Bachelor of Science (Honours) with Major in Data Science and Economics Cross-Disciplinary Programme

Admissions

The application requirements for the respective applicant groups are as follows:

1. Singapore-Cambridge GCE ‘A’ Level qualification- A very good pass in H2 Mathematics
2. International Baccalaureate (IB) Diploma- A very good pass in HL Mathematics or Mathematics: Analysis and Approaches (MAA)
3. NUS High School Diploma- Very good major CAP in Mathematics
4. Polytechnic Diploma from Singapore- Excellent Overall Polytechnic results with a Diploma Plus certification in Mathematics listed here.
5. International Qualifications- Strong Year 12 pass or strong higher-level pass in Mathematics.
6.  

Bachelor of Science (Honours) with Major in Data Science and Economics Cross-Disciplinary Programme

Mid-Stream Admission

Mid-stream admission is open to CHS enrolled undergraduate students who are keen to pursue the Data Science and Economics (DSE) cross-disciplinary programme and are reading/have read MA2001, MA2002 and CS1010S (or any of its variants). Only students who have obtained very good results for these courses will be considered for mid-stream admission. Other criteria such as overall GPA (Grade Point Average), high school results etc may be taken into consideration. The Data Science and Economics programme committee may also conduct interviews to assess applicants for suitability for the programme.

Interested CHS students should submit their application here (refer to the section Current Undergraduate in NUS/Yale-NUS/NTU/SMU/SUTD/SUSS/SIT (all citizenships)) via the NUS Office of Admissions (OAM) when the application window for transfer opens in February and October each year, for transfer to DSE in Semester 1 and 2 respectively.

Bachelor of Science (Honours) with Major in Data Science and Economics Cross-Disciplinary Programme

Curriculum

The curriculum incorporates interdisciplinary learning from data science and economics, with foundations in computer science, mathematics and statistics.

In addition to higher-level courses that integrate knowledge and concepts from lower-level core foundational courses, students also read courses related to the application of data science and analytics to the financial and labour markets, and applied economic issues in education, health, housing and industrial organisation.

The programme has a substantial focus on experiential, self-directed and industry-relevant learning. Students get to learn from data science professionals and economists within and beyond a formal classroom setting. A suite of newly designed integrated courses, such as digital currencies, data science in financial technology and the digital economy, offer substantial practical components related to real-world problems, with some of these courses co-taught by industry experts.

The programme culminates in a capstone project, an industry-driven platform where students apply integrated knowledge and skills in data science and economics to address challenging, real-world issues in economics, finance, public policy and society.

Students can also participate in student exchange programmes with overseas partner universities. This provides them exposure to different cultures and academic environments, which broadens their intellectual and global outlook.

Bachelor of Science (Honours) with Major in Data Science and Economics Cross-Disciplinary Programme

Graduation

The Bachelor of Science (Honours) degree with Major in Data Science and Economics will be awarded to candidates who complete 160 Units (table below), typically over 4 years, and fulfil graduation requirements in the XDP. Those who do not meet the requirements of an Honours degree will be awarded a Bachelor of Science degree with Major in Data Science and Economics.

Please refer to this page for a sample study plan of the programme.

Bachelor of Science (Honours) with Major in Data Science and Economics Cross-Disciplinary Programme

Career Prospects

Large economic data sets are constantly generated by consumption, production and investment activities. At the same time, new analytical techniques like machine learning and nowcasting are becoming part of mainstream econometric tools. There is therefore a growing demand for professionals with cross-disciplinary expertise in both data science and economics.

Graduates will have diverse career choices as data science professionals and economists in the public sector, as well as leading public and private organisations in a multitude of industries including consulting, financial services, healthcare, insurance and wealth management, amongst others. These are examples of a growing number of fields which increasingly rely on the extensive collection, processing and analyses of economic data, calling for the rigour of data science as well as the intuition of economics.

Bachelor of Science (Honours) with Major in Data Science and Economics Cross-Disciplinary Programme