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Master of Science in Data Science & Statistics

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Master of Science in Data Science & Statistics

Course Introduction

The Master of Science in Data Science and Statistics is designed to equip students with advanced statistical, computational, and analytical skills required to extract meaningful insights from complex data.

This interdisciplinary program blends theory, practical applications, and research, preparing professionals capable of data-informed decision-making across academia, industry, and government sectors.

Eligibility Requirements
  • A Bachelor’s Degree or a Bachelor’s Honours Degree in Science or a related field from a recognized University, equivalent to SLQF Level 5 or 6, with a minimum of 30 credits in Statistics, Mathematics, Computer Science, or related disciplines, OR
  • Any other qualification deemed equivalent, as accepted by the Senate of the University of Ruhuna upon the recommendation of the Board of Study in Science and the Faculty Board of Graduate Studies.

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Course Details

  • Duration:
    MSc by Dissertation - 2 Years
    MSc by Coursework - 1 Year

  • Medium: English

  • Course structure :
    This program combines theoretical instruction with practical experience. Students will learn foundational and advanced concepts through lectures and apply them in hands-on lab sessions using real-world datasets.

    Through guided exercises, students will gain proficiency in statistical software and programming languages such as R and Python for data analysis, modeling, and visualization.

    The hybrid learning mode integrates both in-person and online delivery (60% face-to-face: lectures, computer labs, and seminars / 40% online: lectures, access to materials, assignments, and discussions at students’ convenience. Online components include lectures on basic concepts, ensuring that students can grasp theoretical foundations before engaging in advanced practical sessions.

  • Weekend Programme

  • Venue : Department of Mathematics

  • SLQF :
    MSc by Dissertation - SLQF 10
    MSc by Coursework - SLQF 9

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