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113學年度課程規劃
亞洲大學 人工智慧博士學位學程課程規劃表 113學年度入學適用
Doctoral Program Curriculum Plan for Ph.D. Program in Artificial Intelligence, Asia University
(Applicable for Fall 2024 Enrollees)
畢業總學分: 27 學分 校課程委員會通過次別：1124
Credits of Graduation：27 Approved in the 1124 University Curriculum Committee meeting
|
類別 |
科目名稱 |
英文名稱 |
修課 |
修課 |
學分數 |
每週上課時數 |
備 註 |
||
| 講授 Lecture |
實作(驗) Practice (laboratory) |
實習 Intern |
|||||||
| 校定必修6學分 (6) University Required Credits |
博士論文 | Doctoral Dissertation | 二 2nd |
上 1s |
3 | 0 | 0 | 0 | |
| 博士論文 | Doctoral Dissertation |
二 2n |
下 2nd |
3 | 0 | 0 | 0 | ||
| 必修6學分 (6) Required Credits |
專題講座 (一) | SeminarⅠ |
一 1st |
上 1st |
1 | 1 | 0 | 0 | |
| 專題講座 (二) | Seminar Ⅱ |
一 1st |
下 2nd |
1 | 1 | 0 | 0 | ||
| 專題講座 (三) | Seminar Ⅲ |
二 2nd |
上 1st |
1 | 1 | 0 | 0 | ||
| 人工智慧 | Artificial Intelligence |
一 1st |
上 1st |
3 | 3 | 0 | 0 | ||
| 選修15學分 (15) Elective Credits |
資料科學 | Data Science |
一 1st |
上 1st |
3 | 3 | 0 | 0 | |
| 機器學習 | Machine Learning |
一 1st |
上 1st |
3 | 3 | 0 | 0 | ||
| 演算法 | Algorithms |
一 1st |
下 2nd |
3 | 3 | 0 | 0 | ||
| 深度學習 | Deep Learning |
一 1st |
下 2nd |
3 | 3 | 0 | 0 | ||
| 資料探勘 | Data Mining |
一 1st |
上 1st |
3 | 3 | 0 | 0 | ||
| 大數據資料處理 | Big Data Management |
二 2nd |
上 1st |
3 | 3 | 0 | 0 | ||
| 語音辨識 | Speech Recognition |
二 2nd |
下 2nd |
3 | 3 | 0 | 0 | ||
| 電腦視覺 | Computer Vision |
二 2nd |
上 1st |
3 | 3 | 0 | 0 | ||
| 影像處理 | Image Processing |
一 1st |
下 2nd |
3 | 3 | 0 | 0 | ||
| 自然語言處理 | Natural Language Processing |
二 2nd |
下 2nd |
3 | 3 | 0 | 0 | ||
| 模糊理論 | Fuzzy Theory |
一 1st |
上 1st |
3 | 3 | 0 | 0 | ||
| 精準醫療 | Precision Medicine |
二 2nd |
上 1st |
3 | 3 | 0 | 0 | ||
| 區塊鏈技術與應用 | Blockchain Technology and Its Application |
二 2nd |
下 2nd |
3 | 3 | 0 | 0 | ||
| 智慧物聯網(AIoT) | Artificial Intelligence & Internet of Things (AIoT) |
一 1st |
下 2nd |
3 | 3 | 0 | 0 | ||
| 雲端運算實務 | Cloud Computing Practices |
一 1st |
上 1st |
3 | 3 | 0 | 0 | ||
| 機器人計算學 | Robotic Computing |
一 1st |
上 1st |
3 | 3 | 0 | 0 | ||
1. 畢業學分數最低為 27 學分，含校定必修 6 學分（博士論文），學程必修 6 學分，學程選修 15學分。其中，學程選修課程經指導教授與學程主任同意後，得選修本校相關系所開授之博士相關課程，最多 9 學分。
The minimum credits required for graduation is 27, including 6 credits of university-required courses (dissertation), 6 credits of program core courses, and 15 credits of program electives. Among the elective courses, students may select up to 9 credits from other doctoral courses offered by the university, subject to approval from their advisor and the program director.
2. 學生除須修畢規定之畢業學分外，須通過資格考、畢業資格審查、博士學位考試(含博士論文計畫書及博士論文審查)，始可畢業。學生應於四年內通過二科資格考試，選考科目包含「資料科學」、「演算法」、「機器學習」、「人工智慧」。
In addition to completing the required credits for graduation, students must pass the qualifying examination, the graduation qualification review, and the doctoral degree examination (including the dissertation proposal and dissertation review) to graduate. Students must pass qualifying examinations in at least two subjects within four years. The available subjects include "Data Science," "Algorithms," "Machine Learning," and "Artificial Intelligence."
3. 依「亞洲大學學生學術研究倫理教育課程實施要點」109學年度（含）起入學之各系、所、學位學程的碩士班、碩士在職專班及博士班學制，【學生需透過「臺灣學術倫理教育資源中心」線上平台修習指定課程6小時，並於課程總測驗成績達及格標準，始得申請學位考試。】
All master's and doctoral students must complete 6 hours of designated courses through the online platform of the Center for Taiwan Academic Research Ethics Education and achieve a passing grade on the final exam before they can apply for their degree examination.
4. 學程必修學分之抵免，或以上未盡事宜，得經由學程主任召開會議討論後裁決之。
Credit exemptions for core courses within the program, or other matters not mentioned above, may be decided after discussion at a meeting convened by the program director.
