114年第1學期-0571 Generative AI Presentation and Communication 課程資訊

評分方式

評分項目	配分比例	說明
In-Class Participation, Study Attitude	15	In-Class Participation, Study Attitude (discussion and project critiques)
Assignments	25	Take home assignments or online quizzes
Mid term Exam	20	Mid term Exam
Final Project & Presentation	40	Final Project & Presentation

教育目標

• Develop a foundational understanding of generative artificial intelligence, with a focus on large language models (LLMs) and their underlying principles. • Explore the landscape of AI-enhanced presentation tools and their applications in academic and professional settings. • Apply generative AI technologies to support research activities, including content development, synthesis of information, and idea generation. • Examine contemporary applications of AI in domains such as sustainability, green energy, environmental science, and chemistry, with attention to emerging trends and future directions. • Learn to design and deliver compelling presentations by integrating GenAI-generated text, visuals, audio, and video content. • Enhance clarity, coherence, and persuasiveness in written and spoken communication through the strategic use of AI tools. • Critically evaluate the ethical considerations surrounding the use of generative AI in communication, including issues of authorship, transparency, and bias. • Analyze real-world case studies to understand practical implementations and best practices in GenAI-supported communication. • Investigate future developments in generative AI and their potential impact on communication practices across disciplines.

基本資料

選修課，學分數：2-0
上課時間：三/3,4[M007]
修課班級：化學系1-4
修課年級：1年級以上
選課備註：英語授課，永續學程2836課程併班。上課地點：第二校區電腦教室。

參考書目

1.S. Russell and P. Norvig, Artificial Intelligence: A Modern Approach, Pearson Series, 4th Eds., 2021.
2.Bernard Marr, Generative AI in Practice: 100+ Amazing Ways Generative Artificial Intelligence is Changing Business and Society,1st Edition, Wiley, 2024.
3.Valentina Alto, Practical Generative AI with ChatGPT, 2nd ed. Edition, Packet Publishing, 2025.
4.Melanie Mitchell, Artificial Intelligence: A Guide for Thinking Humans, Picador, 2019.
5.David Foster, Generative Deep Learning: Teaching Machines to Paint, Write, Compose, and Play, O’Reilly Media, 2019.
6.C.C. Aggarwal, Neural Networks and Deep Learning, Springer, 2023.