Type of Credit: Partially Required
Credit(s)
Number of Students
In recent years, artificial intelligence (AI) has been classified as one of the most important transformational technologies to improve social life and address organizations' problems. AI's practical application is profoundly versatile and has the unique ability to offer convenience and efficiency. However, the proliferated application of AI has also raised some skepticism since the impacts of AI involve not only institutions that maintain societal operations, but also the way in which we confront social problems.
能力項目說明
This course will introduce diverse aspects concerning AI, and students will learn about AI’s advantages and limitations as well as strategies to drive AI.
Course Prerequisites and Policies:
You should read all the required materials prior to attending the classes.
| 教學週次Course Week | 彈性補充教學週次Flexible Supplemental Instruction Week | 彈性補充教學類別Flexible Supplemental Instruction Type |
|---|---|---|
Week 1 (2/21): Introduction of the Course
Week 2 (2/28): 228 Peace Memorial Day
Week 3 (3/7): AI’s Development
Required Reading:
Agrawal, A., Gans, J. and Goldfarb, A., 2018. Prediction Machines: The Simple Economics of Artificial Intelligence. Harvard Business Press. Chapter 1 & 2
Week 4 (3/14): Data and Basic Deep Learning
Required Reading:
Krohn, J., Beyleveld, G. & Bassens, A,. 2019. Deep Learning Illustrated: A Visual, Interactive Guide to Artificial Intelligence. Addison-Wesley Professional; 1st edition. Chapter 5-7
Week 5 (3/21): Convolution Neural Network
Required Reading:
Krohn, J., Beyleveld, G. & Bassens, A,. 2019. Deep Learning Illustrated: A Visual, Interactive Guide to Artificial Intelligence. Addison-Wesley Professional; 1st edition. Chapter 10
Week 6 (3/28): Recurrent Neural Network (RNN)
Required Reading:
Leifer, L., Lewrick, M., & Link P. (2018). The Design Thinking Playbook. New York: Wiley. Chapter 11 : NETWORKS DESIGNED FOR SEQUENTIAL DATA
Week 7 (4/4): Spring Break
Week 8 (4/11): Round Table 1
Week 9 (4/18): RNN for Natural Language Processing
Required Reading:
Leifer, L., Lewrick, M., & Link P. (2018). The Design Thinking Playbook. New York: Wiley. Chapter 11-13
Week 10 (4/25): Transformer and BERT: The Game-changing NLP Models
Week 11 (5/2): Introduction AIGC and ChatGPT’s Application
Week 12 (5/9): Round Table 2: AI Project Proposal
Week 13 (5/16): Advanced AIGC and ChatGPT’s Application I
Week 15(5/30): Round Table 3
Week 16 (6/7): Final Presentation
Week 17 (6/14): Final Paper Workshop
Week 18 (6/21): Final Paper Writing
Generative AI Utility Policy
Conditional Acceptance:
Agrawal, A., Gans, J. and Goldfarb, A., 2018. Prediction Machines: The Simple Economics of Artificial Intelligence. Harvard Business Press.
Krohn, J., Beyleveld, G. & Bassens, A,. 2019. Deep Learning Illustrated: A Visual, Interactive Guide to Artificial Intelligence. Addison-Wesley Professional; 1st edition
Leifer, L., Lewrick, M., & Link P. (2018). The Design Thinking Playbook. New York: Wiley.