Course Syllabus

Course Information：

Year-Semester Course Number Course Name Phase Credits Hours Required/Elective Instructor Class Student NO. Withdraw Note

Spring Semester
Year 2026 357177 Deep Learning 1 3.0 3 ★ YAO LEEHTER GEE
IEECSG
MSAI 36 0 Jointly offered by Electrical Engineering department.

Year-Semester	Course Number	Course Name	Phase	Credits	Hours	Required/Elective	Instructor	Class	Student NO.	Withdraw	Note
Spring Semester Year 2026	357177	Deep Learning	1	3.0	3	★	YAO LEEHTER	GEE IEECSG MSAI	36	0	Jointly offered by Electrical Engineering department.

Course Plan：

Instructor YAO LEEHTER　Office Hours

Email ltyao@ntut.edu.tw

Last Updated 2025-12-18 12:23:36

Course Objective 1. 類神經網路簡介 2. 淺層類神經網路 3. 深層類神經網路 4. 深層類神經網路之學習與泛化 5. 遞歸類神經網路 6. 長短期記憶類神經網路 7. 卷積類神經網路 8. 深度強化學習 1. Introduction to Neural Networks 2. Shallow Neural Networks 3. Deep Neural Networks 4. Learning and Generalization of Deep Neural Networks 5. Recurrent Neural Networks 6. Long Short-term Memory Neural Networks 7. Convolutional Neural Networks 8. Deep Reinforcement Learning

Course Schedule 1. Introduction to Neural Networks (1 wk) 2. Shallow Neural Networks (2 wks) 3. Deep Neural Networks (2 wks) 4. Learning and Generalization of Deep Neural Networks (3 wks) 5. Recurrent Neural Networks (2 wks) 6. Long Short-term Memory Neural Networks (2 wks) 7. Convolutional Neural Networks ( 3 wks) 8. Deep Reinforcement Learning (3 wks)

Evaluation and grading policy 3 take-home programming exams. 1st Exam: 30% 2nd Exma: 30% Final Exam: 40%

Materials All right reserved. Do not reproduce without permission.

Foreign-language textbooks:Yes
Text Book: Neural Networks and Deep Learning, 2nd Edition, Springer, 2023. Author: Charu C. Aggarwal

The access to curricular consultation 姚立德教授
電機系
綜合科館314

Prof. Leehter Yao
Dept. of Electrical Engineering
314, Complex Building
Email: ltyao@ntut.edu.tw

The course corresponds to the SDGs SDG1：消除貧窮（No Poverty）
SDG4：優質教育（Quality Education）
SDG8：尊嚴就業與經濟發展（Decent Work and Economic Growth）
SDG9：產業創新與基礎設施（Industry, Innovation and Infrastructure）

Does the course incorporate AI ● 鼓勵學生使用生成式AI工具（Encourage students to use generative AI tools）
● 深入探討AI的原理與應用（Explore the principles and applications of AI in depth）

Note
　

Instructor	YAO LEEHTER　Office Hours
Email	ltyao@ntut.edu.tw
Last Updated	2025-12-18 12:23:36
Course Objective	1. 類神經網路簡介 2. 淺層類神經網路 3. 深層類神經網路 4. 深層類神經網路之學習與泛化 5. 遞歸類神經網路 6. 長短期記憶類神經網路 7. 卷積類神經網路 8. 深度強化學習 1. Introduction to Neural Networks 2. Shallow Neural Networks 3. Deep Neural Networks 4. Learning and Generalization of Deep Neural Networks 5. Recurrent Neural Networks 6. Long Short-term Memory Neural Networks 7. Convolutional Neural Networks 8. Deep Reinforcement Learning
Course Schedule	1. Introduction to Neural Networks (1 wk) 2. Shallow Neural Networks (2 wks) 3. Deep Neural Networks (2 wks) 4. Learning and Generalization of Deep Neural Networks (3 wks) 5. Recurrent Neural Networks (2 wks) 6. Long Short-term Memory Neural Networks (2 wks) 7. Convolutional Neural Networks ( 3 wks) 8. Deep Reinforcement Learning (3 wks)
Evaluation and grading policy	3 take-home programming exams. 1st Exam: 30% 2nd Exma: 30% Final Exam: 40%
Materials	All right reserved. Do not reproduce without permission. Foreign-language textbooks:Yes Text Book: Neural Networks and Deep Learning, 2nd Edition, Springer, 2023. Author: Charu C. Aggarwal
The access to curricular consultation	姚立德教授電機系綜合科館314 Prof. Leehter Yao Dept. of Electrical Engineering 314, Complex Building Email: ltyao@ntut.edu.tw
The course corresponds to the SDGs	SDG1：消除貧窮（No Poverty） SDG4：優質教育（Quality Education） SDG8：尊嚴就業與經濟發展（Decent Work and Economic Growth） SDG9：產業創新與基礎設施（Industry, Innovation and Infrastructure）
Does the course incorporate AI	● 鼓勵學生使用生成式AI工具（Encourage students to use generative AI tools） ● 深入探討AI的原理與應用（Explore the principles and applications of AI in depth）
Note