Programme at a Glance
Intake and Application
Overview
The National University of Singapore (NUS) Master of Science (Computer Engineering), also known as MSc (Computer Engineering), is offered by the NUS College of Design and Engineering.
The MSc (Computer Engineering) – Machine Intelligence and Applications (MIA) Specialisation will give students an opportunity to explore artificial intelligence (AI) and machine learning (ML) techniques on a variety of engineering application-level problems in areas such as robotics, healthcare, and cyber-physical infrastructures.
As modern engineering systems attempt to employ machine intelligence techniques, courses in this specialisation attempt to inculcate knowledge pertaining to tools and techniques that go into the design process in a given application.
In certain courses (and also in compulsory project courses), student will have opportunities to undertake independent projects and use real-life application data for processing. A variety of machine learning tools will be introduced to facilitate handling data for a given engineering application.
The programme curriculum for this specialisation also includes a compulsory project course, which will serve as a challenge for students after they acquire the fundamental and practical skills in required areas of learning.
The project(s) could be:
Additional details about the project course (and the overall curriculum) can be found in the Programme Structure section below.
Admission to the NUS MSc (Computer Engineering) programme is granted on a competitive basis as places in the programme are limited. Applicants should possess the following minimum requirements:
| Academic | Bachelor’s Degree (preferably with Honours) or equivalent, in relevant engineering discipline or other disciplines including computing and applied mathematics from an institution of recognised standing |
| Skill/Experience | Not applicable |
| English Language | Applicants whose native tongue and medium of university instruction is not completely in English: Test of English as a Foreign Language (TOEFL) minimum score of 85 (Internet-based), or International English Language Testing System (IELTS) minimum Academic score of 6.0. Note: TOEFL / IELTS scores are valid for two years from the test date and should not have expired at point of application. Expired scores will not be considered for the application. |
| Other | Not applicable |
Candidates may visit the official Educational Testing Service (ETS) website for scheduling of TOEFL/GRE tests.
Note: Applications must be completed on the NUS Graduate Admission System (GDA2). Please see application information here.
Applicants are responsible for ensuring that application information and all supporting documents are truthful and correct. NUS reserves the right to verify information provided as part of an application. False or misleading information in an application (including but not limited to test scores, resumes, certificates, transcripts, etc.) is grounds for admission rejection, revocation and/or dismissal from the University.
The NUS MSc (Computer Engineering) programme is offered on the following basis (with estimated time to complete the programme indicated below):
| Full-time | 12–24 months |
| Part-time | 24–48 months |
Note: International applicants must be accepted into an approved full-time course in Singapore to apply for a Student’s Pass. For more information, refer to the Singapore Immigration & Checkpoints Authority (ICA) website.
The MSc (Computer Engineering) – MIA Specialisation is a 40-Unit coursework-based Master’s Degree programme comprising:
Core/essential courses (8 Units)
Elective courses (32 Units)
Core/Essential Courses
Students are required to complete at least two courses (totalling 8 Units) from the list below, with CEG5301 Machine Learning with Applications being compulsory.
| Course Code | Course Title | Units |
|---|---|---|
| CEG5101 | Modern Computer Networking | 4 |
| CEG5201 | Hardware Technologies, Principles, & Platforms | 4 |
| CEG5301* | Machine Learning with Applications | 4 |
* Compulsory for MIA Specialisation
Core/Essential Courses
Students must complete 32 Units of electives, of which 16 Units must comprise Specialisation Elective Courses and Project Elective Courses. The remaining 16 Units of courses can be chosen from courses within the MSc (Computer Engineering) programme (CEG graduate courses) and up to a maximum of two relevant non-CEG courses, at least level 4000 and above, subject to approval on case-by-case basis (additional fees might be applicable as determined by the course host department).
Specialisation Elective Courses
Students may choose to do two or three courses from the list below (two courses if doing two 4-Unit projects or one 8-Unit project, or three courses if doing one 4-Unit project; see Project Elective Courses below for more details).
| Course Code | Course Title | Units |
|---|---|---|
| CEG5302 | Evolutionary Computation | 4 |
| CEG5303 | Intelligent Autonomous Robotic Systems | 4 |
| CEG5304 | Deep Learning for Digitalisation Technologies | 4 |
| EE5731 | Visual Computing | 4 |
Project Elective Courses
It is mandatory to do at least one project course for the MIA Specialisation. Students are allowed to do either one or two 4-Unit project(s) or a single 8-Unit project.
| Course Code | Course Title | Units |
|---|---|---|
| CEG5001 | Computer Engineering Project (Minor) I | 4 |
| CEG5002 | Computer Engineering Project (Minor) II | 4 |
| CEG5003 | Computer Engineering Project | 8 |
CEG Graduate Courses
| Course Code | Course Title | Units |
|---|---|---|
| CEG5102 | Wireless Communications for IoT | 4 |
| CEG5103 | Wireless and Sensor Networks for IoT | 4 |
| CEG5104 | Cellular Networks | 4 |
| CEG5202 | Embedded Software Systems and Security | 4 |
| CEG5203 | Hardware Acceleration and Reconfigurable Computing | 4 |
| CEG5204 | Smart Sensing Systems | 4 |
| CEG5205 | AI Sensors and Virtual/Augmented Reality Technologies | 4 |
Note: A guide to course registration for graduate students is available here, and class timetables may be viewed here. For more information about the courses listed above (as well as other courses offered in the current academic year), please visit NUSMODS.
To graduate from the NUS MSc (Computer Engineering) programme – MIA Specialisation, students must meet the following requirements:
| Programme and/or Specialisation | Read and pass a total of 40 Units, comprising: At least 8 Units of core/essential courses, and 32 Units of elective courses |
| Course and/or Qualification | Refer to the Programme Structure above. |
| Grade Point Average (GPA) | Minimum 3.0 (out of maximum 5.0)
Please see also the University’s minimum standards for Continuation and Graduation Requirements. Specific programmes may implement stricter or additional requirements. |
| Other | Fulfil required e-courses as and when imposed at the University level. |
The University reserves all rights to review fees as necessary and adjust accordingly without prior notice.
| Tuition | S$53,100.00
(excluding GST) /
Note: The tuition fee stated above is for 40 Units. Students who are required to take more than 40 Units for programme completion are subject to supplementary tuition fees. |
| Application | S$109.00 (including 9% GST) Non-refundable and non-transferable |
| Acceptance | S$5,450.00 |
| Miscellaneous Student Fees | As published by Office of the University Registrar
Payable every regular semester |
Scholarships & Financial Assistance
The scholarships and financial assistance schemes presented here are examples of the kinds of funding from the University as well as third-party sponsors that might be available to eligible NUS Master's Degree (Coursework) programme students and applicants.
The information provided is subject to change, and warranties cannot be provided as to its completeness or accuracy. Students and applicants are strongly encouraged to conduct their own research, and refer to the relevant sponsors and/or websites for more detailed and up-to-date information.
Master of Science (Computer Engineering) Tuition Fee Rebate
NUS Master's by Coursework Enhanced Tuition Fee Rebate
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