| 開課班級Class： | 授課教師Teacher： | 學分數Credits： |
| 四生機三A | 張仲良 | 3 |
| 課程大綱Course Description： |
| 本課程內容包含人工智慧開發的方法以及其智慧系統的基礎知識、人工智慧的應用方式與實例以及人工智慧的未來發展趨勢，這另包括專家系統、演算計算、資料探勘與知識工程。另一方面，一些現有的Python語言和套件會用來示範其在迴歸、分類、模式辨識的效果。修課生能藉由此課程了解與認識人工智慧的內涵，並能應用此些概念與做法來解決各種產業問題。 |
| English Outline： |
| This course covers the development methods and foundational knowledge of artificial intelligence (AI) and its intelligent systems. It includes the application methods and examples of AI, along with discussions on future development trends in the field. The course also explores expert systems, computational methods, data mining, and knowledge engineering. Additionally, students will use Python programming language and its associated packages to demonstrate AI techniques in regression, classification, and pattern recognition. Through this course, students will gain a comprehensive understanding of AI concepts and practices, enabling them to apply these skills to solve various industrial problems effectively. |
| 本科目教學目標Course Objectives： |
| 本課程的教學目標在於培養學生對人工智慧（AI）及其智慧系統的基本專業知識和應用技術的理解。修課生將學習AI開發的方法、專家系統、運算方法、數據探勘及知識工程的相關知識，並掌握未來AI發展趨勢。此外，課程將使用Python語言及其相關套件，模擬在數據迴歸、分類及特徵識別領域的效果。修課生將具備應用這些AI概念和技術來解決各種產業問題的能力，以邏輯化思維找出問題的解決方案，為未來邁入職場時做好準備。 The teaching goal of this course is to cultivate understanding of the basic professional knowledge and application technology of artificial intelligence (AI) for student and its intelligent systems. Students taking this course will learn about AI development methods, expert systems, computing methods, data exploration, and knowledge engineering, and grasp future AI development trends. In addition, the course will use Python and its related packages to simulate applications in data regression, classification, and feature recognition. By the end of the course, students will be equipped with the ability to apply these AI concepts and technologies to solve various industrial problems, use logical thinking to find solutions, and be prepared to enter the workforce in the future. |
| 教學型態Teaching Models： | 成績考核方式Grading： |
| 課堂教學 | 平時成績General Performance：10% 期中考Midterm Exam：20% 期末考Final exam：30% 其它 Other：(出席率10%；作業15%；期末報告15%) |
| 參考書目Textbooks/References： |
| 謝政勳等人譯(2012)，人工智慧：智慧型系統導論(第三版)，全華圖書。ISBN: 978-986-280-095-9 張志勇等人(2023)，人工智慧(第三版)，全華圖書。ISBN:978-626-328-703-7 |
| SDGs指標： |
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| UCAN職業項目： |
| 課程更新狀態： | 課程匯入時間Import Time：2025-07-04 09:17:13 |
| 最後更新時間Last Modified：2025-07-04 09:33:03，更新人modified by： |