The Master of Science in Artificial Intelligence (MSAI) programme is created for students who wish to develop, design and implement AI systems and at the same time cultivate a deep understanding of AI for project management and policy making. The programme emphasizes on AI theory, techniques and tools to solve real world problems with multiple types of constraints, e.g. problems with limited training data and big data problems. Equipped with both theoretical and activity-based learning, this will allow graduates to upgrade their competencies and skills. The core courses focus on the foundations of AI knowledge, such as machine learning and deep learning, while a wide range of elective courses in different domains, such as image, video, text and IoT data are available to deepen understanding and knowledge in this specialisation.
MSAI programme is an intensive one-year full-time (or 2-year part-time) programme by coursework. Students will be awarded the Master of Science in Artificial Intelligence after completion of study. The minimum and maximum periods of candidature for full-time candidates are 12 and 30 months respectively. For part-time candidates, they are 24 and 48 months respectively. The programme consists of a total of 30 Academic Units (AUs), with 12 AUs stemming from core courses and 18 AUs from master project and elective courses, covering general AI techniques and techniques especially for image, video, IOT and time series data. Each course is 3 AUs and has 39 contact hours consisting of lectures, tutorials, example classes and labs over 13 weeks. The master project of AI is a one year project with 6 AUs. The master project is not a compulsory component. The bridging course, Python Programming, with zero AU is for students who have graduated from bachelor programmes with limited programming training and working adults who do not usually write codes. All students can take the bridging course in their first semester. It is not a compulsory course.
Please click on item for the latest information:
Schedule of Key Academic Activities (Graduate Programmes)
|Core Courses||12 AUs|
|Elective courses/ Master Project of AI||18 AUs|
|Total Graduation Requirement||30 AUs|
You can check the courses registered through the GSLink. You may add or drop courses during the Add/Drop period, within in the first two weeks of the semester.
Course registration after the Add/Drop period will not be accepted.
All students are advised to check via their GSLink before the end of the Add/Drop period to ensure courses have been registered / de-registered correctly.
If you wish to withdraw from any courses, you must submit your request to the school by the 10th week of the semester, otherwise a 'Fail' grade will be reflected in your transcript.
Do note that there is a maximum for course registration allowed per semester:
- Full-time students: Up to 5 courses (15 AUs)
- Part-time students: Up to 3 courses (9 AUs)
Also note that there is a minimum and maximum candidature:
- Full-time students: 12 months to 30 months
In any case if you want to withdraw from any courses, you have to submit your request to the School by the 10th week of the semester, otherwise a 'Fail' grade will be reflected in your transcript.
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You may view the course information here
To be awarded the Master in AI degree, student must:
- Complete a total of 30 AUs
o Compulsory courses 12 AU
o Elective courses / master project 18 AU
- Attain a minimum CGPA of 2.50 at the completion of the programme of study.
Satisfactory Academic Performance
In any term of study, a coursework student is considered to be making satisfactory progress if he attains a minimum TGPA of 2.50.
Poor Academic Performance, AW and FO
A coursework student with poor academic performance will be subject to the following actions:
1. Academic warning (AW) if TGPA or CGPA <2.50 in any term of study.
2. Termination of Candidature (FO) if TGPA <2.50 for the second consecutive term of study.
Course Coordinator: Sourav Sen Gupta (Dr) firstname.lastname@example.org
This project, to be performed over two consecutive semesters, provides students an opportunity to work with faculty members in SCSE and to learn state-of-the-art AI techniques for a particular problem. Scope of project may be based on staff research interest or industrial collaboration. Students are expected to document their work and report their findings in formal reports and give oral presentations together with demonstration (if any) as the conclusion of their projects.
The master project of AI is a one-year project with 6 AUs.
Interested students are to register for AI6129 during the Course Registration Period first, project is chosen in consultation with a supervisor (via the on-line MSAI project application available via GSLink) during the first two weeks of the semester in which the course will be taken. The project topic requires agreement by the proposed supervisor.
- Faculty Members propose Projects
- Students choose AI Master Projects
- Students work on the Projects
- Students submit the AI Master Project Report
- Supervisor and Examiner Evaluation
- Finalization of Marks and Marks Submission
Request for leave of absence must be submitted at least 7 working days in advance of leave. Reasons for application must be clearly indicated with relevant supporting documents attached.
Students who are not attending classes and not working on their project are advised to apply for leave of absence. Otherwise, they shall be liable for full tuition fees.
Students who are granted leave of absence after having attended lessons for more than 2 weeks of the term shall be liable for tuition fees for the entire term.
For each term of leave granted, the student will be liable for an administrative fee.
After the leave period, you are required to contact your Programme Administrator immediately.
The maximum period of LOA allow is (1) academic year for each application.
Note that LOA is counted towards your maximum candidature period.
Leave of Absence Form
MSAI TIMETABLE FOR SEMESTER 2, AY2020 (STARTING 11 JANUARY 2021)
INTRODUCTION TO AI & AI ETHICS
|Monday||6.30pm - 9.30pm||LT3||Prof Yu Han+/|
Prof Bo An/
Dr Melvin Chen
TEXT DATA MANAGEMENT & PROCESSING
|Tuesday||6.30pm- 9.30pm||LT4||Prof Sun Aixin|
TIME SERIES ANALYSIS
|Wednesday||6.30pm- 9.30pm||LT3||Prof Pan Guangming|
|Thursday||6.30pm- 9.30pm||LT5||Prof Zhang Jie|
DEEP NEURAL NETWORKS FOR NATURAL LANGUAGE PROCESSING
|Friday||6.30pm- 9.30pm||LT3||Prof Joty Shafiq Rayhan / Dr Kim Jung Jae |
AI MASTER PROJECT
|Dr Sourav Sen Gupta|
MSAI TIMETABLE FOR SEMESTER 1, AY2020-2021 (STARTING FROM 11 AUGUST 2020)
Mathematics for AI
|Saturday||10am–1pm||Online/ LT3||Assoc Prof Kong Adams|
Machine Learning: Methodologies and Applications
|Monday||6.30pm- 9.30pm||Online/ LT3||Assoc Prof Sinno Jialin Pan|
Deep Learning and Applications
|Thursday||6.30pm- 9.30pm||Online/ LT15||Assoc Prof Xavier Bresson|
|Friday||6.30pm- 9.30pm||Online/ LT3||Assoc Prof Lu Shijian|
Advanced Computer Vision
|Tuesday||6.30pm- 9.30pm||Online/ LT3||Assoc Prof Chen Change Loy|
Neuro Evolution and Fuzzy Intelligence
|Wednesday||6.30pm- 9.30pm||Online/ LT3||Asst Prof Zinovi Rabinovich+/|
Dr Ang Kai Keng
|Saturday||2.30pm-5.30pm||Online/ LT3||Asst Prof Cheng Long+/|
Asst Prof Tan Rui
(this is a bridging course)
|Tuesday||6.30pm- 9.30pm||Online/ LT3||Dr Sourav Sen Gupta|
AI Master Project
|N.A.||Dr Sourav Sen Gupta|
(MSAI Project Coordinator)
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