
Program Details
Visualise, summarise, and interpret biological and health data using appropriate statistical methods.
Identify and apply suitable analytical techniques to solve problems in health and biological sciences.
Demonstrate programming skills to deliver data-driven solutions for decision making.
Exhibit teamwork, leadership, and consultation skills through statistical consultancy projects.
Pursue higher studies and advanced research.
Integrated Theory and Health Sciences: We combine rigorous statistical theory with practical health sciences applications so you can solve real-world biomedical and public health problems.
Hands-on Training in Modern Tools: You gain practical exposure to R, Python, and SAS for data analysis, modelling, and research applications.
Advanced Statistical Methodologies: Strong emphasis on Bayesian statistics, predictive modelling, and stochastic processes allows you to conduct complex and data-intensive research.
Interdisciplinary Research and Industry Exposure: You bridge statistics, epidemiology, and biomedical research through consultancies, with a dedicated final-semester project and internship.

Lab Work
Well-equipped computer laboratory with 60 functional systems, Coursera-enabled learning, and a statistical consultancy unit working on real-world health datasets.
Lab Work
Well-equipped computer laboratory with 60 functional systems, Coursera-enabled learning, and a statistical consultancy unit working on real-world health datasets.



















Our meaningful collaborations with industry leaders and global universities enhance your career opportunities and higher education pathways.
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Admissions Path
Program Eligibility
You must successfully completed B.Sc. (Statistics/Mathematics/Computer Science), BE, BTech, BCA, or any other graduation or equivalent from a recognized university with 60% aggregate marks, with a minimum of two years in Mathematics/ Statistics. And complete all academic requirements (classes, examinations, and other assessments) of your undergraduate program on or before 31 July of the year of admission.
You can qualify through MAHE Merit list based on your academics.
OR
Appear for PGCUET 2026.
Curriculum and Fees
You build competencies in computational mathematics, probability, statistical inference, data management, and programming with R and Python. In the second semester, you advance into regression, Bayesian and hierarchical models, epidemiology, experimental design, stochastic processes, survival analysis, machine learning, and disease modelling.
Program Duration
Total Program Fee
General:
Total Program Fee
NRI/Foreign:
Scholarships


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