Introduction
The proper governance of Artificial Intelligence (AI) and autonomous decision-making systems involves addressing many ethical issues such as data privacy, biasness, fairness and explainability. In this introductory course, learners will understand what each of these issues involve and how they relate to the notion of good AI governance. Interesting real-world case studies will be presented to help contextualise these ethical challenges in different industries. The course will also discuss techniques that can help address issues of data privacy, biasness and explainability, both at the stage when data is being prepared and during the process of AI model training. On completion of this course, learners will have acquired the useful AI governance skills and know-how that will help them design, evaluate and deploy Responsible AI solutions in their work place.
- Graduate Certificate in Responsible Artificial Intelligence Practices
- Certificate in AI Ethics and Governance
Register on this page if you intend to take this course only. If you intend to take the Certificate in AI Ethics and Governance, please register here.
Course Availability
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Date(s): 19 Apr 2025 to 24 May 2025
Time: Synchronous E-Learning every Saturday (9.30 – 11.30 a.m.) Live E-consultation every Wednesday (7.30 – 9.00 p.m.)
Venue: Synchronous and Asynchronous E-Learning
Registration is closed.
Objectives
At the end of the course, learners will be able to:
- Describe ethical issues in data processing such as informed consent, data privacy, reproducibility, data biasness and techniques to achieve K-anonymity and combating bias in the data.
- Describe the different notions of fairness and develop a smart task allocation algorithm that balances efficiency and fairness considerations.
- Describe ethical risks in the training of data for AI systems and the use of techniques like federated learning to enhance data privacy during training.
- Describe the different levels of machine learning algorithms and be able to relate them to the governance issue of AI explainability and techniques for interpretable explanations in autonomous decision-making systems.
- Describe Singapore’s AI governance practices and guidelines in various industry sectors like finance and healthcare.
Assessment
To meet the requirement of SkillsFuture Singapore, assessment(s) will be conducted during every course. The assessment(s) include:
- Quizzes
- Assignment
Who should attend
Fees and Funding
Standard Course Fee: S$6,540
SSG Funding Support | Course fee | Course fee payable after SSG funding, if eligible under various schemes | |
BEFORE funding & GST | AFTER funding & 9% GST | ||
Singapore Citizens (SCs) and Permanent Residents (PRs) (Up to 70% funding) | S$6,000 | S$1,962.00 | |
Enhanced Training Support for SMEs (ETSS) | S$762.00 | ||
SCs aged ≥ 40 years old | |||
- Standard course fee is inclusive of GST.
- NTU/NIE alumni may utilise their $1,600 Alumni Course Credits. Click here for more information.
Trainers
Prof Cong Gao
Assoc Prof Yu Han
Dr Weng Jianshu
Dr Kwong Yuk Wah
Recommended Add-Ons
| Course Code | Course Title | |
|---|---|---|
| CET946 | Responsible Generative AI and Applications | 3AU |
| CET949 | Addressing Issues in Generative AI System Design and Deployment | 2AU |
| CET947 | AI Ethics and Governance Fundamentals | 2AU |
| CET948 | Addressing Issues in AI Ethics and Governance | 3AU |
Listed courses are:
- Credit-bearing and stackable to Graduate Certificate in Responsible Artificial Intelligence Practices. Graduate Certificate will be awarded to learners upon successful completion of at least 6 AUs, with a minimum Grade Point of 2.5 (which is equivalent to a letter grade of C+) achieved for each course.
- CET946 and CET949 are part of the Certificate in Responsible Generative AI Governance
- CET947 and CET948 are part of the Certificate in AI Ethics and Governance
- SSG funded and SkillsFuture Credit approved.
