CET946 Responsible Generative AI and Applications

Course Provider

College of Computing and Data Science

Certification

Graduate Certificate

Academic Unit

3

Introduction

With the rapid growth in Generative Artificial Intelligence (GAI) technologies, professionals in every industry need a good grasp of what GAI is and how they can exploit it in a responsible and thoughtful manner. This introductory course helps learners understand GAI technology, its capabilities, limitations and applications in various scenarios. More importantly, it highlights new ethical risks associated with the use of GAI, along with risk mitigation strategies and practical approaches in deploying trusted GAI solutions. Exercises in effective prompt engineering techniques will expose learners to the use of GAI tools to generate relevant text and images that are context-appropriate for their needs and that of their organisations. At the completion of this course, learners will have acquired the understanding and skills to responsibly exploit GAI technologies within their organisation and existing work processes.

This course is part of:

- 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:

  • Describe the basic technology behind Generative AI (GAI) algorithms and how they relate to GAI applications, performance and limitations.
  • Develop a comparative appreciation for the current variety of GAI models and tools, and the skills in making appropriate choices for different use cases.
  • Understand new ethical risks associated with the use of GAI and develop skills to mitigate such risks and implement responsible GAI solutions.
  • Relate best practices in GAI applications to existing GAI governance frameworks, guidelines and evolving international AI regulatory landscape.
  • Develop practical and responsible understanding for how effective prompts can be engineered for generating relevant and appropriate text and images for various use cases relevant to one’s domains of interest. 

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
This course is suitable for learners working in industries that are currently employing or intending to employ Generative AI technologies to improve their work processes or increase their productivity in handling day-to-day knowledge-oriented activities.   

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
SkillsFuture Mid-career Enhanced Subsidy (MCES)
(Up to 90% funding)

  • Standard course fee is inclusive of GST.
  • NTU/NIE alumni may utilise their $1,600 Alumni Course Credits. Click here for more information.

 

Read more about funding

Trainers

Assoc Prof Guosheng Lin

Assoc Prof Guosheng Lin is an Associate Professor at the College of Computing and Data Science (CCDS), NTU. Before moving to Singapore, he was a research fellow at the Australian Centre for Robotic Vision (ACRV), affiliated with The University of Adelaide. His research interests lie in computer vision and deep learning. His recent work focuses on generative learning, including 3D generation and editing, video generation and editing, scene generation, controllable generation, and their applications in scene understanding and 3D vision

Asst Prof Wang Wenya

Asst Prof Wang Wenya is an Assistant Professor at the College of Computing and Data Science (CCDS), NTU. She has received her PhD degree from CCDS, NTU, supervised by Sinno Jialin Pan, and the BSc degree from the School of Mathematical Sciences, NTU. Her main research interest lies in Natural Language Processing with extension to Multimodal Learning, particularly investigating and utilising the mystery of generative AI in knowledge reasoning, model explainability and trustworthiness.

Assoc Prof Goh Wooi Boon

Assoc Prof Goh Wooi Boon is the Associate Dean (Continuing Education - FlexiMasters & Short Courses) at the College of Computing and Data Science (CCDS), NTU. Before joining NTU, he was senior engineer and later engineering section manager at the Mechanization and Automation department of Hewlett Packard Singapore. His industrial engineering expertise is in the area of developing robot-assisted automation systems. Assoc Prof Goh’s interests lie in the interface between humans and computers, especially the design of interactions and issues arising from such interactions, including ethical and societal issues. He is a regular instructor for courses in AI Ethics and Governance (AIEG) and was a reviewer for the Singapore Computer Society’s AIEG Body of Knowledge (BoK) 2.0.

Assoc Prof Chia Liang Tien, Clement

Assoc Prof Chia Liang Tien, Clement is an Associate Professor at the College of Computing and Data Science (CCDS), NTU. He was the Director, Centre for Multimedia and Network Communications 2002-2007 and Head, Division of Computer Communications 2006-2009. Assoc Prof Chia’s research interests can be broadly categorized into two main areas, Internet related research with emphasis on the Semantic Web and Multimedia Understanding for Information Management through media analysis, annotation and adaptation.

Dr Zhiqi Shen

Dr Zhiqi Shen is a Senior Lecturer at the College of Computing and Data Science (CCDS), NTU. His research interests include goal oriented intelligent agents, multi agent systems, agent oriented software engineering and interdisciplinary research in artificial intelligence (AI), machine learning, game design, digital storytelling, e-learning, e-health, crowdsourcing and active ageing. Collaborating with Harvard, MIT and NIE/LSL researchers, “Virtual Singapura” built using his agent based game engine is the first immersive, situated and massive multi-user online role playing (MMORP) virtualised learning environment in Singapore for enabling students to learn through exploring in virtual worlds.

Recommended Add-Ons
Course Code Course Title  
CET946Responsible Generative AI and Applications 3AU
CET949Addressing Issues in Generative AI System Design and Deployment 2AU
CET947AI Ethics and Governance Fundamentals 2AU
CET948Addressing 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.

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