Course Syllabus

Course Information：

Year-Semester	Course Number	Course Name	Phase	Credits	Hours	Required/Elective	Instructor	Class	Student NO.	Withdraw	Note
Fall Semester Year 2026	366624	Physical Technology and Application of Edge AI	1	3.0	3	★	Hong,Tzu-Yen Shu-Kai Fan	4IEM3A 4IEM3B	40	0	工管三甲乙合開

Course Plan：

Instructor	Shu-Kai Fan　Office Hours
Email	morrisfan@ntut.edu.tw
Last Updated	2026-08-06 13:10:41
Course Objective	本課程介紹終端人工智慧之實體技術與應用的核心概念與實務應用，聚焦於智慧系統如何透過感知、決策與行動與實體世界互動。課程內容涵蓋實體 AI 系統的重要基礎技術，包括機器學習感知模型、神經網路訓練、強化學習、模擬環境，以及系統整合等主題。並透過實作練習理解終端人工智慧於機器人、智慧裝置、自主系統等實體場域之實際應用建立對新興智慧實體技術發展趨勢的整體認識。 This course introduces the core concepts and practical applications of PhysicalTechnology and Edge AI, focusing on how intelligent systems interact with the physical world through perception, decision-making, and action. The course covers fundamental technologies of embodied AI systems, including machinelearning-based perception models, neural network training, reinforcement learning, simulation environments, and system integration. Through hands-on exercises, students will gain an understanding of the practical applications of Edge AI in physical domains such as robotics, smart devices, and autonomous systems, while developing a broad perspective on emerging trends in intelligent physical technologies.
Course Schedule (Week 1-16)	I will coordinate and oversee the final six weeks of the course, with most sessions delivered by engineers and technical specialists from Qualcomm Taiwan. This advanced module will provide comprehensive, hands-on coverage of the Arduino VENTUNO Q edge AI and robotics platform, focusing on its heterogeneous computing architecture, NPU-accelerated on-device inference, deterministic real-time control, embedded Linux–MCU co-design, multimodal sensing, and end-to-end deployment of intelligent cyber-physical systems.
Flexible Learning (Week 17-18)	Category ● 學生分組實作及討論(Student group practice and discussion) Content ** group presentations Hours 6 Learning Outcomes ** group term project demos Assessment Percentage 35%
Evaluation and grading policy	homework assignments group term projects
Materials	All right reserved. Do not reproduce without permission. Foreign-language textbooks:No The classnotes will be shared.
The access to curricular consultation	By appointment
Expanding teaching and resources	● 混成學習 (Blended Learning) 課程結合實體授課與線上學習（同步視訊／非同步活動）。 Combines face-to-face instruction with online learning (including synchronous video sessions or asynchronous activities). ● 參與式創新教學 (Participatory & Innovative Teaching) 強調學生參與與產出，導入翻轉、PBL/專題、設計思考或遊戲化等策略。 Emphasizes student engagement and outcomes by adopting strategies such as Flipped Classroom, PBL (Problem/Project- Based Learning), Design Thinking, or Gamification. ● 數位教材資源應用 (Application of Digital Resources) 採用影音多媒體或具開放授權之資源（如OCW、開放教科書）作為主要或輔助教材。 Adopts multimedia or open-licensed resources (e.g., OCW, Open Textbooks) as primary or supplementary teaching materials. ● 數位科技融入 (Digital Technology Integration) 運用生成式AI、VR/AR、IoT、IRS等新興科技輔助教學與評量。 Utilizes emerging technologies such as Generative AI, VR/AR, IoT, and IRS (Interactive Response Systems) to facilitate teaching and assessment.
The course corresponds to the SDGs	SDG4：優質教育（Quality Education） SDG9：產業創新與基礎設施（Industry, Innovation and Infrastructure）
Does the course incorporate AI	● 使用生成式AI作為教學過程的輔助工具（Use generative AI tools as an aid to the teaching process） ● 鼓勵學生使用生成式AI工具（Encourage students to use generative AI tools） ● 使用生成式AI進行課堂即時互動（Use generative AI for real-time classroom interaction） ● 簡單介紹AI的基本概念（Briefly introduce the basic concept of AI） ● 深入探討AI的原理與應用（Explore the principles and applications of AI in depth）
Note	N/A