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 362572 Artificial Intelligence for Optoelectronics Applications 1 3.0 3 ★ Yibeltal Chanie Manie 4EOE2 47 0 計中電腦教室

Year-Semester	Course Number	Course Name	Phase	Credits	Hours	Required/Elective	Instructor	Class	Student NO.	Withdraw	Note
Fall Semester Year 2026	362572	Artificial Intelligence for Optoelectronics Applications	1	3.0	3	★	Yibeltal Chanie Manie	4EOE2	47	0	計中電腦教室

Course Plan：

Instructor Yibeltal Chanie Manie　Office Hours

Email yibeltal_chanie@mail.ntut.edu.tw

Last Updated 2026-06-05 13:57:37

Course Objective 1. 人工智慧簡介及基本概念 2. 各種人工智慧技術介紹 3. 人工智慧工具和框架 4. 人工智慧在光電領域的應用 1. Introduction and basic concepts of artificial intelligence 2. Introduction to various artificial intelligence technologies 3. Artificial intelligence tools and frameworks 4. Application of artificial intelligence in the field of optoelectronics

Course Schedule 1-3 Introduction and basic concepts of artificial intelligence 4-5 Intelligent systems 6-7 Introduction to Machine learning 7-8 Introduction to Deep Learning 9-11 Computer vision 12-13. Generative AI 14 . AI agent and Agentic AI 15. Recent trends of AI 16 Application of artificial intelligence in the field of optoelectronics 17-18 Final Project

Evaluation and grading policy Homeworks: 40% Labs / Mini Projects: 20 % Class Participation and Attendance: 10% Final project and report: 30%

Materials All right reserved. Do not reproduce without permission.

Foreign-language textbooks:Yes
References : 1. Goodfellow, I., Bengio, Y. & Courville, A.: Deep Learning. 2016, MIT. 2. Anirudh Koul, Siddha Ganju, Meher Kasam: Practical Deep Learning for Cloud, Mobile, and Edge: Real-World AI & Computer-Vision Projects Using Python, Keras & TensorFlow 1st Edition

The access to curricular consultation Email: yibeltal_chanie@mail.ntut.edu.tw

Expanding teaching and resources ● 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 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
　

Instructor	Yibeltal Chanie Manie　Office Hours
Email	yibeltal_chanie@mail.ntut.edu.tw
Last Updated	2026-06-05 13:57:37
Course Objective	1. 人工智慧簡介及基本概念 2. 各種人工智慧技術介紹 3. 人工智慧工具和框架 4. 人工智慧在光電領域的應用 1. Introduction and basic concepts of artificial intelligence 2. Introduction to various artificial intelligence technologies 3. Artificial intelligence tools and frameworks 4. Application of artificial intelligence in the field of optoelectronics
Course Schedule	1-3 Introduction and basic concepts of artificial intelligence 4-5 Intelligent systems 6-7 Introduction to Machine learning 7-8 Introduction to Deep Learning 9-11 Computer vision 12-13. Generative AI 14 . AI agent and Agentic AI 15. Recent trends of AI 16 Application of artificial intelligence in the field of optoelectronics 17-18 Final Project
Evaluation and grading policy	Homeworks: 40% Labs / Mini Projects: 20 % Class Participation and Attendance: 10% Final project and report: 30%
Materials	All right reserved. Do not reproduce without permission. Foreign-language textbooks:Yes References : 1. Goodfellow, I., Bengio, Y. & Courville, A.: Deep Learning. 2016, MIT. 2. Anirudh Koul, Siddha Ganju, Meher Kasam: Practical Deep Learning for Cloud, Mobile, and Edge: Real-World AI & Computer-Vision Projects Using Python, Keras & TensorFlow 1st Edition
The access to curricular consultation	Email: yibeltal_chanie@mail.ntut.edu.tw
Expanding teaching and resources	● 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	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