M.Sc. Statistics (Data Science & Health Analytics)

The M.Sc. Statistics (Data Science & Health Analytics) program is designed to provide students with a strong foundation in statistical theory, data science techniques, and applications in health analytics. The program integrates statistics, machine learning, and biostatistics to equip students with the analytical and computational skills required to extract meaningful insights from complex health and biomedical data.

With the rapid expansion of digital health systems, electronic health records, genomic data, and large-scale epidemiological datasets, there is a growing demand for professionals who can apply statistical and data science methodologies to improve health outcomes and support evidence-based decision-making.

Health analytics is an interdisciplinary field that combines statistical modeling, data management, machine learning, and epidemiological methods to analyze health data, understand disease dynamics, evaluate healthcare interventions, and support public health planning. This program emphasizes both theoretical foundations and practical analytical skills, enabling students to work with real-world data and interpret results within a meaningful public health context.

The curriculum provides comprehensive training in statistical inference, predictive modeling, big data analytics, machine learning, survival analysis, epidemiological methods, and health data management. Students will also gain hands-on experience with key analytical tools, including advanced MS Excel, R, Python, SQL, Java, and data visualization platforms. Through applied coursework, case studies, and project-based learning, students develop the ability to handle large and complex datasets from healthcare systems, clinical trials, and population health studies.