/enri-thumbnails/careeropportunities1f0caf1c-a12d-479c-be7c-3c04e085c617.tmb-mega-menu.jpg?Culture=en&sfvrsn=d7261e3b_1)
/cradle-thumbnails/research-capabilities1516d0ba63aa44f0b4ee77a8c05263b2.tmb-mega-menu.jpg?Culture=en&sfvrsn=1bc94f8_1)
7e6fdc03-9018-4d08-9a98-8a21acbc37ba.tmb-mega-menu.jpg?Culture=en&sfvrsn=7deaf618_1)
Data science is a data-driven approach to problem solving and scientific exploration that involves the process of collecting, managing, analyzing, explaining, and visualizing data and analysis results. It is inherently interdisciplinary in nature. The aim of the Master of Science in Data Science (MSDS) programme is to provide graduate students with robust training in the field of Data Science. The program is led and mainly run by the College of Computing and Data Science (CCDS). Faculty members from several other schools also actively contributes to this programme to support interdisciplinary flavour of data science.
The unique features of the MSDS program are as follows:
Tight integration of relevant theories and principles from social sciences with computing-driven data science. Given that data is generated by humans or machines, it is paramount to consider social context for any data science problem. Consequently, the core courses focus not only on computing-driven data science courses but also courses and projects that steer students to take a realistic look at a data science problem by considering various social, economics, and behavioural issues. A wide range of elective courses to tackle various data types one may encounter in different application domains along with deeper insights to psychology and economic theories are provided to broaden the knowledge.
Comprehensive coverage of the data science ecosystem. In MSDS program, we do not just simply teach analytics. Data analytics techniques are ineffective if your input data is dirty, messy, and not ready for analysis! Our program ensures every student goes through the entire data science ecosystem – from data preparation to data visualization, giving them a comprehensive depth and breadth of data science.
The Capstone Project gives students hands-on opportunities to realize the data science ecosystem for domain-specific applications in industrial settings or academia. The former enables a student to address industry-specific data science problem whereas the latter allows a student opportunity to address such problem for non-industrial end users.
Inter-disciplinary nature of MSDS is supported by courses taught by faculty members from different schools. In particular, the core course entitled “Data Science Thinking” will be jointly taught by faculty members from the School of Social Sciences (SSS) and CCDS. Several electives are also taught by faculty members of SSS and the School of Physical and Mathematical Sciences (SPMS). Furthermore, students may take an application domain-specific elective that may be offered by any school (e.g., NBS, SBS, ASE, MAE, EEE, SPMS, SSS, LKC) in NTU (excluding CCDS). Lastly, a capstone project in the MSDS program can be a collaboration between domain-specific industry participants, faculty members from various schools and CCDS.
- At least a good relevant bachelor's degree
- Relevant working experience is an advantage
APPLICATION INFORMATION
Application
Applicants are to submit their applications via the online application portal (Graduate Admission System).
A S$50 non-refundable application fee (per online application and inclusive of prevailing GST) is payable.
Starting from AY2025 intake, the application period are as follows:
| Intake | Opening Date | Closing Date |
|---|---|---|
| August intake* | November | end February |
| January intake | July | end August |
*For the August intake, applicants who submit their applications by end of January may be considered for early offers of admission.
Application Status
The application outcome will be released via the online Graduate Admission System by end May/June (August Intake) or end November (January intake).
Submission of Application
Please ensure that all mandatory and supporting documents are uploaded in the online Graduate Admission System before submitting your application. The College will not assist to upload documents on behalf of applicants. Submission of hardcopy documents is not required at the application stage.
Documents submitted must meet the following requirements:
- Documents are in PDF format.
- Documents are in English. All documents that are not in English must be accompanied by certified true copies of the English translated documents.
Only applications submitted by the stipulated application deadline will be processed.
Applications deemed incomplete by the College will not be processed (e.g. those with insufficient documents, transcripts that do not contain all semesters’ examinations results or have not satisfactorily completed their Bachelor’s degree requirements).
Applicants are required to submit a new application with a full set of supporting documents should they be interested to apply for the programme again.
***Applicants should consider carefully that they are able to cope with work/personal/financial commitments before applying/accepting admission as full-time/part-time candidates. Deferment of admission base on these reasons may not be considered.
The following documents are to be submitted online via the Graduate Admission System:
| Checklist of Mandatory Documents to be Submitted Online | |
|---|---|
| Proof of Residence | Singapore Citizens and Singapore Permanent Residents: · Identity Card (Pink/Blue NRIC)^ · Re-Entry Permit (required only for Permanent Residents) ^ International Applicants: · Passport copy (bio page) and · Work Pass (Employment Pass/S Pass), Long-Term Visit Pass, Dependent’s Pass and other Passes (if applicable) ^ ^Please provide both the front and back of these documents in full colour. |
Academic Qualifications (with English Translation)
| Applicants who have completed their Bachelor’s Degree: · Official Degree Certificate for Bachelor’s Degree (certifying award of Bachelor’s degree) # · Official Transcript for Bachelor’s Degree # All academic documents must be certified true copy (i.e. contains University seal and/or Registrar’s signature). Transcripts must show the grades of all courses taken. Applicants who have not received their Bachelor’s Degree Certificate are required to submit an official letter from their University stating their expected date of graduation or certifying their completion of Bachelor’s Degree. *** For conditional offers, latest transcript is acceptable Applicants who have obtained higher degrees should also submit their Master’s/PhD Degree Certificate(s) and the relevant Official Transcript(s). #Both original and English translated copies |
Test Scores
Medium of Instruction letter |
|
| Referee’s Report (not applicable) |
|
For admissions matters and enquiries, please email directly to the followings:
MSc Data Science: [email protected]
Total Graduation Requirement: 30 AUs
| Study Type | Minimum Candidature | Maximum Candidature |
| Part Time Study | 2 years (4 semesters) | 4 years (8 semesters) |
| Full Time Study | 1 year (2 semesters) | 2.5 years (5 semesters) |
Except for a bridging course, each course is a 3 AU course with 39 teaching hours, including lectures, tutorials, example classes and labs over 13 weeks. The capstone project is a one-year project with 6 AU. The bridging course, Python Programming, with zero AU is for students graduated from bachelor programme 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.
View the Course Content Here
*Note: the curriculum is subject to change.
Top 5 Careers in Data Science
- Data Scientist
- Data Analyst
- Business Intelligence Developer
- Applications Architect
- Statistician
Programme Fees in AY2025 and after
Please note that this MSc programme is a non-MOE subsidised programme and is not eligible for Service Obligation
| S$ | ||
| Tuition Fees Inclusive of 9% GST | 63,220 | |
| Deposit Payment inclusive of 9% GST (The deposit will be used to offset the semester 1 tuition fees after matriculation) | Non-refundable & non-transferable (Payable upon acceptance of offer of admission) | 5000 |
| Payment Schedule | Full-time students will be billed in two semesters while part-time students will be billed in four semesters | |
| Financial Assistance | Singapore Citizens (SCs): enjoy a study grant of S$10,000 + prevailing GST (S$10,900). • Singapore Permanent Residents (SPRs): enjoy a study grant of S$5,000 + prevailing GST (S$5,450). • Needy SCs and SPRs may apply for financial aid (up to S$5,450 in addition to the SC/SPR study grant). • NTU Alumni: On top of the above, alumni can enjoy a 10% grant of the tuition fee (S$5,800 + Prevailing GST (S$6,322) | |
| Education loans | Education loans with some leading banks/institutions that offer optimal lending terms to eligible applicants are available. Please note that NTU is not an agent for these banks/institutions and students must apply for the loans directly with the respective banks/institutions and abide by their terms and conditions. |
Note: Tuition fee is payable each semester regardless of the number of courses registered that term. The University reserves the right to revise its fees every year without notice.
Scholarship
International Students
Please view more information Here.
Frequently Asked Question
For more Frequently Asked Question, please click here.
Contact Us
| No. | Staff/Office | Contact Details |
| 1 | Programme Administrator | Email : [email protected] |