim and Wai Fong Boh, HBSP No.: NTU202

    The AI Tech Stack_2023

    Case teaching and lecture.

     

    HW #3: Make a comparison between your company and SenseTime regarding the strategical, managerial, and operational arrangement in deploying the AI.

    蔡瑞煌老師

    第8次

    人工智慧AI文章討論

    Competing in the age of AI -- How machine intelligence changes the rules of business, Marco Iansiti, Karim R. Lakhani, HBR, Jan/Feb 2020

    金融AI雲以台灣證券業為例

    In-depth communications and discussions as well as lecture.

    HW #4: What is the strategy of your company in the age of AI

    蔡瑞煌老師

    學生學習投入時間:

    每週課堂教學時數: 3 .5小時

    每週預習/複習時數: 4~6小時

     

    ※主題三: 區塊鏈技術:商業創新與應用,授課老師:陳 恭老師

    每周課程進度與作業要求

    課次/日期

    課程主題

    課程內容與指定閱讀

    教學活動、上課方式

    課前要求/課後要求

    授課教師

    第9次

    區塊鏈與智能合約介紹,區塊鏈商業應用分析

    1. 陳恭,區塊鏈革命 迎向產業新契機
    2. 陳恭,智能合約的發展與應用https://www.fisc.com.tw/Upload/b0499306-1905-4531-888a-2bc4c1ddb391/TC/9005.pdf
    3. 陳恭,區塊鏈與數位轉型,https://www.hbrtaiwan.com/article_content_AR0009452.html
    4. HbR,哈佛商業評論,建立透明供應鏈:善用區塊鏈,提升信任、效率和速度,https://www.hbrtaiwan.com/article_content_AR0009678.html

    講課與討論

    分組

    陳 恭老師

    第10次

    基於區塊鏈的代幣(Token)應用與去中心金融發展

    1. 陳恭,運用區塊鏈進行資產代幣化, http://www.smctw.tw/portfolio-item/?p=6825/
    2. Steve Kaczynski and Scott Duke Kominers (2021), How NFTs create Value, Harvard Business, Nov. 10, 2021, https://hbr.org/2021/11/how-nfts-create-value
    3. Marco Di Maggio, Wenyao Sha and Nicolas Andreoulis (2021), Awakening the Blockchain: An Overview of DeFi, August 2021, Background Note, HBS Case Collection

    講課與討論,

    線上影片

     

    陳 恭老師

    第11次

    區塊鏈商業應用之評估框架與個案解析

    1. Gräther, Wolfgang, Klein, Sandra, Prinz, Wolfgang, A Use Case Identification Framework and Use Case Canvas for identifying and exploring relevant Blockchain opportunities, 2018, Proceedings of 1st ERCIM Blockchain Workshop 2018
    2. 陳恭,劉柏定, 導入區塊鏈之應用場域與評估準則”, Ch.3 in區塊鏈+ 時代的社經變革與創新思維 - 財團法人中技社,2019

    講課與討論

     

    陳 恭老師

    第12次

    延伸個案、

    分組簡報

    指定個案討論、學生分組簡報

    心得報告與討論

     

    陳 恭老師

    學生學習投入時間:

    每週課堂教學時數:3.5 小時

    每週預習/複習時數:2小時

     

    授課方式Teaching Approach

    47%

    講述 Lecture

    40%

    討論 Discussion

    10%

    小組活動 Group activity

    3%

    數位學習 E-learning

    0%

    其他: Others:

    評量工具與策略、評分標準成效Evaluation Criteria

    1. GRADE DISTRIBUTION:

    Weekly meeting attendance (1% x 18) 20%

    Meeting participation                       40%

    Homework                                 40%

    Total                                                   100%

     

    2. CONTRIBUTION EVALUATION:

        You are expected to attend each meeting on time with the assigned readings prepared in advance and to contribute to the meeting discussion either by starting the discussion or building on the contribution of others to move the discussion forward. The sharing of your experience and insights is a key part of the leaning process. To build on the contribution of others requires you to listen and to consider the timing of your participation.

        Meaningful meeting participation will be a factor in the determination of your grade. As in all meetings the more you put into a meeting the more you get out of it. We encourage the sharing of ideas with the meeting during meeting discussions. You are of course responsible for all material discussed in meeting even if you are absent. If you miss a meeting you must get notes from someone else in the meeting and you should designate someone to pick up any handouts for you. When you attend meeting you must be on time and remain for the entire meeting.

        The quality and frequency of your contribution will be taken into account in the grading scheme and will include the quality of your responses when cold called. You will be evaluated after every meeting session using the following criteria. Please note that contributions are NOT equivalent to only attending meeting or talking in meeting. The quality of what is said and of one's listening and responding to others are important components of my evaluation.

        Excellent Participation (A): (1) regularly initiates meeting discussions; (2) contributes consistently to meeting discussions; (3) regularly gives indication of substantial knowledge and insights; (4) frequently facilitates others in clarifying and developing their own viewpoints; (5) regularly builds on the thinking of others and integrates that thinking into own contributions to produce a larger synergistic understanding of the issues being discussed.

        Good Participation (B): (1) frequently initiates meeting discussions; (2) contributes consistently to meeting discussions; (3) regularly gives indication of substantial knowledge and insights; (4) occasionally facilitates others in clarifying and developing their own viewpoints.

        Fair Participation (C): (1) occasionally initiates meeting discussions; (2) contributes occasionally to meeting discussions; (3) gives indication of some knowledge and insights; (4) almost never responds constructively to the contribution of others.

        Poor Participation (D): (1) never or almost never initiates meeting discussions; (2) never or almost never contributes to meeting discussions; (3) is late for, does not attend, or is not prepared for 3 or more meetings; (4) actively inhibits or impedes the course of discussion; (5) exhibits defensive behavior such as aggression or withdrawal rather than being thoughtful and considerate of others' ideas.

        Failing Participation (F): (1) never or almost never initiates meeting discussions; (2) never or almost never contributes to meeting discussions; (3) is late for, does not attend, or is not prepared for 6 or more meetings; (4) actively inhibits or impedes the course of discussion; (5) exhibits defensive behavior such as aggression or withdrawal rather than being thoughtful and considerate of others' ideas.

    指定/參考書目Textbook & References

    DBA office will help buy and distribute the course materials.

    已申請之圖書館指定參考書目 圖書館指定參考書查詢 |相關處理要點

    維護智慧財產權,務必使用正版書籍。 Respect Copyright.

    課程相關連結Course Related Links

    
                

    課程附件Course Attachments

    課程進行中,使用智慧型手機、平板等隨身設備 To Use Smart Devices During the Class

    Yes

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