課程目的：
本課程為「智慧應用微學程」的成果展現課程 (Capstone Course)。旨在讓學生將微學程中所學的跨域知識（如人工智慧、大數據、物聯網等），整合並實務應用於解決真實世界的創新問題，學生依據所修之微學程製作專題並於期末發表專題成果。本課程目的在於幫助學生瞭解AI 與產業的關聯性，並強化學生將所學知識應用於實務的能力。透過產業實務經驗導入教學，縮短理論與實務應用的落差。透過此課程，旨在培育具備「智慧創新跨域潛力」的應用型人才。
授課教師與分組：
本課程由資工系、資管系、教育研究所、統計系及通識中心教師共同開課。依據教師研究專長分組，進行產業AI 應用專題研究，學生依興趣選擇專題組別，透過分析不同產業類型的資料，深入探討 AI 在該領域的應用，並透過實際產業數據佐證研究成果，培養學生理論與產業實務能力。

上課時間與方式：
本課程上課時程涵蓋暑假及115學年度第一學期。暑假期間規劃共同課程，邀請業界教師到校授課，由具跨領域背景且熟稔軟體開發實務之業界專家進行分享，並安排企業參訪，總時數約18小時。
115學年度第一學期開學後，由各組教師帶領並協助學生分組完成專題研究與成果發表，並由各組師生約定討論時間，依進度推動專題執行，總時數約36小時。

成果發表：
學期末各組須繳交10頁以內之小論文，並進行專題成果發表。本課程將邀請校內相關專長教師進行評分，遴選優秀作品投稿發表及參與全國競賽。
評量方式包含企業參訪心得、業界講師演講、小組專題參與貢獻及小組期末成果等。

Course purpose:
This course is the Capstone Course of the "Smart Application Micro-Course". The aim is to allow students to integrate and practically apply the cross-domain knowledge (such as artificial intelligence, big data, Internet of Things, etc.) learned in the micro-learning program to solve real-world innovation problems. Students will create special topics based on the micro-learning courses they have taken and publish the results at the end of the semester. The purpose of this course is to help students understand the correlation between AI and industry, and to strengthen students' ability to apply the knowledge they have learned into practice. Introduce teaching through industrial practical experience to shorten the gap between theory and practical application. Through this course, we aim to cultivate applied talents with "cross-domain potential for smart innovation."
Teachers and groups:
This course is jointly taught by teachers from the Department of Finance and Economics, the Department of Asset Management, the Institute of Education, the Department of Statistics and the General Studies Center. Teachers are grouped into groups according to their research expertise to carry out special research on industrial AI applications. Students select thematic groups according to their interests and analyze the data of different industrial types to deeply explore the application of AI in this field. The research results are supported by actual industrial data to cultivate students' theoretical and industrial practical abilities.

Class time and method:
The class schedule of this course covers the summer vacation and the first semester of the 2015 academic year. During the summer vacation, common courses are planned and industry teachers are invited to the school to teach. Industry experts with cross-domain backgrounds and familiarity with software development practices will share their knowledge and arrange company visits, with a total duration of about 18 hours.
After the start of the first semester of the 2015 academic year, teachers from each group will lead and assist students to complete special research and publish results in groups. Teachers and students in each group will agree on a discussion time and promote the implementation of the project according to the progress, with a total of about 36 hours.

Results published:
At the end of the semester, each group must submit a short paper within 10 pages and publish the results on a special topic. This course will invite teachers with relevant expertise within the school to conduct grading, select outstanding works for publication, and participate in national competitions.
The evaluation methods include company visit experiences, industry lecturers’ speeches, group topic participation contributions, and group final results, etc.

自編講義

Self-compiled handouts