HBTU M.Sc Mathematics with Data Science: Fees 2026, Course Duration, Dates, Eligibility

Ans. The two-year programme pairs an advanced mathematics core with data-science training in programming, statistics, machine learning and applied analytics. Students take theory and laboratory courses and complete a project on real data problems. This blend is designed for the growing demand for graduates who understand both the mathematical foundations and the practical tools used in data-driven roles, making it more applied than a traditional pure-mathematics master’s. Early semesters strengthen the mathematical base while later ones add programming and modelling, so students from varied backgrounds can build the full skill set step by step.

Ans. The total fee is just INR 45,000 for the two years, among the lowest for this discipline anywhere, because HBTU is a state government university. Hostel and mess charges are separate. Domicile students from Uttar Pradesh can also claim state fee reimbursement, so the effective cost can be reduced even further, making the programme an exceptionally cost-effective route into data science. For students who want analytics skills without the high cost of a private institute, the value on offer here is hard to match.

Ans. Selection is merit-based, using the IIT JAM score first, then CUET-PG, and finally a University Entrance Test if seats remain. Candidates apply through the HBTU portal after their entrance result is declared. The programme has 38 sanctioned seats in the School of Basic and Applied Sciences, so a competitive JAM score in mathematics is the most reliable way to secure admission. Because the seat count is limited, candidates should treat IIT JAM as their primary entrance exam and keep a valid scorecard ready for counselling.

Ans. Applicants need a bachelor’s degree with mathematics as a major or as a subject studied for at least two years or four semesters, including students from computer science, statistics and IT backgrounds. A valid IIT JAM or CUET-PG score is preferred. The mathematics requirement ensures students can handle the quantitative depth of the data-science and modelling coursework. Graduates from engineering streams who studied enough mathematics also qualify, which makes the intake a mix of mathematics, science and computing backgrounds.

Ans. Graduates move into data science, analytics, statistical modelling, research and software roles that need strong quantitative skills. The applied training suits analyst and modelling positions in technology, finance and consulting firms. Those inclined towards academics can pursue a doctorate, while the low fee and practical curriculum make the programme an efficient stepping stone into the data-driven job market. The combination of rigorous mathematics and hands-on data tools is increasingly sought after for machine-learning and quantitative roles across industries.

Ans. A pure mathematics master’s focuses mainly on theory such as algebra, analysis and topology, whereas this programme keeps a strong mathematical core but adds substantial data-science content like programming, statistics, machine learning and applied projects. The aim is to produce graduates who can both reason mathematically and build practical data models. For students who want quantitative careers in industry rather than only academia, the applied orientation of this track is usually the better fit while still keeping doctoral study open as an option.