1. Introduction and need for the programme

The B.S. in Mathematics and Computing is designed to meet the growing national and global demand for graduates who possess strong mathematical foundations and advanced computational skills. The curriculum combines foundational mathematical areas such as analysis, algebra, probability, combinatorics, and optimisation with core computing subjects including algorithms, data structures, machine learning, and database systems. The programme aims to develop graduates who can approach complex problems with mathematical clarity and computational precision.

Across industry and research sectors, there is a growing demand for professionals who possess both strong mathematical foundations and advanced computational capabilities. Fields such as finance, technology, analytics, engineering, and scientific research increasingly require individuals who can design efficient algorithms, construct reliable mathematical models, analyse large-scale data, and develop scalable systems. This evolving landscape underscores the need for a programme that places mathematical thinking at the core of computational problem-solving and prepares students for roles including quant analysts, algorithm engineers, data scientists, optimisation specialists, modelling experts, cryptography and security analysts.

The programme contrasts with other B.Tech. degrees in AI&DS and CSE by emphasising the mathematical foundations and rigour necessary for developing strong analytical and computational skill sets with broad applicability. Combined with dedicated elective verticals in Data Science, Mathematical Computing, and Scientific Computing, this programme will enable students to launch into diverse career paths. Thus, the programme aims to nurture graduates who are not only technically skilled but also analytical, ethical, and adaptive - capable of innovating across disciplinary boundaries and contributing meaningfully to the rapidly evolving technological landscape.

2. Name of the degree to be awarded and projected intake

• Name of the degree: B.S. (Mathematics and Computing)
• Projected intake: 40

3. Objectives of the program

The B.S. in Mathematics and Computing aims to fulfil the following objectives:

• Understanding core concepts: Develop graduates with strong mathematical foundations and advanced computational skills, emphasising mathematical thinking as the basis of computational problem-solving.
• Algorithmic and computational thinking skills: Translate complex real-world problems into mathematical models for analysis and optimisation.
• Industry readiness: Prepare students to build and implement robust systems for data-intensive fields, including Scientific Computing, Machine Learning, Computational Finance, and Cryptography.
• Research readiness: Equip graduates with the expertise required to drive innovation in academic and industrial research.
• Leadership: Develop entrepreneurial skills and interdisciplinary competence for leadership roles in industry and academia.

4. Graduate Attributes & Learning Outcomes:

(a) Graduate Attributes:

Graduates of the B.S. in Mathematics and Computing will:

• Demonstrate strong conceptual understanding and analytical proficiency in mathematics and computing.
• Utilise modern computational tools and technologies effectively across diverse multidisciplinary application domains using algorithmic thinking, mathematical rigour, and logical reasoning.
• Integrate data-driven and mathematical approaches for informed analysis and decision-making.
• Ability to innovate and contribute towards next-generation data-driven technology.
• Communicate complex mathematical and computational ideas clearly and collaborate effectively within diverse and interdisciplinary teams.
• Exhibit leadership, professionalism, and initiative in academia, research, and industry.

(b) Learning Outcomes:

The students have:

• Rigorous training in mathematical reasoning across analysis, algebra, probability, linear algebra, and discrete structures.
• The ability to apply the mathematical concepts for designing efficient algorithms to solve application-oriented problems, analyse their complexity, and implement their computational solutions.
• The proficiency in building and analysing mathematical models for data-driven systems using computational tools, including quantum, physical and financial systems.
• The ability to utilise optimisation techniques, statistical and machine learning approaches for data-driven decision-making.
• The ability to write technical reports, communicate mathematical and computational ideas effectively, and work ethically in teams.
• The ability to advance technological innovation and national growth by supporting Government-led initiatives like Make in India, Startup India and Viksit Bharat 2047.