All four programmes share a common foundation in computational thinking, mathematical reasoning, and professional development.
They diverge in emphasis, depth, and the kinds of problems students are trained to tackle.
Bachelor of Computing
Artificial Intelligence & Society (AISC)
Human-Centric AI with Ethical Depth
· Strong technical training in AI, grounded in responsible and human-centred design
· Focus on societal implications, governance, and ethical deployment of AI systems
· Interdisciplinary exposure across computing, business, and humanities
· Team-based projects addressing risks across the AI lifecycle
AISC develops graduates who are technically capable and socially accountable in how AI systems are built and deployed.
Bachelor of Engineering
Computer Engineering
(CE)
Hardware–Software Systems Integration
· Integrated training across computer science and engineering principles
· Emphasis on hardware–software co-design and system-level optimisation
· Applications in embedded systems, robotics, cyber-physical systems, and high-performance computing
· Accreditation pathway aligned with professional engineering standards
CE develops engineers who design and optimise computing systems at the intersection of hardware and software.
Bachelor of Computing
Computer Science
(CSC)
Foundations for Building Real-World Systems
· Strong grounding in core computer science theory and systems
· Repeated hands-on development through embedded project cycles
· End-to-end software engineering capability — from algorithm design to deployment
· Mandatory 20-week professional internship
CSC focuses on producing software engineers who can design, build, and deploy production systems at scale.
Bachelor of Science
Data Science & Artificial Intelligence (DSAI)
Mathematical Rigor for Intelligent Systems
· Deep integration of mathematics, statistics, and computer science
· Emphasis on probability, optimisation, and machine learning from first principles
· Full data science pipeline training — from data preparation to deployment
· Joint expertise from CCDS and SPMS
DSAI develops graduates who understand why algorithms work — not just how to apply them.
Comparing the Programmes
A structural view of breadth and depth across computing.
The four undergraduate programmes differ primarily in their intellectual emphasis – particularly in how they balance breadth across computing with depth in specific domains.
Foundations Across Computing
Bachelor of Computing in Computer Science (CSC) and Bachelor of Engineering in Computer Engineering (CE)
Both programmes provide a broad and comprehensive foundation in computing. They cover core areas such as algorithms, systems, software engineering, and mathematical reasoning.
They differ in orientation:
· CSC has a stronger software-centric focus, emphasising software systems, abstraction, and theoretical foundations.
· CE places greater emphasis on hardware–software co-design, embedded systems, and system-level optimisation.
Focused Depth in AI and Data
Bachelor of Science in Data Science & Artificial Intelligence (DSAI) and Bachelor of Computing in Artificial Intelligence & Society (AISC)
These programmes focus more deeply on specific domains within computing, particularly AI, machine learning, and data-related areas. Sufficient computing foundations are covered to support this depth.
They differ in emphasis:
- DSAI is mathematically intensive, with strong grounding in statistics, probability, optimisation, and machine learning theory.
- AISC combines technical AI training with additional emphasis on ethics, governance, and human-centric design, supported by interdisciplinary collaboration.
Each programme reflects a different intellectual emphasis within computing.
