Bachelor of Computing in Artificial Intelligence
The Bachelor of Computing (Honours) in Artificial Intelligence or BComp (AI) programme aims to provide students with a strong foundation in AI knowledge and skills to meet today’s computing needs, and to prepare them for the continuously changing computing landscape of the future. This programme aims to educate the next generation of AI scientists with the following goals and objectives:
- Providing students with a world-class education in AI, broadly covering the three main areas in AI today (Reasoning and Decision Making, Learning, and Perception and Language).
- Preparing students for AI-centric job roles that require deep knowledge of AI.
- Preparing students for the continual and rapid changes in the computing landscape, which requires constant adaptation and self-learning of the newest technologies.
- Producing graduates that understand the responsible use of AI, including issues of ethics, privacy, and AI governance
At the time of graduation, students are expected to demonstrate:
- Strong knowledge of computing foundations and fundamentals, including (a) familiarity with common computing themes and principles, (b) high-level understanding of systems as a whole, (c) understanding of the theoretical underpinnings of computing and their influences in practice.
- Strong knowledge of AI foundations and fundamentals, including broad-based knowledge across the three major areas of AI: Reasoning & Decision Making, Learning, and Perception & Language.
- An ability to design, implement, and evaluate AI systems and models.
- An ability to understand the applications of AI tools and techniques and to analyse the local and global impact of AI on individuals, organisations, and society.
- An understanding of the responsible use of AI, including ethical, legal, privacy-related, security, and social responsibilities.
- An ability to function effectively on teams to accomplish a common goal.
- The ability to continually adapt to the rapid evolution in computing technologies via self-learning and professional development; and the recognition of the need for continuing professional development
Within 3-5 years from graduation, a graduate from the programme is expected to be able to:
- Have a career as AI professional engaging in research and/or development;
- Engage in a supportive or leadership role in a multi-disciplinary, collaborative, team environment;
- Engage in continuous learning of state-of-the-art advances in Artificial Intelligence (including graduate studies);
- Function as an ethical, legal and socially responsible member of the society;
- Apply computing and AI knowledge and skills to contribute positively to the betterment of society.
For a well-rounded education, students pursuing this programme will also acquire knowledge in computing core and mathematics.
Beginning in Academic Year 2025/26, students will be admitted to the following two degree programmes in a common admission pool:
• Bachelor of Computing (Computer Science)
• Bachelor of Computing (Artificial Intelligence)
Please note that the “Computer Science” Common Admissions programme and preferred major can only be selected once in the online application form. Your choice of preferred major within this option will not affect your chance of admission.
When students first matriculate, they will remain in an “indeterminate” state for their first four semesters (or equivalent, if they are transfer students or otherwise begin the programme in a more advanced stage). During this time, they will have access to courses from both programmes. (This is feasible
because courses taken in the first two years are largely common to the two degrees. And the AI courses they may take are most applicable to the AI focus area, if they choose CS.)
At the end of their fourth semester (or equivalent), students will declare either the AI degree programme or the Computer Science degree programme. Note that a student who does not submit their choice or academic plan to AI degree will be placed in the CS programme.
From that point onwards, students can apply to switch between programmes as per current SoC and NUS policy for changing degree programmes.
The Bachelor of Computing (Artificial Intelligence) programme, BComp (AI), requires at least 160 units.
(1) Common Curriculum Requirements1 (40 units)
(2) Unrestricted Electives (40 units)
Students without A-level or H2 Mathematics or equivalent are required to complete the bridging course MA1301/X or equivalent as part of the Unrestricted Electives.
(3) Programme Requirements (80 units)
Computing Foundations
- CS2030S Programming Methodology II
- CS2040S Data Structures and Algorithms
- CS2100 Computer Organisation
- CS2101 Effective Communication for Computing Professionals
- CS3230 Design and Analysis of Algorithms
AI Foundations
- CS2109S Introduction to AI and Machine Learning
- CS3xxx Privacy, Fairness, and Transparency in AI
- CS3263 Foundations of Artificial Intelligence
- CS3264 Foundations of Machine Learning
- CS3230 Design and Analysis of Algorithms
- Perception: one of the following two courses:
• CS4243 Computer Vision and Pattern Recognition
• CS4248 Natural Language Processing
Artificial Intelligence (AI) Breadth & Depth
Students must complete 20 units and subject to the following constraints:
- At least 12 units from the AI Technical Electives list. Courses are:
CS4220 Knowledge Discovery Methods in Bioinformatics
CS4225 Big Data Systems for Data Science
CS4240 Interaction Design for Virtual and Augmented Reality
CS4244 Knowledge Representation and Reasoning
CS4246 AI Planning and Decision Making
CS4261 Algorithmic Mechanism Design
CS4347 Sound and Music Computing
CS4277 3D Computer Vision
CS4278 Intelligent Robots: Algorithms and Systems - At least 12 units at level-4000 or above.
- Industrial Experience Requirement: at least 6 units and at most 12 units of industrial experience courses. Students with a GPA of
4.00 or higher may opt to replace the Industry Experience Requirement with the programme’s dissertation course (i.e., CP4101). - Students who aim for Honours (Highest Distinction) must pass the
programme’s dissertation course (i.e. CP4101). - All courses except Industry Experience must be CS/IFS/IS/CP-coded.
- At most 12 units of CP-coded courses (aside from Industry Experience Requirement).
Industry Experience Requirement
The industry experience courses are as follows:
- A 6-month internship through CP3880 Advanced Technology Attachment Programme (12 units), IS4010 Industry Internship Programme (12 units), or ETP3201L Innovation & Enterprise Internship (12 units);
- A 3-month internships through one of the followings: CP3200 Internship (6 units), CP3202 Internship II (6 units), CP3107 Computing for Social Service Agencies I (6 units), CP3110 Computing for Social Service Agencies II (6 units), ETP3205 Innovation & Enterprise Internship (6 units);
- Other forms of industry experience approved by the Department of Computer Science. Certain NOC internships are not CP-coded, but also can be used to satisfy Breadth-and-Depth requirements as if they were CP-coded.
Students who aim for Honours (Highest Distinction) must pass the CP4101 BComp Dissertation. Students with GPA of 4.00 or higher after completing at least 70% (i.e. 112 units) of the total unit requirement for the degree programme may opt to replace the Industry Experience Requirement by CP4101 B.Comp Dissertation (12 units). Note that the CP4101 project selection process takes place one semester ahead of the semester in which the students commence CP4101. Thus, the students can tentatively select CP4101 projects; but the condition “GPA of 4.00 or higher after completing at least 70% (112 units) of the total unit requirement for the degree programme” must be satisfied before they can commence CP4101 in lieu of Industry Experience Requirement.
Mathematics Foundations
- CS1231S Discrete Structures
- CS2xxx Optimization and Regression
- MA1521 Calculus for Computing
- MA1522 Linear Algebra for Computing
- ST2334 Probability and Statistics 2
Footnotes:
1 Students can refer to: https://www.nus.edu.sg/registrar/academic-information-policies/undergraduate-students/general-education/for-students-admitted-from-AY2021-22 for the University Level Requirements (ULR). CS1101S will satisfy the Digital Literacy pillar.
2 If a student has already taken ST2131/MA2116/MA2216 that precludes ST2334, he/she will have to take ST2132 to fulfil the BComp(AI) degree requirements.
Students who attended NOC programme may:
- count ETP3202L Innovation & Enterprise Case Study and Analysis towards Unrestricted Electives.
- count ETP3203L Innovation & Enterprise Internship Practicum (8 units) towards unrestricted elective course (4 units).
- count ETP3206L Innovation & Enterprise Internship (12 out of 16 units) towards Industrial Experience Requirement.
| Courses | Units | Subtotals |
|---|---|---|
| COMMON CURRICULUM REQUIREMENTS 1 | 40 | |
| University Level Requirements: 6 University Pillars | 24 | |
| Digital Literacy — CS1101S Programming Methodology | 4 | |
| Cultures and Connections — GEC% | 4 | |
| Data Literacy — Either GEA1000, BT1101, ST1131 or DSA1101 | 4 | |
| Singapore Studies — GES% | 4 | |
| Communities and Engagement — GEN% | 4 | |
| Computing Ethics | 4 | |
| IS1108 Digital and AI Ethics | 4 | |
Interdisciplinary & Cross-Disciplinary Education Comprises of Interdisciplinary (ID) Courses and Cross-disciplinary (CD) Courses Students are required to take 12 units from the above courses with at least two ID courses and no more than one CD course to satisfy the 12 units required in this group. | 12 | |
| PROGRAMME REQUIREMENTS | 80 | |
| Computer Science Foundations | 20 | |
| CS2030S Programming Methodology II | 4 | |
| CS2040S Data Structures and Algorithms | 4 | |
| CS2100 Computer Organisation | 4 | |
| CS2101 Effective Communication for Computing Professionals | 4 | |
| CS3230 Design and Analysis of Algorithms | 4 | |
| Artificial Intelligence (AI) Foundations | 20 | |
| CS2109S Introduction to AI and Machine Learning | 4 | |
| CS3xxx Privacy, Fairness, and Transparency in AI | 4 | |
| CS3263 Foundations of Artificial Intelligence | 4 | |
| CS3264 Foundations of Machine Learning | 4 | |
| Perception: Read one of the following two courses • CS4243 Computer Vision and Pattern Recognition • CS4248 Natural Language Processing | 4 | |
| Artificial Intelligence (AI) Breadth and Depth | 20 | |
| Students must complete 20 units subject to the following constraints: • At least 12 units from the AI Technical Electives list. • At least 12 units at level-4000 or above. • Industrial Experience: at least 6 units and at most 12 units of industrial experience courses. Students with a GPA of 4.00 or higher may opt to replace the Industry Experience with the programme’s dissertation course (i.e., CP4101). • Students who aim for Honours (Highest Distinction) must pass the programme’s dissertation course (i.e. CP4101). • All courses except Industry Experience must be CS/IFS/IS/CP coded. • At most 12 units of CP-coded courses (aside from Industry Experience. | ||
AI Technical Electives List The currently available courses are:
| Each course is 4 units | |
| Mathematics Foundations | 20 | |
| CS1231S Discrete Structures | 4 | |
| CS2xxx Optimization and Regression | 4 | |
| MA1521 Calculus for Computing | 4 | |
| MA1522 Linear Algebra for Computing | 4 | |
| ST2334 Probability and Statistics2 | 4 | |
| UNRESTRICTED ELECTIVES 3 | 40 | |
| Grand Total | 160 |
Footnotes:
1 Students can refer to: https://www.nus.edu.sg/registrar/academic-information-policies/undergraduate-students/general-education/for-students-admitted-from-AY2021-22 for the University Level Requirements (ULR). CS1101S will satisfy the Digital Literacy pillar.
2 If a student has already taken ST2131/MA2116/MA2216 that precludes ST2334, he/she will have to take ST2132 to fulfil the degree requirements.
3 Students without A-level or H2 Mathematics or equivalent are required to complete the bridging course MA1301/X or equivalent as part of the Unrestricted Electives.
The number of students enrolled in the School of Computing can be found here.
