School of Computing
Coursework Programmes
Overview
The Master of Computing programme (MComp) with specialisations offered by the School of Computing, is a comprehensive and challenging graduate programme with area specialisations. It encompasses latest research findings, both applied and fundamental. The programme also provides advanced and in-depth knowledge of IT to prepare the students for challenges in IT career.
The School also offers a General Track for the Master of Computing programme. This track programme is designed primarily for students with non-computing undergraduate degrees and aims to provide a systematic pathway for graduates who wish to embark on an accelerated conversion to the computing field. In addition to helping build a strong foundation in computing fundamentals, this programme offers elective modules that cover deep computing expertise to help prepare MComp graduates for future career challenges in the Infocomm sector.
Artificial Intelligence (AI) is increasingly recognised as an important source of economic growth nationally and globally, leading to growing demand for AI-focused education and training for careers in industry as well as research. The Master of Computing in Artificial Intelligence (MComp in AI) programme aims to meet this need by providing systematic breadth-and-depth training in advanced principles, algorithms, and applications in AI. It focuses on the computational fundamentals and principles that underlie intelligent systems (knowledge representations, machine learning, and reasoning), as well as state-of-the-art technologies in major AI application domains (vision, speech & language processing, data analytics, and robotics).
The Master of Science in Business Analytics (MSBA) is a graduate degree programme offered by the NUS Business Analytics Centre (BAC). It is designed and taught by award-winning academics from NUS Business School and NUS Computing. It aims to equip professionals with business analytics skills that will meet the growing demands of companies looking to improve their operations through data analytics.
Financial technology (abbreviated as FinTech) refers to a broad spectrum of the technologies and innovations that are being used to improve and automate the delivery of financial services. The FinTech industry has grown explosively in the last decade, with the advances being made in cloud computing, data analytics and artificial intelligence (AI). To meet surging demand for high quality FinTech talent in Singapore and globally, this graduate programme in FinTech is designed to help students build a strong foundation in computing and finance, and features a range of elective modules organised along three tracks: Computing Technologies, Financial Data Analytics and Intelligence, and Digital Financial Transactions and Risk Management.
The Master of Science in Digital Financial Technology (MSc DFinTech) is designed primarily to help prepare graduates for challenging but rewarding careers as AI software developers, data scientists, FinTech security specialists, financial quantitative analysts and other similar professions in financial institutions or FinTech firms.
In addition, to help build a strong foundation in computing and finance, this programme offers elective modules that cover deep computing and finance expertise to help prepare graduates for future career challenges in the FinTech sector.
Degrees Offered
The School of Computing offers the following degree programmes:
Master of Computing (MComp)
- Specialisations
- Computer Science
- Infocomm Security
- Information Systems
- General Track
Master of Computing in Artificial Intelligence
Master of Business Analytics (jointly with the NUS School of Business)
Master of Science - Digital Financial Technology (MSc DFinTech)
Curriculum Structure & Degree Requirements
Structure of MComp (Specialisations) Programme
Candidates admitted to the MComp (Specialisations) programme, can apply to one of the following specialisations offered in the School:
- Computer Science; or
- Infocomm Security; or
- Information Systems
Computer Science (CS) and Information Systems (IS) Specialisations
Students will complete the programme by selecting one of the following options:
Coursework Option:
Students are required to pass ten courses, with at least five courses selected from their specialisation (total of 40 Units). The remaining five non-specialisation courses (20 Units) can be chosen from level 4000 to 6000 courses offered by the School of Computing. Students are allowed a maximum of two level 4000 courses.
Project Option
The project option provides the experience for individual students to work on a significant computing project. It aims to prepare students with sufficient practical and/or research experiences in the computing field. Students who choose to embark on the project option will need to complete eight courses (32 Units), from level 4000 to 6000, offered by the School of Computing, with at least four courses (16 Units) from the area of specialisation.
Students are allowed a maximum of two level 4000 courses.
Dissertation Option
The dissertation option gives individual students the opportunity for independent study and research in the area of their selected specialisation. The dissertation is equivalent to four courses (16 Units). Students who opt to take the dissertation will need to complete six courses (24 Units), from level 4000 to 6000, offered by the School of Computing, with at least three courses (12 Units) from the area of specialisation.
Students are allowed a maximum of two level 4000 courses.
Both the project and dissertation will be carried out under the supervision of an academic staff, and the selection of the topic/area will be done in consultation with the advisor in the area of expertise.
Infocomm Security (InfoSec) Specialisation
Students enrolled to the Infocomm Security specialisation will complete the MComp programme by selecting one of the following options:
Option 1 - Dissertation Option
InfoSec specialisation students under this option are to complete six courses (24 Units), from level 4000 to 6000, offered by the School of Computing, with at least three courses (12 Units) from the InfoSec specialisation. A maximum of two level 4000 courses is allowed.
In addition, they will need to complete a project which culminates with a dissertation (16 Units).
Option 2 - Project Option
Students will need to complete eight courses (32 Units), from level 4000 to 6000, offered by the School of Computing, with at least four courses (16 Units) from the InfoSec specialisation. A maximum of two level 4000 courses is allowed.
Students will also complete a one-semester long project (8 Units). Students can undertake an external company/agency-proposed InfoSec projects with a SoC faculty member’s involvement, or a project proposed solely by a SoC faculty member.
Option 3 - Coursework Option
Students are required to pass ten courses (40 Units), with at least six courses (24 Units) selected from their specialisation. The remaining four non-specialisation courses (16 Units) can be chosen from level 4000 to 6000 courses offered by the School of Computing.
Out of the required maximum ten courses, students are allowed a maximum of two level 4000 courses.
Structure of MComp (General Track) Programme
Students are required to pass the MComp requirement of 40 Units, together with an additional 12 Units of bridging courses, meeting the following requirements:
- six essential computing courses (24 Units)
- four elective courses (16 Units)
- one capstone project (12 Units)
For admission and further details of Master of Computing programme, please visit: https://www.comp.nus.edu.sg/programmes/#graduates
Structure of Master of Computing in Artificial Intelligence Programme
Students admitted to the MComp in AI programme are required to pass a total of 40 Units, which can be completed via the Coursework option or Dissertation option.
Coursework Option
- Essential Courses:
Five courses (20 Units) from at least 3 of the 4 sub-areas in the MComp in AI courses list. - Elective Courses:
Five courses (20 Units) from level 4000 to 6000 courses offered by the School of Computing.
Out of the required ten courses, students will be allowed at most two level 4000 courses (8 Units).
Dissertation Option
The dissertation option gives individual students the opportunity for independent study and research in AI.
- Essential Courses:
Three courses (12 Units) from at least 3 of the 4 sub-areas in the MComp in AI courses list. - Elective Courses:
Three courses (12 Units) from level 4000 to 6000 courses offered by the School of Computing. - Dissertation:
MComp dissertation equivalent to four courses (16 Units) on a topic related to AI. The dissertation will be carried out under the supervision of an academic staff, and the selection of the topic will be done in consultation with the advisor in the area of expertise.
Out of the required six courses, students will be allowed at most two level 4000 courses (8 Units).
For admission and further details of Master of Computing in Artificial Intelligence programme, please visit: https://www.comp.nus.edu.sg/programmes/#graduates
Students must complete a total of 44 Units, which comprise of 8 courses (5 essential, and 3 electives) and 1 capstone project. The MSBA capstone course will be a year-long course in the form of capstone classes, industry analytics seminars, and a 3 – 6 month full-time^ capstone project.
For admission and further details, please visit: https://msba.nus.edu.sg/about/master-of-science-in-business-analytics-msba/
^Part-time students are recommended to do their capstone project with the company they are working for.
The MSc DFinTech is a master’s degree by coursework programme. Students are required to pass the requirement of 40 Units (equivalent to 10 courses), together with an additional 12 Units of bridging courses, meeting the following 52-Unit programme requirements:
- 28 Units Core/Essential Computing Courses
-16 Units used to strengthen computing and finance foundations of MSc DFinTech students
-12 Units used to strengthen FinTech foundations of MSc DFinTech students
- 12 Units Elective Courses
- 12 Units Capstone Project
For admission and further details, please visit: https://www.comp.nus.edu.sg/programmes/#graduates