本課程以專題實作主軸，相關理論的研讀為輔。實作的主題包括：數據分析、機器學習、機械手臂路徑控制等。課程的進行方式包括：
1. 理論研讀
2. 文獻報告
3. 實作討論

歡迎有興趣的大學部同學選修（建議先與找授課教師討論）。

This course focuses on the implementation of special topics and is supplemented by the study of relevant theories. The topics implemented include: data analysis, machine learning, robotic arm path control, etc. How the course is conducted includes:
1. Theoretical study
2. Documentation report
3. Implementation discussion

Interested undergraduate students are welcome to take the course as an elective (it is recommended to discuss with the instructor first).

本課程著重於探討工程經濟分析在決策與管理上的應用，內容涵蓋資金時間價值、投資替選方案比較、壽命週期成本分析、風險與不確定性決策方法、成本效益分析，以及永續與社會影響評估等議題並與生成式AI應用相結合。課程將結合理論講授與實務案例，透過案例討論與專題研討同時應用生成式AI應用輔助決策與討論，提升學生在成本分析、投資評估、風險管理與永續發展議題上的專業判斷期望學生能在課程結束後，具備獨立進行工程專案經濟評估與決策之專業能力，並能進一步應用於產業實務與學術研究。

This course focuses on the application of engineering economic analysis in decision-making and management. It covers topics such as time value of money, comparison of investment alternatives, life cycle cost analysis, risk and uncertainty decision-making methods, cost-benefit analysis, and sustainability and social impact assessment, and is combined with generative AI applications. The course will combine theoretical teaching and practical cases, and use generative AI applications to assist decision-making and discussion through case discussions and special seminars to enhance students' professional judgment on cost analysis, investment evaluation, risk management and sustainable development issues. It is expected that after the course, students will have the professional ability to independently conduct economic evaluation and decision-making of engineering projects, and can further apply it to industrial practice and academic research.

1. Deep learning with Python, Francois Chollet, 2018, Nanning Publication.
2. Deep Learning (Adaptive Computation and Machine Learning series), Ian Goodfellow, Yoshua Bengio and Aaron Courville, The MIT Press (November 18, 2016).
3. 機器學習（參考書籍 2. 的中譯本）

1. Deep learning with Python, Francois Chollet, 2018, Nanning Publication.
2. Deep Learning (Adaptive Computation and Machine Learning series), Ian Goodfellow, Yoshua Bengio and Aaron Courville, The MIT Press (November 18, 2016).
3. Machine Learning (Chinese translation of reference book 2.)