Programme Structure

Announcements

Last updated 3 July 2026

Please refer to the links in the table below for the programme requirements.

Please note that students should refer to programme documents that correspond to their year of matriculation.

Declaration of Major/2nd Major/Minor should be done before the start of the 5th semester.
Late declaration will not be considered by the department.

Matriculation Year Major in Statistics 2nd Major in Statistics Minor in Statistics
AY2019/20 and AY2020/21 [160 units] [42 units] [20 units]
AY2021/22 and after [160 units] [40 units] [20 units]
Matriculation Year Major in Data Science and Analytics 2nd Major in Data Analytics Minor in Data Analytics
AY2019/20 and AY2020/21 [160 units] [42 units] [20 units]
AY2021/22 [160 units] [40 units] [20 units]
AY2022/23 to AY2025/26 [160 units] [40 units] [20 units]
Matriculation Year Major in Data Science and Applied AI   2nd Major in Data Analytics       Minor in Data Analytics
 AY2026/27 and after [160 units] [40 units] [20 units]


Major in Data Science and Applied AI (DSAAI)
The DSAAI programme is applicable only for Cohorts AY2026/27 and after. It supersedes the Major in Data Science and Analytics (DSA) which is applicable only for Cohorts AY2019/20 to AY2025/26.

Major in Data Science and Economics 
The Data Science and Economics cross-disciplinary programme is hosted by the Department of Mathematics. 
For more information, please refer to this page.

Yes. Students are strongly advised to follow the sample study plan provided in the programme structure documents as closely as possible to ensure timely graduation.

 

In particular, students in the Data Science and Analytics (DSA) and Data Science and Applied AI (DSAAI) programmes should complete:

 

  • DSA1101 by Year 1, Semester 2
  • DSA2101 by Year 2, Semester 2
  • DSA3101 by Year 3, Semester 2

 

Failure to complete these courses according to the recommended timeline may delay graduation. Students are responsible for ensuring that they have satisfied all prerequisite requirements before enrolling in a course. As the department generally does not grant prerequisite waivers, students are advised to plan their study schedules carefully.

If you are unable to complete the required courses according to the recommended study plan, you must complete any outstanding required courses by Semester 1 of the following academic year to minimise the risk of delaying your graduation.

The reading of courses during UPIP is strongly discouraged. Should, in exceptional circumstances, you need to read a course, you will need to obtain final approval from the UPIP team. Please visit the UPIP webpage for more information. 

 

For students intending to take the Undergraduate Professional Internship Programme (UPIP) to fulfil the ST/DSA/DSAAI graduation requirements:

 

(a) The Department of Statistics and Data Science (DSDS) grants blanket approval for students to read either ONE of the following DSA courses concurrently with UPIP:

 

  • DSA3101, or
  • One DSA426X course

 

This blanket approval applies only if DSA3101 or one DSA426X course is the only course you are reading concurrently with UPIP. In this case, you do not need to seek approval from the DSA3101 or DSA426X course coordinator to read the course concurrently with UPIP. 

 

If you are taking only DSA3101 or one DSA426X course together with UPIP, you may also take one GEN-coded or one CFG-coded course.

 

However, you must:

  • Obtain approval from the respective GEN/CFG course coordinator, and
  • Include this approval when submitting your appeal to the UPIP team.

 

Permissible combinations include:

  • DSA3101 + one GEN-coded course
  • One DSA426X course + one CFG-coded course

 

Not permissible:

  • DSA3101 or DSA426X together with any non-GEN/CFG-coded course

 

(b) For all courses offered by DSDS, you must obtain written consent from your employer confirming that you may attend all lectures and tutorials. This written approval must be submitted to the DSDS course coordinator when requesting permission to read courses concurrently with UPIP.

 

Exception: You do not need employer approval if you are taking only DSA3101 or one DSA426X course concurrently with UPIP under the blanket approval described in (a).

 

(c) Do note that the course coordinator is not obligated to make special arrangements or approve requests to read additional courses for students on UPIP. Students should therefore plan their study schedules carefully before applying for an internship.

Yes. As part of the compulsory graduation requirements for all our undergraduate degree programmes, students are required to complete either an approved internship (UPIP or NOC) or an approved research project (UROPS or FYP). These are stated in our programme structure documents – please refer to our Graduation Requirements webpage for more information too.

 

Both internships and research projects provide valuable experiential learning. Students interested in industry practice may choose the internship option, while those wishing to deepen their academic or research experience may opt for a research project. Students should carefully consider which pathway best aligns with their interests and career goals.

The DSAAI major applies only to students admitted from Cohort AY2026/27 onwards. It replaces the DSA major, which is applicable only to students admitted between AY2019/20 and AY2025/26. Students already enrolled in the DSA major will continue to follow the curriculum requirements of their admitted cohort. The new curriculum will not apply to students who have already enrolled under the previous curriculum.

To be admitted to read the DSAAI major, you will need to apply for admission to the Faculty of Science. After you are successfully admitted, you will be able to declare DSAAI as your major.

 

To be able to read some of the first-year core courses, you will need a very good H2 pass or equivalent in Mathematics/Further Mathematics. If you do not have this background, you are required to read the bridging course, MA1301 or MA1301X, first.

The revised curriculum has been updated to better prepare students for modern data science and AI practice.

 

Some of the key enhancements include:

  • CS1231 Discrete Structures to provide students with a stronger mathematical foundation

  • CS2109HS Introduction to AI and Machine Learning as a prescribed course for the Artificial Intelligence pillar of the Common Curriculum courses

  • Updated core courses that integrate and modernise existing content:
    • DSA3111 Numerical Computation and Optimisation
    • ST2133 Statistical Inference

  • Two new practice-oriented essential courses:
    • DSA2111 Cloud-Based Data Science and Programming
    • DSA2112 Practical AI for Data Science Pipelines
  • New and refreshed advanced electives:
    • DSA4214 Computer Vision
    • DSA426x Applied AI in X series (formerly Sense-making Case Analysis courses).

 

These updates reflect current industry practices and emerging developments in data science and artificial intelligence.

The new DSAAI programme structure is designed to maintain a manageable workload and provide better alignment of courses. While there are updates to the programme structure, the overall degree requirements remain at 160 units, across the three key components: Common Curriculum (52 units), Major Requirements (60 units), and Unrestricted Electives (48 units).

 

Students will still have ample room in their study plans to pursue a minor, second major, internships, exchange programmes, and/or research opportunities, depending on how they plan their semesters. Students are strongly encouraged to follow the recommended study plan provided on the DSAAI programme structure document, which illustrate recommended course sequencing to support smooth progression through the degree.

Contact Us
For general enquiries on undergraduate programmes (Statistics, Data Science and Analytics, Data Science and Applied AI), please email askdsdsug@nus.edu.sg.

For enquiries related to undergraduate student exchange programmes, please email askdsdssep@nus.edu.sg.