DSU Bangalore M.Sc. Data Science FAQs
Ques. What is the fee for M.Sc. Data Science at DSU Bangalore?
Ans. The M.Sc. Data Science at DSU Bangalore has a total fee of INR 3,04,000 for the 2-year programme (INR 1,52,000 per year). Verify the current fee at dsu.edu.in or DSU admissions office before applying.
Ques. What is the eligibility for M.Sc. Data Science at DSU?
Ans. B.Sc. (Statistics / Mathematics / Computer Science / IT) or BCA or B.Tech / B.E. with minimum 50% aggregate is required for M.Sc. Data Science at DSU. Admission is through Karnataka PGCET 2026 or DSAT 2026. Candidates must confirm their eligibility at dsu.edu.in.
Ques. What entrance exam is required for M.Sc. Data Science at DSU?
Ans. M.Sc. Data Science at DSU Bangalore accepts scores from Karnataka PGCET 2026 or DSAT 2026. Karnataka PGCET is conducted by KEA (Karnataka Examinations Authority). DSAT is DSU’s own aptitude test conducted throughout the year.
Ques. What career opportunities are available after M.Sc. Data Science from DSU?
Ans. Graduates can work as data scientists, data analysts, machine learning engineers, business intelligence consultants, and analytics managers at technology firms, banks, consulting organisations, and data-driven enterprises. Professionals with this specialisation are in demand across technology, banking, consulting, and enterprise sectors. Industry certifications and practical project experience strengthen employment prospects further.
Ques. What does the M.Sc. Data Science curriculum cover at DSU?
Ans. DSU’s M.Sc. Data Science covers statistical learning, machine learning, deep learning, data wrangling, Python, R, SQL, big data platforms, data visualisation, and applied analytics. The programme blends theory with hands-on project work using real industry datasets, preparing students for analytics and data science roles in technology firms, banking, consulting, and data-driven enterprises. The programme is structured to prepare students for industry roles and higher studies. Practical labs and project assignments provide applied learning alongside theoretical coursework.


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