教學大綱 Syllabus

科目名稱：Web概念與技術

Course Name: Web Concepts and Technologies
  • 學年學期：112-1 Fall Semester, 2023
  • 科目代碼：753882001 Course No.753882001

修別：選

Type of Credit: Elective

3.0

學分數

Credit(s)

30

預收人數

Number of Students

課程資料Course Details
  • 開課單位：資碩工一、資碩計一 Course Department:Computer Science/M/1
  • 授課老師：謝佩璇 Instructor: HSIEH PEI-HSUAN
  • 先修科目：無Prerequisite(N/A)
  • 上課時間：二234 Session: tue09-12

課程簡介Course Description

In this course, students will acquire knowledge of web mining and deep learning for web development. The course covers various concepts, including taxonomy, scraping, social network analysis, and web applications. Students will also be introduced to different web applications that utilize deep learning technologies. Each concept will be presented through in-class hands-on sessions, either individually or in groups. Python sample codes will be provided to complement the covered concepts. Throughout the semester, additional reference materials will be provided, focusing on critical web architecture, common web services (such as CSS, SOAP, and XML), and the latest hot topics (including flow architecture, no/low code, progressive web apps vs. accelerated mobile pages). It is expected that students fully participate in all course activities. Additionally, they have the option to engage in self-study regarding security issues and end-to-end integration with APIs related to web development towards the end of the course.

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

    1. Students are able to acquire knowledge about web mining for web development.
    2. Students are able to gain knowledge about deep learning for web development. 
    3. Students are able to learn the techniques behind each web development concept. 

    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

    週次Week

    課程主題 Topic

    課程內容與指定閱讀 Content and Reading Assignment

    教學活動與作業Teaching Activities and Homework

    學習投入時間 Student workload expectation

    課堂講授

    In-class Hours

     

    課程前後

    Outside-of

    -class Hours

     

    W1 - Sept 12

    Introduction

    Syllabus Review /

    Intro of Web Mining Intro /

    Intro of Deep Learning for Web

    [WDM Ch1]

    3

    3

    W2 - Sept 19

    Web mining

    Web Mining Taxonomy

    [WDM Ch2]

    3

    3

    W3 - Sept 26

    Prominent Applications
    with Web Mining

    [WDM Ch3]

    3

    4.5

    W4 - Oct 03

    Web mining /

    Deep learning for Web

    Python Fundamentals  /

    AI and Fundamentals of ML

    [WDM Ch4]

    [DLW Ch1]

    3

    4.5

    W5 - Oct 10

    [NO CLASS]

    Review

    [WDM Ch1~4]

    0

    9

    W6 - Oct 17

    Web Scraping

    [WDM Ch5]

    3

    4.5

    W7 - Oct 24

    Web Opinion Mining

     

    [WDM Ch6]

    3

    4.5

    W8 – Oct 31

    Web Structure Mining /

    DL using Python and NN

    [WDM Ch7]

    [DLW Ch2]

    3

    4.5

    W9 –

    Nov 07

    Social Network Analysis in Python

    [WDM Ch8]

    3

    4.5

    W10 –

    Nov 14

    Web Usage Mining

    [WDM Ch9]

    3

    4.5

    W11 - Nov 21

    Deep learning for Web

    DL Web App

    [DLW Ch3]

    3

    4.5

    W12 – Nov 28

    TensorFlow.js

    [DLW Ch4]

    3

    4.5

    W13 – Dec 05

    DL through APIs

    [DLW Ch5]

    3

    4.5

    W14 –

    Dec 12

    DL on Google Cloud

    [DLW Ch6]

    3

    4.5

    W15 –

    Dec 19

     

    DL on AWS

    [DLW Ch7]

    3

    4.5

    W16 -

    Dec 26

    DL on Microsoft Azure

    [DLW Ch8]

    3

    4.5

    W17 -  Jan 02

    Production Framework for DL Enabled Websites

    [DLW Ch9]

    3

    4.5

    W18 – Jan 09

    Deep learning for Web (optional)

    Securing Web Apps with DL / Web DL Production Environment / E2E Web App using DL APIs and Customer Support Chatbot

    [DLW Ch10~12]

    0

    9

    授課方式Teaching Approach

    40%

    講述 Lecture

    0%

    討論 Discussion

    0%

    小組活動 Group activity

    30%

    數位學習 E-learning

    30%

    其他： Others: Individual hand-on sessions

    評量工具與策略、評分標準成效Evaluation Criteria

    80%  Pass a quiz or participate in a class activity in each session (5 points per session from W1 to W17, except W5).

    20% Self-study and then show any proof for the two sessions of the course (W5 NO class and W18).


     

    指定/參考書目Textbook & References

    Textbooks (Students are NOT required to purchase them.)

    • [WDM] Rajnish, R. & Srivastava, M. (2023). Web data mining with Python: Discover and extract information from the web using Python. London, UK: BPB Online.
    • [DLW] Singh, A. & Paul, S. (2020). Hands-on Python deep learning for the web: Integrating neural network architectures to build smart web apps with Flask, Django, and TensorFlow. Packt Publishing.

     

    References

    • Vincent, W. S. (2023). Django for beginners: Build websites with Python and Django. WelcomeToCode. [DfB] 
    • Urquhart, J. (2021). Flow architectures. The future of streaming and event-driven integration (1st ed.). Sebastopol, CA: O'Reilly Media. [FA]
    • Brikman, Y. (2019). Terraform: Up & running: writing infrastructure as code (2nd ed.). Sebastopol, CA: O'ReillyMedia. [IaC]

     

    Other Books

    • Miwa, H., Chen, H. C., & Barolli, L. (2021). Advances in intelligent networking and collaborative systems. The 13th International Conference on Intelligent Networking and Collaborative Systems (INCoS-2021). Springer International Publishing. 
    • Gilman, E., & Barth, D. (2017). Zero trust networks: Building secure systems in untrusted networks. Sebastopol, CA: O'Reilly Media. [ZTN]
    • Buyya, R., & Dastjerdi, A. V. (2016). Internet of things: Principles and paradigms. Cambridge, MA: Morgan Kaufmann.  [IoT] FULLTEXT VERSION 2016 IS AVAILABLE TO DOWNLOAD FROM NCCU LIBRARY.
    • Bean, J. D. (2016). SOA and Web services interface design principles, techniques, and standards. San Francisco, CA: Morgan Kaufmann; Oxford: Elsevier Science distributor. [SOA] FULLTEXT VERSION 2010 IS AVAILABLE TO DOWNLOAD FROM NCCU LIBRARY.
    • Mcllwraith, D. G., Marmanis, H., & Babenko, D. (2016). Algorithms of the intelligent (2nd eds.). web. Shelter Island, NY: Manning. [AI]
    • Rosenfeld, L., Morville, P., & Arango, J. (2015). Information architecture: For the web and beyond (4th ed.). Sebastopol, CA: O'Reilly. [IA] RESERVED AT NCCU LIBRARY BUT VERSION 2002 ONLY.

     

    Journal article readings:

    • World Wide Web-Internet and Web Information Systems
    • ACM Transactions on Internet Technology
    • IEEE Internet of Things Journal
    • IEEE INTERNET COMPUTING
    • Internet Research
    • Journal of Internet Technology
    • JOURNAL OF Medical Internet Research
    • KSII Transactions on Internet and Information Systems

    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

    SAP Business Objects Web Intelligence
https://help.sap.com/docs/SAP_BUSINESSOBJECTS_WEB_INTELLIGENCE?locale=en-US

(Chinese version)
https://help.sap.com/docs/SAP_BUSINESSOBJECTS_WEB_INTELLIGENCE/4ef7aa2cbf3d432a80d8b85a9c2c7e20/4733e21f6e041014910aba7db0e91070.html

    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

    是 Yes

    列印