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Introduction
AI systems are black boxes whose behaviors are difficult to explain. However, to ensure auditability and build trust, we should establish governance frameworks that provide explanations for AI decisions. In this course, we will discuss how to develop such policies for AI governance and build trust in stakeholder relations.
- Graduate Certificate in Artificial Intelligence and AI Ethics
- FlexiMasters
in Artificial Intelligence and AI Ethics
By the end of the course, learners are able to:
1. Know about the development of explainability policies;
2. Be able to identify core stakeholders and their expectations, and the setup of feedback channels, and communication mechanisms and;
2. Know the best practices for complex real-world situations.
This course covers the development of explainability policies, the identification of stakeholders, the management of stakeholder relations with regards to AI explainability, the setup of feedback channels, and communication mechanisms. It will present a number of case studies as illustrations of the core principles to integrate different aspects into complete examples.
For learner who wish to acquire more knowledge in applying ethical AI practices in organizations and, to understand and help societies to solve problems brought about by the impact of AI.
Standard Course Fee: S$1,944
SSG Funding Support | Course fee payable after SSG funding, if eligible under various schemes | ||
Fee BEFORE funding & GST | Fee AFTER funding & 8% GST | ||
Singapore Citizens (SCs) and Permanent Residents (PRs) (Up to 70% funding) | S$1,800.00 | S$583.20 | |
Enhanced Training Support for SMEs (ETSS) | S$223.20 | ||
SCs aged ≥ 40 years old | |||
• NTU/NIE alumni may utilise their $1,600 Alumni Course Credits. Click here for more information.
| COURSE TITLE | ACADEMIC UNIT |
| CET787 Foundations of Computation Thinking and Programming | 1 |
| CET788 AI 1:AI Foundation | 1 |
| CET789 AI 2: Reinforcement Learning | 1 |
| CET790 AI 3: Computational Game Theory | 1 |
| CET791 ML1: Supervised learning: Bayesian decision theory and classifiers | 1 |
| CET792 ML2: Supervised learning: Non-probabilistic classifiers | 1 |
| CET793 ML3: Unsupervised learning | 1 |
| CET794 AI Ethics 1: Foundations of AI Ethics | 1 |
| CET795 AI Ethics 2: AI Ethic Standardization | 1 |
| CET807 Application 2: Introduction to Computer Vision | 1 |
| CET797 Body of Knowledge (BoK) for AI Ethics and Governance | 1 |
| CET798 AI Ethics Governance Framework for Organisations | 1 |
| CET799 Business Liability and Ethics in AI Usage | 1 |
| CET800 AI Ethics 3: Ethics in Data Processing | 1 |
Listed courses are:
- Credit-bearing and stackable to Graduate Certificate in Artificial Intelligence and AI Ethics and FlexiMasters in Artificial Intelligence.
- SSG funded and SkillsFuture Credit approved.
