Program Overview

Introduction to the Data Science and Analytics Programme

The Data Science and Analytics (DSA) programme is a four-year direct Honours programme 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.

Programme Description

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 the future. The programme has several key facets:

• Interdisciplinary curriculum: A key facet is the interdisciplinary nature of the programme. Students will read courses in mathematics, statistics, and computer science, and be exposed to the interplay among these three key areas in the practice of data science.
• Deep domain knowledge: Programmes offered under the CHS have a flexible curriculum structure. By pursuing appropriate second major, major-minor, and specialisation pathways, students will gain in-depth exposure to artificial intelligence, computation and optimisation, computer algorithms, database and data processing, data mining and machine learning, and high-dimensional statistics.
• Experiential learning: Students will undertake a capstone course that is industry-driven, where they will have the opportunity to work on practical problems that are related to real-life data and workplace challenges.

Student Learning Outcomes

The student learning outcomes of the DSA programme are:

• To comprehend the conceptual and methodological foundations of analytical methods and techniques for data science, drawn from the broad disciplines of computing, mathematics, and statistics
• To appreciate and understand current data-scientific problems in engineering and sciences, government and public service, and industry at large, and be able to identify, formulate, and resolve practically relevant scientific questions and issues in these sectors and domains using appropriately curated data
• To apply, or develop and implement, appropriate analytic tools and techniques to resolve complex data-scientific problems in various sectors and domains, and be able to communicate findings and insights gained clearly 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

Industry Partnerships and Experiential Learning

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.

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.

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 found in the programme documentation.

Data Analytics and Consulting Centre

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 sources for industry projects and works 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 benefits to students involved in the project are:

• 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.
• They have access to additional faculty mentoring.