Administered by the NUS Faculty of Science
The National University of Singapore Master of Science in Data Science and Machine Learning is an interdisciplinary graduate degree programme designed to nurture the next generation of leaders in data science.
The programme is supported by leading NUS researchers in data science as well as data scientists from industry, and offers multiple data science specialisations. Its curriculum incorporates interdisciplinary learning from fields such as computer science, mathematics and statistics, as well as data analytics and machine learning.
It is jointly offered by the Faculty of Science’s Department of Mathematics and Department of Statistics and Applied Probability, the School of Computing's Department of Computer Science, the Faculty of Engineering, and the Saw Swee Hock School of Public Health.
WHY THIS PROGRAMME?
Learn from the best of academia and industry
The NUS MSc in Data Science and Machine Learning is supported by leading NUS researchers in data science as well as data scientists from industry.
Choose from multiple specialisations
The programme offers multiple data science specialisations, and is jointly offered by the Faculty of Science’s Department of Mathematics, Department of Statistics and Applied Probability, and Department of Computer Science.
A robust, interdisciplinary curriculum
The curriculum incorporates interdisciplinary learning from fields such as computer science, mathematics and statistics, as well as data analytics and machine learning.
Professor Zhang Louxin
NUS MSc in Data Science and Machine Learning
Today, we face a massive explosion in the amount of data generated and retained by organisations, the government, and even individuals like you and me. In this age of “big data”, the ability to analyse and process data has become a critical skill set – data scientists make sense out of all this data and use it to make good business decisions.
The MSc in Data Science and Machine Learning is an interdisciplinary graduate degree programme. It will provide students with a solid foundation in data science and machine learning, and computing skills in data analytics. This is achieved by integrating statistics, mathematics and computing, as well as machine learning and AI.
The programme offers upgrading opportunities for industrial engineers and students who wish to equip themselves with data science and machine learning knowledge and data analytic skills. It will also help to meet the growing demands for a big data workforce in all industries by transforming graduates in quantitative science into data science and analytics practitioners.
I look forward to seeing you in the programme.
To apply for admissions to the NUS MSc in Data Science and Machine Learning programme, applicants should possess a Bachelor's (Hons) degree or a four-year Bachelor’s degree in quantitative science (e.g. Mathematics, Applied Mathematics, Statistics and Physics) or Engineering or Computer Science.
Applicants whose medium of university instruction is not English are required to demonstrate their English proficiency by possessing a Test of English as a Foreign Language (TOEFL) minimum score of 580 (paper-based) or 85 (Internet-based), or a International English Language Testing System (IELTS) minimum Academic score of 6.0.
Students are likely to take between 18 and 24 months to complete the programme on a full-time basis and 24 to 48 months on a part-time basis.
Admissions Intake & Application Period
Next Admissions Intake: August 2022
Application Period: To be announced
FULL TUITION FEES
Singaporeans and Singapore PRs may enjoy tuition fee subsidies
• There is an application fee of $50.
• Apart from tuition fees, there is a Student Services Fee (as published by NUS Registrar’s Office) payable every regular semester.
• Admissions to the programme is granted on a competitive basis as places in the programme are limited. A non-refundable and non-transferable acceptance fee of S$5,000 - which will be credited towards your tuition fees - is payable upon acceptance of offer.
• All fees quoted here are exclusive of prevailing GST, unless otherwise stated. The University reserves all rights to review fees as necessary and adjust accordingly without prior notice.
FREQUENTLY ASKED QUESTIONS
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After completing the programme, can I proceed to PhD?
The Faculty of Science offers PhD programmes by research only, and there is no direct admission route into such programmes for MSc by coursework students. Students who are interested to pursue a PhD upon completion of the MSc in Data Science and Machine Learning programme should apply separately for admission into the PhD programme of their choice.
What does the DSML Industry Consulting and Applications Project cover?
In this module (4 MCs), students will get a chance to apply their DSML skills and knowledge to address real-world problems, while collaborating with industry experts and sector leaders.
Projects will be solicited from the industry by the Programme Management Committee, and allocated to students based on choice, balloting, and/or suitability. There will be a wide variety of real-world DSML projects from local and international enterprises.
Students who receive sponsorship from their companies may also elect to work with their own respective organisations for the module, subject to the Programme Management Committee’s approval.
What is the difference between full-time and part-time students in this programme, in terms of workload and class timetable?
Full-time students may take a higher workload than part-time students, but both full-time and part-time students are expected to attend the same classes.
Full-time students may read up to five modules per regular semester, while part-time students may read only up to two modules per regular semester.
Both full-time and part-time students will be reading a common set of modules. Part-time students are expected to make their own arrangements to attend classes scheduled during the daytime. Prospective applicants whose work schedules will affect their ability to attend daytime classes are strongly advised against applying for the programme on part-time basis.
If I choose Graduate Certificates modules as my electives, how many certificates will I earn upon completion of the programme?
Students who take elective modules from two or more Graduate Certificate tracks will be eligible to be awarded at least two Graduate Certificates along with the Master’s Degree upon completion of the programme. Students who take elective modules only from the clusters are eligible to be awarded only the Master’s Degree.
For “Source of Finance” in the Graduate Admission System (GDA2), I can only select one option: “Self-finance”. I cannot select “Other Financial Assistance”. What should I do if I am seeking (or have already secured) other forms of financial assistance?
Because the MSc in Data Science and Machine Learning is a self-funded programme (i.e. it is not subsidised by the Singapore Ministry of Education), applicants are not eligible to apply for financial assistance from NUS (e.g. Tuition Fee Loan, Service Obligation Scheme, etc.). Hence, applicants will only be able to select the “Self-finance” option in GDA2.
Financial assistance provided by third parties (such as company sponsorships, external scholarships, education loans, funding by parents, etc.) are considered separate private arrangements between the applicants and their respective organisations or sponsors. Since these arrangements do not involve NUS, applicants who are financing their studies with assistance from third parties are still required to select the ‘Self-finance’ option, before uploading the necessary supporting documents.
International applicants must submit documentary evidence of their ability to support their study (e.g. a bank statement) indicating the availability of funding of at least S$40,000 or its equivalent.
Applicants who are sponsored by an individual or organisation will need to upload a letter from the sponsor with details/documentary proof of the sponsorship.
Those who are working in Singapore and applying for admission into the part-time MSc in Data Science and Machine Learning programme may upload a copy of their most-recent pay slip.
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