人工智慧概論 AA
Introduction to Artificial Intelligence
115-1 課程介紹 · Course Introduction | 國立東華大學 通識教育中心 National Dong Hwa University
GENERAL EDUCATION · COURSE INTRO
Introduction to Artificial Intelligence人工智慧概論
From creative AI tools to supervised AI agents
Make real thingsBack it with evidenceKeep agents in check
做得出作品 · 查得到證據 · 管得住 Agent
COURSE INFO
Course Information課程資訊
Section / Code
Section AA · GC__6753AA · ID 115133850
General-education core elective · 3 credits · 17-week termAA 班・校核心選修・3 學分・17 週新制
General-education core elective · 3 credits · 17-week termAA 班・校核心選修・3 學分・17 週新制
Time
Monday, periods 8‑10 · 13:10–16:00 週一 第 8–10 節・13:10–16:00
Classroom
Science & Engineering Building II, Room E403理工二館 E403
Instructor
Prof. Wen-Sheng Chen · TA to be announced陳文盛・TA 另行公布
Contact
e-Learning message · wschen@gms.ndhu.edu.twe學苑課程訊息或 Email
Class Platforms
Roll call: Zuvio · Submit: e‑Learning · Notes: HackMD點名 Zuvio・教材與交作業 e學苑・共筆 HackMD
WHERE WE MEET
Where We Meet上課地點
E403AI 教室教室教室電梯樓梯光電系實驗室教授研究室光電系討論室光電系辦公室4F
Science & Engineering Building II · Room E403 AI Classroom
理工二館 E403・AI 教室
YOUR INSTRUCTOR
About Me — Wen-Sheng Chen關於我 陳文盛
Project Assistant Professor · General Education Center, NDHU專案助理教授・國立東華大學 通識教育中心
I'll help you put AI to work on real tasks—not just tool demos.我會帶你把 AI 用在真實任務，而不只看工具展示。
Email
wschen@gms.ndhu.edu.tw
Phone
03-890-6610
Office
Science & Engineering Building II, Room C306理工二館 C306
Contact
e-Learning message or emaile學苑課程訊息或 Email
OFFICE
My Office研究室位置
Science & Engineering Building II, Room C306
理工二館 C306
JOIN AT SLIDO.COM
Grab your phone—
let's meet you first拿出手機，先認識一下你
let's meet you first拿出手機，先認識一下你
Scan the QR to join slido.com · #1321545
Coming up: your department, what AI feels most like to you, and how you actually use AI.
等等問你：你的系所、AI 對你來說最像什麼、你平常怎麼用 AI
等等問你：你的系所、AI 對你來說最像什麼、你平常怎麼用 AI
#1321545
WHAT YOU'LL LEARN
What you'll learn: three parts這門課在學什麼：三部曲
Zero prerequisites—no coding, Git, or command-line background needed; every week runs Make → Test/Break → Make it yours.零先修——不要求程式設計、Git 或命令列背景；每週固定走 Make → Test／Break → Make it yours
PART 1
AI foundations & creationAI 基礎與創作
Tell tools, teammates, workflows and agents apart; make images, a web app, version safety, and source-backed research. Midterm = W2–7 skills.分辨工具、隊友、工作流與 Agent；做出圖像、web app、版本安全與來源查證。期中範圍＝W2–W7 的能力。
PART 2
Agent literacy & supervisionAgent 素養與監督
What counts as a real agent; task contracts, action preview, permissions, logs and recovery; agent-assisted data analysis.什麼才算真正的 Agent；任務契約、動作預覽、權限、log 與復原；Agent 輔助資料分析。
PART 3
Final project & showcase期末專題與成果節
One final piece: a task contract, two iterations, sources and tests, red-teaming and repair—shown at the showcase.收成一件作品：任務契約、兩次迭代、來源與測試、紅隊與修復，在成果節展出。
COURSE DESTINATION
The destination:
an AI workflow you can keep in check這門課的終點：一個你管得住的 AI 工作流
an AI workflow you can keep in check這門課的終點：一個你管得住的 AI 工作流
Not memorizing tool names—turning a real problem into work you can build, back with evidence, and keep under control.
不是背工具名稱，而是把一個真實問題，變成做得出來、查得到證據、也管得住的作品。
不是背工具名稱，而是把一個真實問題，變成做得出來、查得到證據、也管得住的作品。
01Make it做出作品
→
02Verify & test查證與測試
→
03Supervise & recover監督與復原
17-WEEK ROADMAP
17-Week Roadmap17 週課程地圖
W1
Intro & course guide課程介紹與修課導覽
W2
Prompts, images & judgment提問、圖像與人的判斷
W3
First web app with AI用 AI 做第一個 web app
W4
9/28 No class9/28 教師節停課
W5
10/05 Git + AI learningW4＋W5 版本＋學習
W6
Failure, bias & retraining失敗、偏誤與重訓
W7
10/19 Sources + mediaW7＋W8 查證＋多模態
PART 1 · AI FOUNDATIONS & CREATION (W1–W9)
W8
10/26 No class10/26 補假停課
W9
Midterm showcase期中 AI 作品展
W10
What makes a real agent?什麼才算真正的 AI Agent？
W11
Agent-assisted data analysisAgent 輔助資料分析
W12
Supervising agent actions監督 Agent 動作
W13
Agent-controlled web appAgent 控制的 web app
W14
Connecting AI to systems連接 AI 與外部系統
W15
Final project sprint期末專題衝刺
W16
Red team, repair & recover紅隊、修復與復原
W17
Final showcaseAI 期末成果節
PART 1 (cont.)
PART 2 · AGENT LITERACY & SUPERVISION (W10–W14)
PART 3 · FINAL PROJECT & SHOWCASE (W15–W17)
●=weekly topic ●=midterm/final milestone · bands=the three parts ｜ 每週主題・里程碑・三部曲分段
GRADING
How grades work成績怎麼算
10%
Participation平時成績
attendance & in-class record
20%
Assignments作業成績
set by teaching progress
30%
Midterm期中
midterm AI showcase
40%
Final期末
AI workflow project & presentation
Final = an AI workflow project: at least one main and one supporting AI capability, three tests, and one failure-and-recovery. You may build on earlier work—brand count, technical difficulty and public deployment earn no extra points.
期末＝AI 工作流專題：至少一項主要與一項輔助 AI 能力、三筆測試、一次失敗與復原；可沿用深化先前作品，品牌數量、技術難度與公開部署不加分。
期末＝AI 工作流專題：至少一項主要與一項輔助 AI 能力、三筆測試、一次失敗與復原；可沿用深化先前作品，品牌數量、技術難度與公開部署不加分。
GETTING HELP
Stuck? Here's how to reach me卡關了，怎麼找我
e-Learning (elearn4)
Post a course message—I check ite學苑課程訊息，我會看
Email
wschen@gms.ndhu.edu.tw
JOIN ON E-LEARNING
Join the course on e-Learning加入 e學苑課程
- Sign in at elearn4.ndhu.edu.tw with your school account用學校帳號登入 elearn4.ndhu.edu.tw
- Materials and submissions all live here教材與交作業都在這
OUR PLATFORMS
Tools we use online這門課的網路工具
Roll call
Zuvio課堂點名
Materials & submissions
e-Learning (elearn4)教材與交作業
Shared notes
HackMD課堂共筆
Live Q&A
Slido #1321545課堂互動
TOOLS WE'LL TRY
What you'll do hands-on課堂會親手做的事
Make things做出作品
Text & image generationAI drafts; you adopt, revise or reject
Audio, video & multimodalshort clips, captions, AI disclosure
Verify & data查證與資料
Source-backed researchclaims trace back to real sources
Data storiesclean, chart, spot-check the values
Versions & safety版本與安全
Version safety (Git/GitHub)diff, approve, recover—no commands
Agent supervisionAgent 監督
Task contractsoutcome, checks, limits, stop rules
Action preview & permissionsdry-run, approve, log, recover
Roll callZuvio
Materials & submite-Learning
NotesHackMD
Tools change, skills don't. We grade tasks, evidence, permissions, verification and recovery—never product interfaces. 工具會換、能力不換。
FOR DAILY USE
Everyday AI tools日常 AI 工具推薦
Chat AI
ChatGPT·Claude·Gemini·Grok聊天型 AI
AI search
Perplexity·Felo — leads, not proofAI 搜尋
AI notebook
NotebookLM · read with sourcesAI 筆記本
No-account paths
offline, no-account options免帳號與離線路徑
Pick one that fits you—pre-course accounts are ungraded, and payment is never required. 挑一個順手的就好；課前辦的帳號不計分，付費一律不用。
WHAT TO BRING
What to bring上課要帶什麼
- A laptop or tablet (laptop recommended)—no device? Paper and pre-generated equivalents count the same筆電或平板（建議筆電）；沒有裝置也有等值路徑
- Set up three things before term (ungraded; equivalent paths if they fall through): a GitHub account (Week 4), an agent desktop app (Antigravity or ChatGPT desktop), and a chat AI—install, sign in, then stop. Payment is never required課前先辦好三樣（不計分、辦不成有等值路徑）：GitHub 帳號（W4 用）、agent 桌面 app 二擇一、一個聊天型 AI——裝好登入就停手；付費一律不用
- Room E403—seats near outlets go first-come教室 理工二館 E403——有插座的位子先到先選
HOW WE USE AI
How we use AI in this course這門課的 AI 使用守則
You may learn and create with AI—but you must:可以用 AI 學習與創作，但你要——
01
Explain your own process能解釋自己的過程
Be able to say how you asked, how you revised, and why you decided that way.說得出你怎麼問、怎麼改、為什麼這樣決定。
02
Verify what AI gives you會查證 AI 的輸出
AI gets things wrong and makes things up; check before you hand it in.AI 會錯也會編；交出去前你要查過。
03
Integrity & safety守學術誠信與安全底線
Honor integrity, privacy and copyright; use only public or synthetic data.遵守誠信、隱私與著作權；只用公開或合成資料。
BACK TO SLIDO
Last thing—
tell me what you hope for最後，聊聊你的期待
tell me what you hope for最後，聊聊你的期待
Scan slido.com once more · #1321545
Why you're taking this, one problem you want AI to help you solve, and one word for your hopes.
修課動機、你最想讓 AI 幫你解決的問題、一個詞形容你的期待
修課動機、你最想讓 AI 幫你解決的問題、一個詞形容你的期待
#1321545
SEE YOU NEXT WEEK
Welcome to
Introduction to AI歡迎來到人工智慧概論
Introduction to AI歡迎來到人工智慧概論
Next week: prompts, images & human judgment—how to ask, how to revise, and when to say no.
下週預告：提問、圖像與人的判斷——怎麼問、怎麼改、什麼時候該拒絕
下週預告：提問、圖像與人的判斷——怎麼問、怎麼改、什麼時候該拒絕
Your small task: bring one problem you'd like AI to help you solve.下週的小任務：帶一個你想用 AI 解決的問題來
Course site: cwstedctw.github.io/ndhu-ted-course-hub/courses/11501-ai-intro-aa/ 課程網站
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