本課程旨在培養學生對人工智慧(AI)與生成式人工智慧(Generative AI)之基本認識、應用能力與批判思維，使學生能瞭解 AI 技術發展脈絡、基本原理、應用情境及其對社會、產業與個人之影響。課程首先介紹 AI 的發展歷程、定義、分類與應用現況，說明人工智慧對產業轉型、工作型態及社會運作所帶來之機會與挑戰，並探討相關倫理議題。

課程進一步介紹鑑別式 AI 與生成式 AI 之基本概念與運作原理，使學生建立 AI 模型之基礎知識，並透過文字、圖像及影音生成工具實作，瞭解生成式 AI 之功能、限制與應用潛力。課程亦將透過實際案例分析，引導學生認識生成式 AI 在教育、商業、媒體、設計、研究及日常生活等領域之應用方式。

在掌握 AI 工具操作能力後，課程將進一步介紹 AI 治理、法規遵循、資料隱私與資訊安全等重要議題，使學生建立負責任使用 AI 之觀念。同時說明資料處理與分析之基本概念，培養學生理解 AI 應用所需之資料基礎能力。課程亦將介紹生成式 AI 導入評估與規劃方法，使學生能從問題分析、需求辨識及應用情境等面向，思考 AI 導入之可行性與潛在效益。

此外，課程將結合運算思維、程式思維及 No Code／Low Code 等概念，使學生瞭解如何運用數位工具與 AI 技術協助解決問題，降低技術門檻並提升創新能力。課程後期將透過生成式 AI 實作與應用練習，整合所學知識與技能，培養學生在學習、工作與生活情境中善用 AI 工具之能力，建立面對 AI 時代所需之數位素養、創新思維及終身學習能力。

This course aims to cultivate students' basic understanding, application ability and critical thinking of artificial intelligence (AI) and generative AI (Generative AI), so that students can understand the development context, basic principles, application scenarios and its impact on society, industry and individuals of AI technology. The course first introduces the development history, definition, classification and current application status of AI, explains the opportunities and challenges that artificial intelligence brings to industrial transformation, work patterns and social operations, and discusses related ethical issues.

The course further introduces the basic concepts and operating principles of discriminative AI and generative AI, allowing students to establish basic knowledge of AI models and implement them through text, image and video generation tools to understand the functions, limitations and application potential of generative AI. The course will also guide students through practical case analysis to understand the application of generative AI in fields such as education, business, media, design, research and daily life.

After mastering the ability to operate AI tools, the course will further introduce important issues such as AI governance, regulatory compliance, data privacy and information security, so that students can establish the concept of responsible use of AI. At the same time, the basic concepts of data processing and analysis are explained, and students are trained to understand the data-based abilities required for AI applications. The course will also introduce generative AI introduction evaluation and planning methods, allowing students to think about the feasibility and potential benefits of AI introduction from aspects such as problem analysis, demand identification and application scenarios.

In addition, the course will combine concepts such as computational thinking, procedural thinking, and No Code/Low Code to enable students to understand how to use digital tools and AI technology to help solve problems, lower technical thresholds, and enhance innovation capabilities. Later in the course, generative AI implementation and application exercises will be used to integrate the knowledge and skills learned, cultivate students' ability to make good use of AI tools in learning, work and life situations, and build the digital literacy, innovative thinking and lifelong learning capabilities required to face the AI ​​era.

劉立民，《人工智慧與應用實務 ─ 從基礎理論到生成式 AI 》，普林斯頓，2026。
勁樺科技，《AI Prompt Engineer提示工程師高效工作術》，台科大圖書，2025。

Liu Limin, "Artificial Intelligence and Application Practice - From Basic Theory to Generative AI", Princeton, 2026.
Jinhua Technology, "AI Prompt Engineer Tips for Engineers to Work Efficiently", National Taiwan University of Science and Technology Books, 2025.