Courses

This interdisciplinary course examines the evolving relationship between humans and machines in the age of advanced technology and AI. Drawing from phenomena in philosophy, psychology, behavioural science, sociology, and biology, it explores theories of human dignity, including consciousness, empathy, creativity, and progress. Students will analyse how these ideas apply to real-world examples in case studies

With Artificial Intelligence (AI) increasingly shaping the world, understanding computational thinking and reasoning is becoming more essential. This course aims to empower students with the ability to model thought processes using computational thinking and reasoning methods. By combining theoretical discussions with hands-on problem-solving exercises, the course encourages critical reflection on how machines simulate human reasoning.

This course introduces students to the fundamental computing concepts and programming skills to enhance their problem-solving ability. Ultimately, students will learn how to design solutions that incorporate basic Artificial Intelligence (AI) and implement these solutions using an imperative programming language. This course is equivalent to CS1010X Programming Methodology, as it offers a gradual but critical

This interdisciplinary course explores Artificial Intelligence (AI) innovations across global industries, with a focused examination of Singapore’s unique strategic trade-offs in AI adoption. Students will critically assess how AI impacts economic growth, labour markets, data governance, and societal well-being, identifying challenges and opportunities specific to Singapore’s innovation ecosystem. The course integrates key academic concepts from

This course examines Machine Learning (ML) and Artificial Intelligence (AI) within the context of natural and cultural learning processes. Beginning with information processing in primitive organisms, it traces the evolution of learning through neural systems, human societies, and modern computers. As foundational material, the course covers classic theories of learning and knowledge acquisition from cognitive

This interdisciplinary course explores Artificial Intelligence (AI) innovations across global industries, with a focused examination of Singapore’s unique strategic trade-offs in AI adoption. Students will critically assess how AI impacts economic growth, labour markets, data governance, and societal well-being, identifying challenges and opportunities specific to Singapore’s innovation ecosystem. The course integrates key academic concepts from

This course examines the risks and the role of governance in the use of AI, with a particular focus on Singapore’s approach to balancing technological advancement with ethical and regulatory concerns. Students will explore key AI safety challenges, including lack of transparency, bias, privacy vulnerabilities, cybersecurity threats, autonomous weaponisation, goal misalignment, and overreliance. Through inter-disciplinary

With Artificial Intelligence (AI) increasingly shaping the world, understanding computational thinking and reasoning is becoming more essential. This course aims to empower students with the ability to model thought processes using computational thinking and reasoning methods. By combining theoretical discussions with hands-on problem-solving exercises, the course encourages critical reflection on how machines simulate human reasoning.

This course introduces students to the fundamental computing concepts and programming skills to enhance their problem-solving ability. Ultimately, students will learn how to design solutions that incorporate basic Artificial Intelligence (AI) and implement these solutions using an imperative programming language. This course is equivalent to CS1010X Programming Methodology, as it offers a gradual but critical

This course examines Machine Learning (ML) and Artificial Intelligence (AI) within the context of natural and cultural learning processes. Beginning with information processing in primitive organisms, it traces the evolution of learning through neural systems, human societies, and modern computers. As foundational material, the course covers classic theories of learning and knowledge acquisition from cognitive