教學大綱表 (115學年度 第1學期)
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課程名稱
Course Title
(中文) 人工智慧
(英文) Artificial Intelligence
開課單位
Departments
資訊經營學系
課程代碼
Course No.
N4810
授課教師
Instructor
方怡文
學分數
Credit
3.0 必/選修
core required/optional
選修 開課年級
Level
大四
先修科目或先備能力(Course Pre-requisites):無
課程概述與目標(Course Overview and Goals):This course introduces the fundamental technologies and concepts of artificial intelligence, as well as key developments in its applications. Topics include the basic concepts of artificial intelligence, data processing and analysis, machine learning, discriminative AI and generative AI, no-code and low-code development, and the application areas and tools of generative AI. The course aims to help students establish a foundational understanding of artificial intelligence theories and develop the ability to plan and implement AI applications.
本課程將介紹人工智慧基本技術、知識概念,重要應用發展,如人工智慧概念、資料處理與分析概念、機器學習概念、鑑別式AI與生成式AI概念、No code / Low code 概念、生成式AI應用領域與工具使用等,協助學生建立基本人工智慧基本學理知識與應用能量。
教科書(Textbook) Artificial Intelligence: A Modern Approach(4th Edition),Stuart Russell and Peter Norvig,Pearson Education,2022
Hands-On Machine Learning with Scikit-Learn, Keras, and Tensorflow: Concepts, Tools, and Techniques to Build Intelligent Systems, 3/e, Aurélien Géron,O'Reilly Media,2024-01-04
課程大綱 Syllabus 學生學習目標
Learning Objectives
單元學習活動
Learning Activities
學習成效評量
Evaluation
備註
Notes

No.
單元主題
Unit topic
內容綱要
Content summary
1 Introduction to AI (課程規劃介紹) Course overview and grading criteria (課程規劃介紹與評分標準說明) Introduction to Artificial intelligence (了解人工智慧課程規劃) 講授
 
2 Concepts of Artificial Intelligence (人工智慧概念) 1. Definition and Classification of AI
2. Concepts of AI Governance
Understand the concepts of Artificial Intelligence
(了解人工智慧概念)
討論
講授
 
3 Concepts of Data Processing and Analysis (資料處理與分析概念) 1. Basic Concepts and Sources of Data
2. Data Preparation and Analysis Process
3. Data Privacy and Security
Understand the concepts of data processing and analysis
(了解資料處理與分析概念)
討論
講授
 
4 Concepts of Machine Learning (機器學習概念) 1. Basic Principles of Machine Learning
2. Common Machine Learning Models
Understand the concepts of machine learning
(了解機器學習概念)
討論
講授
 
5 Concepts of Discriminative AI and Generative AI (鑑別式 AI 與生成式 AI 概念) 1. Basic Principles of Discriminative AI and Generative AI
2. Integrated Applications of Discriminative AI and Generative AI
Understand the concepts of discriminative AI and generative AI
(了解鑑別式 AI 與生成式 AI 概念)
討論
講授
 
6 Concepts of No-Code and Low-Code Development (No Code/Low Code 概念) 1. Basic Concepts of No-Code and Low-Code Development
2. Advantages and Limitations of No-Code and Low-Code Development
Understand the concepts of No-Code and Low-Code development
(了解No Code/Low Code 概念)
討論
講授
 
7 Generative AI Application Areas and Tool Usage (生成式 AI 應用領域與工具使用) 1. Generative AI Application Areas and Common Tools
2. Effective Use of Generative AI Tools
Understand Generative AI application areas and tool usage
(了解生成式 AI 應用領域與工具使用)
討論
講授
 
8 Mid-term exam 期中考 Mid-term exam
期中考
Mid-term exam
期中考
 
9 Generative AI Implementation Assessment and Planning (生成式 AI 導入評估規劃) 1. Generative AI Implementation Assessment
2. Generative AI Implementation Planning.
3. Generative AI Risk Management
Generative AI implementation assessment and planning
(了解生成式 AI 導入評估規劃)
討論
講授
 
10 Discriminative AI Application Cases (鑑別式AI應用案例) 1. Discriminative AI Application Cases
2.Discuss the pros and cons of the cases
Understand Discriminative AI Application Cases
(了解鑑別式AI應用案例)
討論
講授
 
11 Generative AI application cases (生成式AI 應用案例) 1. Generative AI Application Cases
2.Discuss the pros and cons of the cases
Understand Generative AI application cases
(了解生成式AI 應用案例)
討論
講授
 
12 Paper Review- using machine learning applications (文獻研析) 1. Supplementary paper review of machine learning applications
2.Discuss and analyze the contents of chosen papers
Study the current research paper and understand the status of this research area.
(研究文獻了解本領域研究現況)
討論
講授
 
13 Paper Review- generative AI applications (文獻研析) 1. Supplementary paper review of generative AI applications
2.Discuss and analyze the contents of chosen papers
Study the current research paper and understand the status of this research area.
(研究文獻了解本領域研究現況)
討論
講授
 
14 Paper Review-AI agent applications (文獻研析) 1. Supplementary paper review of AI agent applications
2.Discuss and analyze the contents of chosen papers
Study the current research paper and understand the status of this research area.
(研究文獻了解本領域研究現況)
討論
講授
 
15 Final project presentation (期末成果) Final project presentation Final project presentation
(期末成果)
討論
心得發表
 
16 Final Exam (期末考) Final Exam
(期末考)
Final Exam
(期末考)
 
彈性教學週活動規劃

No.
實施期間
Period
實施方式
Content
教學說明
Teaching instructions
彈性教學評量方式
Evaluation
備註
Notes
1 起:2026-12-28 迄:2027-01-08 2.非同步線上課程 Asynchronous online course Understand the current development of AI agent (了解AI agent的應用現況) 閱讀線上教材並完成線上測驗


教學要點概述:
1.自編教材 Handout by Instructor:
■ 1-1.簡報 Slides
■ 1-2.影音教材 Videos
□ 1-3.教具 Teaching Aids
■ 1-4.教科書 Textbook
□ 1-5.其他 Other
□ 2.自編評量工具/量表 Educational Assessment
□ 3.教科書作者提供 Textbook


成績考核 Performance Evaluation: 作業:10%   報告:20%   期中考:30%   期末考:30%   彈性教學:10%  

教學資源(Teaching Resources):
□ 教材電子檔(Soft Copy of the Handout or the Textbook)
□ 課程網站(Website)