Introduction
This course teaches learners to implement Generative AI (GAI) responsibly in organisations. It addresses key issues throughout the design, development, deployment, and post-deployment stages. Learners will explore practical considerations, from deciding to adopt a GAI solution to designing a suitable system and establishing governance. The aim is to equip AI practitioners with the knowledge to avoid common pitfalls when integrating GAI in their organisations. Additionally, the course covers security and safety aspects like jailbreaking and prompt injection, highlighting unique vulnerabilities in GAI systems and offering strategies for resilient and responsible deployment.
- Graduate Certificate in Responsible Artificial Intelligence Practices
- Certificate in Responsible Generative AI Governance
Objectives
At the end of the course, learners will be able to:
- Apply various practical technical and operational considerations to the design and deployment of a generative AI solution for a given use case.
- Design sound governance and risk management strategies to ensure that GAI systems are implemented responsibly and securely within the enterprise.
- Describe the different types of security and safety challenges posed by GAI systems and be able to propose appropriate mitigation strategies, techniques and processes to manage such security and safety risks, both during and post deployment.
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$4,360
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$4,000 | S$1,308.00 | |
Enhanced Training Support for SMEs (ETSS) | S$508.00 | ||
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
Ong Chin Ann
Dr Zhang Jiehuang
Dr Zhang Jiehuang is a lecturer at the College of Computing and Data Science (CCDS), NTU. He is a data scientist with years of experience in the technology sector. He currently teaches data science and AI in CCDS, focusing on developing responsible AI systems in real world settings. During his PhD, Dr Zhang developed a set of methodologies to guide and evaluate responsible AI systems for software and AI development.
He was previously in the data chapter team of the Development Bank of Singapore (DBS) bank, where he led high impact projects to build and deploy AI models to predict incidents and discover insights into customer activity. Dr Zhang was also involved in the scoping and proof of concept of Generative AI use cases to apply to the banking and finance sector.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.
