Program Overview

Introduction to the Data Science and Economics Programme

The Data Science and Economics (DSE) cross-disciplinary programme aims to produce students who have a strong foundation in data science and economics, as well as hands-on experience with empirical analysis of economic data. This programme is designed to analyse and interpret the local and global impact of data on individuals, organisations, society, and the global economic ecosystem.

Programme Description

The DSE programme incorporates inter-disciplinary learning from data science and economics, with foundations in computer science, mathematics, and statistics. The curriculum includes 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 market, labour market, and other applied economic issues in education, health, housing, and industrial organisation.

Student Learning Outcomes

The student learning outcomes of the DSE programme are:

• To comprehend the conceptual and methodological foundations of analytical techniques for data science and the fundamentals of theoretical and empirical economic analysis
• To appreciate and understand current data-scientific problems in economics and be able to identify and formulate practically relevant questions and issues in various aspects of economics
• To apply appropriate analytic tools and techniques to resolve complex data-scientific problems in various aspects of economics using appropriately curated data, and be able to clearly communicate findings and insights gained using appropriate visualisation tools
• To cultivate in the students the practice of independent and peer learning so as to prepare them to function effectively in diverse careers as data science professionals and economists

Programme Structure

The programme provides opportunities for experiential and self-directed learning. In the industry-linked integrated courses and the capstone project, students learn from data science professionals and economists both within and beyond the formal classroom setting. Students may work on their capstone projects in certain partner institutions or companies. Interaction with data science professionals allows the students to hone their ability to ask the right questions and formulate problems, be resourceful and enterprising in their approach to data collection and analysis to problem-solve and yield insights, and sharpen their communication skills.

Admission Requirements

The admission requirements for the DSE programme are as follows:

• Singapore-Cambridge GCE ‘A’ Level qualification: A very good pass in H2 Mathematics
• International Baccalaureate (IB) Diploma: A very good pass in HL Mathematics or Mathematics: Analysis and Approaches (MAA)
• NUS High School Diploma: Very good major GPA in Mathematics
• Polytechnic Diploma from Singapore: Excellent Overall Polytechnic results with a Diploma Plus certification in Mathematics

Programme Requirements and Sample Study Plan

The requirements of the DSE programme can be found in the programme documentation. A sample study plan is also available to guide students in their course selection and progression.

Host Department

The Data Science and Economics Cross Disciplinary Programme is jointly offered by the Department of Statistics and Data Science, Department of Mathematics, and Department of Economics. This programme is hosted by the Department of Mathematics.