本課程旨在培養學生具備面向未來職場所需之**AI素養（AI Literacy）與數位轉型思維，系統性介紹大數據（Big Data）、人工智慧（Artificial Intelligence, AI）、機器學習（Machine Learning, ML）與生成式人工智慧（Generative AI）**等核心概念、技術架構與應用實務。課程結合理論基礎、案例分析與實作演練，協助學生理解人工智慧技術的發展脈絡、運作原理及其對產業與社會的影響，建立跨領域應用與問題解決能力。
課程內容涵蓋人工智慧發展趨勢、資料驅動決策、機器學習基本概念，以及各類 AI 工具與應用情境，並探討人工智慧如何應用於企業管理、行銷分析、顧客服務、供應鏈管理、金融科技、智慧製造與創新創業等領域。學生亦將深入認識生成式人工智慧的最新發展，了解大型語言模型（Large Language Models, LLMs）與多模態人工智慧技術如何改變知識工作、生產流程與商業模式。
為提升學生實際運用生成式 AI 的能力，課程將特別介紹**提示工程（Prompt Engineering）**的核心原則與實務技巧，學習如何透過有效的提示設計提升 AI 產出品質，並應用於資訊蒐集、內容創作、商業分析、專案管理及決策支援等情境。透過實際操作與案例練習，培養學生善用 AI 工具提升學習效率與工作效能的能力。
《 課程簡介 -- English 》
This course aims to equip students with the **AI literacy and digital transformation mindset** required for the future workplace, providing a systematic introduction to core concepts, technical architectures, and practical applications of **Big Data, Artificial Intelligence (AI), Machine Learning (ML), and Generative AI**. By integrating theoretical foundations, case studies, and hands-on exercises, the course helps students understand the historical development, operational principles, and societal and industrial impacts of AI technologies, while building their ability to apply these concepts across disciplines and solve problems.
The course content covers AI development trends, data-driven decision-making, fundamental concepts of machine learning, and various AI tools and application scenarios. It also explores how AI is applied in fields such as business management, marketing analytics, customer service, supply chain management, fintech, smart manufacturing, and innovation and entrepreneurship. Students will also gain an in-depth understanding of the latest developments in generative AI, learning how Large Language Models (LLMs) and multimodal AI technologies are transforming knowledge work, production processes, and business models.
To enhance students’ ability to apply generative AI in practice, the course will specifically introduce the core principles and practical techniques of **prompt engineering**. Students will learn how to improve the quality of AI outputs through effective prompt design and apply these skills in scenarios such as information gathering, content creation, business analysis, project management, and decision support. Through hands-on exercises and case studies, students will develop the ability to effectively utilize AI tools to enhance their learning efficiency and work productivity.
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