Master of Science in Artificial Intelligence (MSAI)

ai is the future

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 Courses12 AUs
Elective courses/ Master Project of AI18 AUs
Total Graduation Requirement30 AUs
Please register your courses within the stipulated dates to avoid disappointment.

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.

To write in, please fill in this  form.

Students are required to register your calculator before the examinations.
Please register your calculators at  Dates for Registration of Calculators​.

Note: Students (full time or part time) need not register their calculators if they have previously registered and the seal of the calculator is intact.

Please refer to this link for rules governing the use of calculators at examinations.

Please refer to this link for the approved list of calculators. Please use only calculators that appear in the approved list. Calculators which do not appear in the approved list will not be registered.

The University will allow the use of approved graphic calculators with effect from S1 AY2006/2007 examinations. Please refer to the list above for the approved graphic calculator models. Students are responsible for clearing any information and/or programs stored in the graphic calculators before the examination.​

Each student is allowed to convert their status of study only ONCE. Once successfully converted to full time study, you cannot convert back to part time study or vice versa.

You may view the course information here 

Graduation Requirements
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) sg.sourav@ntu.edu.sg

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.

Project Timeline
- 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 

Leave of Absence (LOA) is taken when a candidate is unable to continue his studies for a short period of time. All applications for LOA are subject to the School’s approval. The candidate is allowed to continue his studies after the leave period.

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​

Academic Calendar

MSAI TIMETABLE FOR SEMESTER 1, AY2021-2022
(STARTING FROM 10 AUGUST 2021)

CourseDayTimeVenueLecturers
CORE
AI6101
INTRODUCTION TO AI & AI ETHICS
Monday
(16 August 2021)
 
6.30pm- 9.30pm LT7 Prof Yu Han+/
Prof Bo An/
Dr Melvin Chen
CORE
AI6104
MATHEMATICS FOR ARTIFICIAL INTELLIGENCE
Saturday
(14 August 2021)
9.30am-12.30pm LT4 Prof Adams Kong
CORE
AI6102
MACHINE LEARNING METHODOLOGIES & APPLICATIONS
Prerequisites: AI6104,
taken probability and linear algebra courses
Wednesday
(11 August 2021)
6.30pm- 9.30pm LT8 Prof Sinno Jialin Pan
CORE
AI6103
DEEP LEARNING & APPLICATIONS
Thursday
(12 August 2021)
6.30pm- 9.30pm LT4 Prof Li Boyang,
Albert
 
AI6121
COMPUTER VISION
Friday
(13 August 2021)
6.30pm- 9.30pm LT4
 
Prof Lu Shijian
 
AI6122
TEXT DATA MANAGEMENT & PROCESSING
 
Tuesday
(10 August 2021)
6.30pm- 9.30pm LT4
 
Prof Sun Aixin
AI6124
NEURO EVOLUTION & FUZZY INTELLIGENCE
Wednesday
(11 August 2021)
6.30pm- 9.30pm LT19
 
Prof Mahardhika Pratama/
Dr Ang Kai Keng
AI6128
URBAN COMPUTING
Saturday
(14 August 2021)
2.30pm-5.30pm LT4Prof Cheng Long+/
Prof Tan Rui
AI6129
AI MASTER PROJECT
(6 AUs)
   Dr Sourav Sen Gupta
AI6120
PYTHON PROGRAMMING
(this is a bridging course with ZERO AU)
Tuesday
(10 August 2021)
6.30pm-9.30pm LHN-LT
The Arc
Dr Sourav Sen Gupta

 

MSAI TIMETABLE FOR SEMESTER 2, AY2020
(STARTING 11 JANUARY 2021)

Course
Day
Time
Venue
Lecturers
CORE
AI6101
INTRODUCTION TO AI & AI ETHICS
Monday6.30pm - 9.30pmLT3Prof Yu Han+/
Prof Bo An/
Dr Melvin Chen
AI6122
TEXT DATA MANAGEMENT & PROCESSING
Tuesday6.30pm- 9.30pmLT4Prof Sun Aixin
AI6123 
TIME SERIES ANALYSIS
Wednesday6.30pm- 9.30pmLT3
Prof Pan Guangming
AI6125 
MULTI-AGENT SYSTEM
Thursday6.30pm- 9.30pmLT5
Prof Zhang Jie
AI6127
DEEP NEURAL NETWORKS FOR NATURAL LANGUAGE PROCESSING
Friday6.30pm- 9.30pmLT3
Prof Joty Shafiq Rayhan / Dr Kim Jung Jae ​
AI6129
AI MASTER PROJECT
   Dr Sourav Sen Gupta



COVID-19 Grant (for New Accepted Students)
Successful Students will receive a one-time grant of 10% off the tuition fees (before GST). This grant will be applied on the final payment of the course and it can only be used to offset the tuition fees and no other fees related to the course of study.
NOTE: This grant is not applicable to those on scholarship, sponsorship, alumni and SkillsFuture Study Award. It is not stackable to any other discounts/scholarships/awards that you are receiving.

Application Period: 12 July 2021 - 30 July 2021

Click here for Application Form
No.Staff/OfficeContact Details
1Programme Administrator
Ms Grace Ho
Email : aslcang@ntu.edu.sg
2Programme DirectorAssoc Prof Adams Kong
Email: AdamsKong@ntu.edu.sg
3Student WellbeingWebsite
4One Stop @ SAC50 Nanyang Avenue NS3-01-03,
Academic Complex North Singapore 639798
Website

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