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BSc in Computational Mathematics

Overview

Mathematics is the rigorous study of structure and relationship. As such, it is fundamental to all of the sciences and Engineering, as well as being an intellectually challenging and fulfilling field of science in its own right. It trains students in analytical thinking and courses are offered with applications to natural as well as social sciences. Mathematics and computing are intertwined, and affect people’s lives in ways one might not expect. Mathematics is a driving force behind many of today’s advancement in Medicine, Economics, Business and Science & Technology. The solid mathematical knowledge and computational skills you acquire at KU will give a competitive edge in a wide variety of careers and prepare you to contribute to the next generation of innovations.

  • Course Info

    Affilation Kathmandu University (KU)
    Duration 4 Years
    Institute Type College
    Average Fees Incurred NPR 820,000
    Employment Roles

    Data Analyst 

    Computational Mathematician 

    Research Scientist

    Statistician
    Placement Opportunities

    Research Institutions 

    IT Companies 

    Financial Institutions 

    Government Agencies

  • Admission Criteria

    Candidates are required to appear for Kathmandu University Common Admission Test (KUCAT) and will be offered admission based on rank in KUCAT result in all merit seats and in the quota seats. The admission test will be conducted in the mode of Computer-Based Test (CBT) as described in the KUCAT CBT Information.

  • Salient Features

    Comprehensive Mathematical Foundation: In-depth exploration of fundamental mathematical concepts.
    Programming Integration: Learning programming languages for mathematical modeling and analysis.
    Numerical Methods Application: Applying numerical techniques to solve mathematical problems.
    Computational Linear Algebra: Utilizing linear algebra in a computational context.
    Real-world Mathematical Modeling: Developing mathematical models for practical problem-solving.
    Probability and Statistics Emphasis: Understanding statistical methods and probability theory.
    Optimization Techniques Application: Applying optimization methods in mathematical problem-solving.

  • Eligibility

    10+2 (or equivalent) examinations with minimum of 50% marks in aggregate and 50% in Physics, Chemistry and Mathematics (PCM) or Physics, Mathematics and Computer Science (PMCs). 

  • Curricular Structure

    Mathematical Foundations: In-depth study of fundamental mathematical concepts.
    Programming for Mathematics: Learning programming languages for mathematical modeling and analysis.
    Numerical Methods: Application of numerical techniques to solve mathematical problems.
    Linear Algebra and Differential Equations: Study of linear algebra and differential equations in a computational context.
    Mathematical Modeling: Developing mathematical models for real-world problems.
    Probability and Statistics: Understanding statistical methods and probability theory.
    Optimization Techniques: Applying optimization methods in mathematical problem-solving.

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