The Bachelor of Science (B.Sc.) programme in MSTCS (Mathematics, Statistics, and Computer Science) is a comprehensive three-year undergraduate degree structured across six semesters. The programme is designed to provide students with a strong interdisciplinary foundation in mathematical reasoning, statistical analysis, and computer programming, preparing them for careers in data-driven and technology-oriented fields.

This course integrates the core principles of mathematics, statistical methods, and computer science to develop analytical thinking, computational skills, and problem-solving abilities. Students gain in-depth knowledge in areas such as algebra, calculus, probability, statistical analysis, programming, database management, and software development, enabling them to understand complex data structures and computational systems.

The curriculum emphasizes both theoretical learning and practical application through laboratory work, programming assignments, statistical analysis projects, and research-based activities. In the fifth semester, students undertake Skill Enhancement Courses (SECs) that strengthen their technical and analytical competencies while improving employability skills. The sixth semester is dedicated to internships, research projects, or industry-oriented training that provide hands-on exposure and bridge the gap between academic knowledge and real-world applications. The programme is carefully designed to address the growing demand for professionals skilled in data analysis, computing technologies, statistical modelling, and information systems. By combining mathematics, statistics, and computer science, the course equips students with the quantitative and technical expertise required in modern industries.

Graduates of B.Sc MSTCS can pursue diverse career opportunities in data analytics, software development, information technology, financial analytics, research organizations, and business intelligence sectors. The programme also provides a strong academic foundation for higher studies in Computer Science, Data Science, Artificial Intelligence, Statistics, Mathematics, and related technological disciplines.