◈ 學分學程介紹 Program Overview
為配合協助政府的各領域的產業創新計畫，驅動產業發展量能，並因應人工智慧及資訊安全迅速發展之趨勢，本學分學程屬於人工智慧技術學分學程，透過循序漸進的修課規劃，讓學生在資安相關領域有所理解，未來應用技術在各產業的創新上。
◈ 適合學生 Who should take this program
本學分學程適合電資領域學生修習，或是已經完成「人工智慧探索應用學分學程」的學生。
This program is suitable for students in electrical engineering, computer science, and related disciplines, or for those who have already completed the Applied AI Exploration Program.
◈ 修課規定 Program Requirements
- 本聯盟各學分學程總修習學分為 15 學分。
- 本聯盟各學分學程間可互相抵免學分上限為 6 學分。
- 若需取得本聯盟頒發學程學分證明，除了修滿15學分外，其中至少 8 學分以上需為聯盟認定課程（主導課程、鏡像課程或衛星課程）。
- Each TAICA program requires completion of 15 credits.
- Up to 6 credits may be cross-counted between different TAICA programs.
- To obtain the program credit certification issued by the TAICA Alliance, students must complete a total of 15 credits, including at least 8 credits from TAICA-recognized courses, which may include leading courses, mirror (core) courses, or satellite courses.
◈ 修課注意事項 Course Enrollment Note
學生修習課程的時候，若因為主修課程安排限制，不一定要根據課程規劃中的修課順序建議，舉例來說：在本學分學程若跳過『資訊安全導論』來修習『深度學習』，也是可行的，但是可能對課程理解、和課程表現上就會較為遜色。又，雖然人工智慧倫理的課程難度可能是最簡單的，但是若沒有按照修課建議順序，有可能會在少部分課程內容上會有囫圇吞棗之憾。因此若選課上有疑惑，請和開課老師討論、或在學期初提前理解課程內容進度，再審慎規劃。
Students are not strictly required to follow the recommended sequence if constrained by their major’s scheduling. For example, taking Deep Learning without first completing Introduction to Information Security is possible, but may result in lower comprehension and performance. Similarly, while AI Ethics is generally considered one of the easier courses, skipping foundational courses may lead to gaps in understanding some parts of the curriculum.
If you have questions about course selection and planning, please consult the course instructor, or review course content early in the semester to make a well-informed decision.