Bachelor of Science (Honours) With Major in Data Science and Analytics

by NUS Business School, National University Of Singapore Claim Listing

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 are

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img Duration

4 Years

Course Details

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:

  • 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

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.

  • 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.
  • 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.
  • Central Branch

    Mochtar Riady Building 15 Kent Ridge Drive, Central

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