NCHU Course Outline
Course Name (中) 人工智慧之應用(6357)
(Eng.) Application of Artificial Intelligence
Offering Dept Department of Bio-Industrial Mechatronics Engineering
Course Type Elective Credits 3 Teacher TSAI YAO CHUAN
Department Department of Bio-Industrial Mechatronics Engineering/Graduate Language 中/英文 Semester 2026-SPRING
Course Description 本課程旨在介紹人工智慧之基本原理與其於生物系統工程及智慧農業領域之應用。課程內容涵蓋機器學習、深度學習、影像辨識、電腦視覺及智慧決策技術之基礎概念與方法。課程將著重於人工智慧技術於智慧農業之實務應用，包括作物生長監測、病蟲害影像辨識、自動化農業機械視覺系統、農產品品質檢測及環境感測資料分析等。並透過案例介紹，使學生了解如何利用人工智慧技術提升農業生產效率、降低人力需求並促進精準農業之發展。
This course aims to introduce the fundamental principles of artificial intelligence and its applications in biological systems engineering and smart agriculture. The course covers the basic concepts and methods of machine learning, deep learning, image recognition, computer vision, and intelligent decision-making technologies. The course emphasizes the practical applications of artificial intelligence in smart agriculture, including crop growth monitoring, pest and disease image recognition, automated agricultural machinery vision systems, agricultural product quality inspection, and environmental sensing data analysis. Through case studies, students will learn how artificial intelligence technologies can be applied to improve agricultural productivity, reduce labor requirements, and promote the development of precision agriculture.
Prerequisites
self-directed learning in the course Y
Relevance of Course Objectives and Core Learning Outcomes(%) Teaching and Assessment Methods for Course Objectives
Course Objectives Competency Indicators Ratio(%) Teaching Methods Assessment Methods
1.了解人工智慧之基本原理與方法。To understand the fundamental principles and methods of artificial intelligence.
2.認識人工智慧於智慧農業及生物系統工程之應用。To recognize the applications of artificial intelligence in smart agriculture and biological systems engineering.
3.具備影像辨識與資料分析之基礎能力。To develop basic abilities in image recognition and data analysis.
4.培養應用人工智慧解決農業工程問題之能力。To cultivate the ability to apply artificial intelligence to solve agricultural engineering problems.
5.建立智慧農業系統整合之基本觀念。To establish fundamental concepts of smart agriculture system integration.
topic Discussion/Production
Discussion
Other
Lecturing
Written Presentation
Attendance
Oral Presentation
Assignment
Course Content and Homework/Schedule/Tests Schedule
Week Course Content
Week 1 課程介紹與人工智慧概論
Course introduction and overview of artificial intelligence
Week 2 人工智慧發展歷史與智慧農業應用介紹
History of AI and applications in smart agriculture
Week 3 機器學習基本概念
Fundamentals of machine learning
Week 4 常用機器學習方法介紹
Machine learning methods
Week 5 深度學習概論
Introduction to deep learning
Week 6 類神經網路原理
Fundamentals of neural networks
Week 7 影像辨識與電腦視覺概論
Introduction to image recognition and computer vision
Week 8 卷積神經網路介紹
Convolutional Neural Networks (CNN)
Week 9 人工智慧於作物生長監測之應用
AI applications in crop growth monitoring
Week 10 人工智慧於病蟲害影像辨識之應用
AI applications in pest and disease detection
Week 11 人工智慧於農產品品質檢測與智慧農業之應用
AI applications in agricultural product quality inspection
Week 12 智慧農業系統整合與案例分析
Smart agriculture system integration and case studies
Week 13 學生專題報告（一）
Student presentations (I)
Week 14 學生專題報告（二）
Student presentations (II)
Week 15 學生專題報告（三）
Student presentations (III)
Week 16 學生專題報告（四）
Student presentations (IV)
self-directed
learning		    01.Participation in professional forums, lectures, and corporate sharing sessions related to industry-government-academia-research exchange activities.
   02.Viewing multimedia materials related to industry and academia.
   03.Preparing presentations or reports related to industry and academia.
   04.Participation in visits or internships at industry, government, or academic institutions.
   05.Participation in various workshops organized by different departments of NCHU.
   06.Participation in field trips and outdoor instructional activities at other NCHU campuses or branches, including experimental forests or test sites.
Evaluation
課堂參與及出席(20%)+作業(20%)+學生專題報告(60%)
Class participation and attendance (20%) + Homeworks (20%) + Student project presentation (60%)
Textbook & other References
No required textbook.

References:
1. Mitchell, M. Artificial Intelligence: A Guide for Thinking Humans.
2. Spellman, F. R. Artificial Intelligence in Agriculture.
Teaching Aids & Teacher's Website
In ilearning website
Office Hours
Every Tuesday, 10:00 AM – 12:00 PM
Sustainable Development Goals, SDGs(Link URL)
01.No Poverty   02.Zero Hunger   03.Good Health and Well-Being   08.Decent Work and Economic Growth   09.Industry, Innovation and Infrastructure   11.Sustainable Cities and Communities   12.Responsible Consumption   13.Climate Actioninclude experience courses：N
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Update Date, year/month/day：2026/02/22 16:30:29 Printed Date, year/month/day：2026 / 3 / 10
The second-hand book website：http://www.myub.com.tw/