Bachelor of Science (Honours) with Major in Data Science and Analytics.
The four-year direct Honours programme is designed to prepare graduates who are ready to acquire, manage and explore data that will inspire change around the world. Students will read courses in Mathematics, Statistics and Computer Science, and be exposed to the interplay between these three key areas in the practice of data science.
The student learning outcomes of the DSA programme are:
The DSA programme is designed with sufficient technical depth to equip graduates with the ability to develop novel analytical tools for new scientific applications and industry problems that will emerge in future.
Professors teaching the DSA programme work with industry partners to develop, incorporate and infuse applications into the industry-linked capstone and elective courses and the Honours level project in the programme. This will ensure that graduates from the DSA programme receive a well-rounded education and have a competitive edge in the data science sector by being sufficiently prepared for the workplace with in-depth practical experience in a number of interesting and novel real-world business problem-solving case studies across various diverse domains, including healthcare and pharmaceutical, transportation, banking and finance, and public service.
Download the NUS CHS Data Science and Analytics programme brochure here.
NUS will adopt three new academic terminologies from 1 August 2023 – “Module” will be renamed “Course”, “Modular Credit (MC)” will be renamed “Unit”, and ‘Cumulative Average Point (CAP)” will be renamed “Grade Point Average (GPA)”. For more information, please click here (undergraduate) or here (graduate).
Updated on 24 June 2024
Harnessing Consulting Projects for Undergraduate Education
The Data Analytics and Consulting Centre is a consulting unit closely linked with the DSA programme. Interested students in the programme have the opportunities to assist in the Centre’s consulting services to the industry, thereby allowing them to gain practical experience in formulating data-driven solutions for real-world business problems in a wide spectrum of our corporate partners, from small and medium enterprises to multinational corporations.
The Centre’s Director source for industry projects and work with a team of professors to supervise students involved in the projects. The students prepare the data and perform data analytics on it. This way the students gain exposure to different business problems across different industries, better understand the challenges that the industry has and learn how industry overcomes these challenges using data analytics.
The Centre’s Director also ensure the security and confidentiality of data and monitor progress towards meeting the goals of the project. The team of professors attached to the project aids in the supervision of students, and in the interactions with clients to understand the problems they want to solve and the type of solutions are feasible for them to implement. The students are involved in the brainstorming of solutions, in the initial data massaging, in the writing of program codes and in the presentation of solutions to clients.
The benefits to students involved in the project are first that they learn how to treat data properly to ensure data security and confidentiality. They get to apply their statistical skills learned in classroom teaching and acquire new ones. They practice their programming knowledge in Python and R and learn how to access and make use of coding platforms. They develop their creative thinking by solving problems not encountered in structured classroom teaching. They boost their presentation skills during their presentations to clients. And finally, they have access to additional faculty mentoring.
Co-Operative Education
The Co-operative (Co-op) Education Programme at NUS formally integrates academic studies with relevant work experience, where students complete multiple internship stints alternating with regular academic semesters over their four-year candidature at NUS. Co-operative education is optional.
Starting from AY2021/2022, DSA students who choose to undertake the Co-op pathway will spend four semesters/terms (15–16 months) at the workplace with reputable employers. This will equip them with the skills, knowledge and expertise that enhance their employability after graduation.
We have entered into partnerships with several companies and organisations to offer internships for the DSA Co-op programme. These companies and organisations include government agencies, telecommunications companies, management consulting, defence science agencies, banking/financial institutions, port operators, multi-sector corporations, etc.
The study/internship sequence for DSA students opting for the Co-op pathway is currently under revision and will be made available here after it has been approved.
Admission Requirements
To be admitted to read a Major in Data Science and Analytics (DSA), you will need to apply for admission to the Faculty of Science. After you are successfully admitted, you would be able to declare DSA as your major.
To be able to read the first-year core course (DSA1101), you will need a good H2 pass or equivalent in Mathematics/Further Mathematics. If you do not have the background, you are to read the bridging course, MA1301 or MA1301X, first.
Programme Requirements and Sample Study Plan
The requirements of the DSA programme can be downloaded here.