Course Syllabus

Course Information：

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

Fall Semester
Year 2021 294738 Artificial Intelligence 1 3.0 3 ★ Huang Yu-Hsien
Kuan-Ting Lai
Chien-Hung Lai 4EN4A
4EN4B
4EN3A
4EN3B 58 6 ◎

Year-Semester	Course Number	Course Name	Phase	Credits	Hours	Required/Elective	Instructor	Class	Student NO.	Withdraw	Note
Fall Semester Year 2021	294738	Artificial Intelligence	1	3.0	3	★	Huang Yu-Hsien Kuan-Ting Lai Chien-Hung Lai	4EN4A 4EN4B 4EN3A 4EN3B	58	6	◎

Course Plan：

Instructor Huang Yu-Hsien

Email yshwang@ntut.edu.tw

Last Updated 2021-09-20 14:24:01

Course Objective 本課程主要在介紹最新的AI技術與應用, 並介紹如何使用主流AI Framework: TensorFlow & PyTorch。需有基本程式經驗。

Course Schedule 1. AI是甚麼, 可以吃嗎? 2. 人工智慧發展歷史 3. 機器怎麼學習? 4. 類神經網路與深度學習 (Deep Learning) 5. 捲積神經網路 (CNN) 6. 自然語言處理 (NLP) 7. 遞迴式神經網路 (RNN & LSTM) 8. 空虛、寂寞、覺得冷? 與GPT-3聊天 9. 物件偵測(Object Detection) 10. AI藝術大師 - 生成對抗網路 (GAN) 11. 影像辨識 12. DeepFake & FaceSwap – 移花接木, 以假亂真 13. 深度強化學習 (Deep Reinforcement Learning) - 訓練AI陪你玩遊戲 14. 使用雲端訓練AI

Evaluation and grading policy Kaggle程式作業 (40%) 期中與期末考試 (30%) 期末分組報告 (30%)

Materials All right reserved. Do not reproduce without permission.

Foreign-language textbooks:Yes
陳昇瑋, 溫怡玲, 人工智慧在台灣：產業轉型的契機與挑戰, 天下雜誌, 2019 Francois Chollet, “Deep Learning with Python, ” Manning, 2017 頂級會議(NeurPS, AAAI, CVPR等)的最新的論文

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

The course corresponds to the SDGs

Note In response to the ongoing outbreaks of Covid-19, for the 2021 fall semester, the general regulations will be as follows
(Adjustments may be made based on the epidemic situation, https://oaa.ntut.edu.tw/p/404-1008-98622.php?Lang=zh-tw):
※COVID-19 Alert Level 1 (or below): All courses will be in-person.
※COVID-19 Alert Level 3 (or above): All courses will be offered remotely.
※COVID-19 Alert Level 2: Please note the following specifications for course delivery.
●Course Option:All Remote

●Examinations & Assessments:
All quizzes, exams and homework are online. For final project, students need to submit a YouTube video.
●Supplementary information:

Instructor	Huang Yu-Hsien
Email	yshwang@ntut.edu.tw
Last Updated	2021-09-20 14:24:01
Course Objective	本課程主要在介紹最新的AI技術與應用, 並介紹如何使用主流AI Framework: TensorFlow & PyTorch。需有基本程式經驗。
Course Schedule	1. AI是甚麼, 可以吃嗎? 2. 人工智慧發展歷史 3. 機器怎麼學習? 4. 類神經網路與深度學習 (Deep Learning) 5. 捲積神經網路 (CNN) 6. 自然語言處理 (NLP) 7. 遞迴式神經網路 (RNN & LSTM) 8. 空虛、寂寞、覺得冷? 與GPT-3聊天 9. 物件偵測(Object Detection) 10. AI藝術大師 - 生成對抗網路 (GAN) 11. 影像辨識 12. DeepFake & FaceSwap – 移花接木, 以假亂真 13. 深度強化學習 (Deep Reinforcement Learning) - 訓練AI陪你玩遊戲 14. 使用雲端訓練AI
Evaluation and grading policy	Kaggle程式作業 (40%) 期中與期末考試 (30%) 期末分組報告 (30%)
Materials	All right reserved. Do not reproduce without permission. Foreign-language textbooks:Yes 陳昇瑋, 溫怡玲, 人工智慧在台灣：產業轉型的契機與挑戰, 天下雜誌, 2019 Francois Chollet, “Deep Learning with Python, ” Manning, 2017 頂級會議(NeurPS, AAAI, CVPR等)的最新的論文
The access to curricular consultation	Email: yshwang@ntut.edu.tw
The course corresponds to the SDGs
Note	In response to the ongoing outbreaks of Covid-19, for the 2021 fall semester, the general regulations will be as follows (Adjustments may be made based on the epidemic situation, https://oaa.ntut.edu.tw/p/404-1008-98622.php?Lang=zh-tw): ※COVID-19 Alert Level 1 (or below): All courses will be in-person. ※COVID-19 Alert Level 3 (or above): All courses will be offered remotely. ※COVID-19 Alert Level 2: Please note the following specifications for course delivery. ●Course Option:All Remote ●Examinations & Assessments: All quizzes, exams and homework are online. For final project, students need to submit a YouTube video. ●Supplementary information: