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In addition to its core mathematical rigor, the B.Sc. Mathematics (Honours with Research) is a four year degree program which offers a specialized stream in Computational Mathematics, which equips students with the skills to solve complex mathematical problems using algorithmic and numerical methods. This stream includes courses such as Computational Mathematics, Advanced Numerical Techniques, Data Structures and Algorithms, Machine Learning, Cloud Computing, and Blockchain Technologies, ensuring students are proficient in both theory and application. With hands-on exposure to programming languages like Python and tools like MATLAB or Scilab, students develop the capability to model, simulate, and analyze real-world systems. The integration of computational mathematics enhances problem-solving efficiency and prepares graduates for cutting-edge careers in data analytics, software development, quantitative finance, and scientific research.
10+2 with Science, including Mathematics as one of the subjects, with a minimum aggregate of 50% marks.
Students with a CUET / SAT (DI Code - 71057) score will be given preference in the merit list
01
This research-focused program enables students to innovate in computational mathematics, tackling advanced equations and algorithms through original theses, performance benchmarking, and conference-ready outputs for cutting-edge scientific computing.
Critical thinking and analytical reasoning: Acquire ability of critical thinking and logical reasoning and capability of recognizing and distinguishing the various aspects of real life problems.
02
Conduct investigations of complex research problems: Use research-based knowledge and research methods including design of experiments, analysis and interpretation of data, and synthesis of the information to provide valid conclusions.
03
Modern tool usage: Create, select, and apply appropriate techniques, resources, and modern scientific and IT tools including prediction and modelling to complex scientific activities with an understanding of the limitations.
04
Communication: Communicate effectively on scientific activities with the community and with society at large, such as, being able to comprehend and write effective reports and design documentation, make effective presentations, and give and receive clear instructions.
05
Environment and sustainability: Understand the impact of the professional scientific solutions in societal and environmental contexts, and demonstrate the knowledge of, and need for sustainable development.
06
Ethics: Apply ethical principles and commit to professional ethics and responsibilities and norms of the scientific practice.
07
Individual and team work: Function effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary settings.
08
Life-long learning: Recognize the need for, and have the preparation and ability to engage in independent and life-long learning in the broadest context of technological change.
Graduates will establish careers in academic research or high-performance computing, authoring 2+ publications on computational algorithms or numerical analysis.
Graduates will develop novel computational models for scientific simulations, securing funding or patents through collaborative research.
Graduates will lead research initiatives in areas like scientific computing or AI, presenting at international forums with impactful results.
Graduates will pursue PhDs or senior R&D roles, exhibiting expertise in advanced topics like parallel computing and fostering innovation in mathematics applications.
Mathematical Foundations: Understanding core concepts, principles, and techniques in computing and related mathematical foundations, enabling effective problem-solving, algorithm development, and application of computing solutions across diverse domains.
Computational Techniques: Apply computational methods and numerical algorithms using tools like Scilab, Python, R etc. to solve mathematical problems that arise in science, engineering, and technology.