校際選修

115-1 選課時程

進行中

  • 初選第一階段 6/15/2026
  • 初選第二階段 6/22/2026
  • 校際選修 8/24/2026
  • 初選第三階段 8/31/2026
  • 開學後加退選 9/7/2026
  • 逾期加退選 9/21/2026
選課資源

新興工程概論

Introduction to Recent Advances in Engineering

學期
110-2
學分
3 學分
當期課號
1209
永久課號
DME4623
開課單位
機械工程學系
授課教師
黃衍佐
校區
光復
類別
選修
上課時間表
週一
2
09:00–09:50
新興工程概論
EE230
3 節連堂
3
10:10–11:00
4
11:10–12:00

* 根據陽明交大上課時間表所列

概述

This course is to introduce and share recent advances in various areas related to engineering and technology 1. to introduce recent developments that are related to mechanical engineering 2. to introduce technological advances that fall beyond conventional mechanical engineering 3. to inspire students for the future applications with creative thinking 4. to encourage students to explore further defense related applications 5. to have students practice their presentation of their own concept/idea/design

先修科目

1. English – reading PPT in English 2. Math – high school level 3. programming – some experience is a plus but not necessary

教學方式

Note 1: In-class discussion and interaction are strongly encouraged (attendance). Note 2: Homework/project/quiz must be done and written by each student himself or herself. Duplicating, copying homework/project from other student(s) is not allowed. Overhead Projector and Internet Wi-Fi Connection will be needed

評分方式

Participation, Homework, Quiz 25% Midterm Test or Project 25% Final project Implementation 25% Final Project PPT & Presentation 25% 1. Choose project topic of your choice, preferably on application of recent advances in engineering 2. Present your work in PPT and in front of the class Presentation and communication are as important as, if not more than, the content of your work  Service to this class (as teamwork contribution) will be rewarded with extra points (學生之班級服務貢獻將可作為課業成績之加分考量)  Teacher has the unlimited right to adjust student’s final score at teacher’s full discretion (任課教師有評定成績之最後決定權, 包含 加分/減分) Machine Learning (AI) Methods and its application in Engineering supervised learning (data preparation) unsupervised learning Topics – defense application and others Automation Industrial Commercial Topics – defense application and others Robotics Industrial Humanoid Topics – defense application and others Industrial 4.0 Platform Data Communication Application Topics – defense application and others Project Development Agile Scrum Topics – defense application and others New Achievements New Products New Achievements Topics – defense application and others Others

週次計畫
週次主題
第 1 週Introduction AI/ML, video, example, discussion
第 2 週Introduction AI/ML, video, example, discussion HW1
第 3 週國定假日
第 4 週students to install Python and run a machine learning example; video of AI & claim-to-be-AI (to judge the difference of AI or not); MOST project of machine learning (AI) on engineering application;
第 5 週Introduction Robotics, vision-based application in robotics, video examples of various industrial and humanoid robotics, discussion
第 6 週Introduction Automation, video, Robotics kinematics basics example, discussion issue HW3
第 7 週Introduction Automation, video, Robotics kinematics basics example, discussion
第 8 週國定假日
第 9 週midterm Introduction Automation, video, Robotics control, PID, Robotic vision based control example, discussion
第 10 週Introduction Automation, video, Robotics kinematics basics Robotics control, vision based control issue HW4 (vision technology)
第 11 週Introduction Industry 4.0 video, example, discussion
第 12 週continue Industry 4.0 videos, example, discussion
第 13 週Industry 4.0 in various countries and focus, example, discussion Explain final project issue scheduling exercise
第 14 週WebEx remote Industry 4.0 (W.O. scheduling) example, discussion Explain final project
第 15 週WebEx remote Introduction project management, Waterfall, Agile, Scrum, video, example, discussion
第 16 週Final project presentation (report due 6/1 midnight)
第 17 週Final project presentation (report due 6/1 midnight)
第 18 週Q&A
教科書

Introduction to Machine Learning with Python, Andreas C. Muller & Sarah Guido 2. Robot Modeling and Control by Spong, Hunchinson, Vidyasagar, 2nd edition, John Wiley, 2020 3. PYTHON 程式設計與數據分析/白文章 編著 4. Public sources, Internet websites, videos, etc.