Master of Science in Data Science (MSDS)

Master (Coursework)

Provided by

Programme Type

Full-time, Part-time

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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.

 

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Unique Feature

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.

Admission Requirements

The following documents are to be submitted online via the Graduate Admission System:  

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For admissions matters and enquiries, please email directly to the following:

MSc Data Science: ccds-msds@ntu.edu.sg

 

Programme Structure & Duration

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.

 

Curriculum

View the Course Content Here

*Note: the curriculum is subject to change.

Career Prospects

Top 5 Careers in Data Science

  • Data Scientist
  • Data Analyst
  • Business Intelligence Developer
  • Applications Architect
  • Statistician

Additional Information

The tuition fees for Academic Year 2025/26 and after are as follows: 

Tuition Fees S$63,220
Deposit Fees S$5,000 – This amount will be deducted from the first billing.
Non-refundable & non-transferable
(Payable upon acceptance of offer of admission)
Payment Schedule Full-time students will be billed in 2 semesters while part-time students will be billed in 4 semesters.

*All fees shown are inclusive of 9% prevailing GST. 

Please note the following:

  1. All fees shown are inclusive of the prevailing Goods and Services Tax (GST).
  2. The above fees are based on the shortest candidature period. Additional fees will be determined and applied on a case-by-case basis.
  3. There is an application fee of S$50.
  4. A one-time miscellaneous fee will be billed every academic year. Please click here for details.
  5. Tuition fees do not include the cost of recommended textbooks and other course materials. The costs of travel, accommodation and miscellaneous expenses must be borne by the student.
  6. All grants will be distributed evenly across the entire billing period, whether it is 2 semesters for full-time students or 4 semesters for part-time students. (The tuition fee will be paid in two instalments at the beginning of each semester. Study grants and other incentives will also be applied to these two instalments.)
  7. The university currently has no scholarship, government service agreement, or service obligation scheme available for students.
  8. The fees and grants are reviewed annually and subject to revision

 

Financial Assistance: 

Singaporeans and permanent residents who enrol in self-financed master’s by coursework programmes at NTU will enjoy a $5,000 subsidy, with those in need of financial aid will receive up to $15,000.

All NTU alumni will receive an additional 10 per cent tuition fee rebate 

SCs and SPRs may enjoy tuition fee subsidies under SkillsFuture Singapore (For enquiry: sfcredit@ntu.edu.sg)

 

Scholarships:

(Singapore Citizens only) The Singapore Digital (SG:D) Scholarship is offered by the Infocomm Media Development Authority (IMDA).  Click here for more information about the scholarship.

 

International Students

Please view more information Here.


Frequently Asked Question

For more Frequently Asked Question, please click here.

Contact Us

Please contact  ccds-msds@ntu.edu.sg for more information on MSDS.