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Computing and Emerging Technology

Data Science Colleges

Statistics, programming, data management, visualisation, machine learning, analytics, governance and decision support.

B.E./B.Tech, B.Sc., integrated degrees, M.E./M.Tech, M.Sc., certificates and doctoral study

Compare exact programmes, interdisciplinary laboratories, faculty specialisations, projects, internships, fees, admission routes and outcomes.

Data Science Colleges in India

Data Science is offered through engineering, science, statistics and online or integrated formats. The table below gives examples for programme exploration, not a ranking. Applicants must confirm the current title, delivery mode, eligibility, fees and admission route.

Institution or groupProgramme pattern to verify
Delhi Technological UniversityFive-year integrated MSc Data Science route; verify the current entrance and counselling process
BITS Pilani DigitalOnline MSc Data Science and Artificial Intelligence for eligible graduates; verify mode and academic requirements
Dr D Y Patil Arts, Commerce and Science College, PuneBSc Data Science route with subject-specific Class 12 conditions
Symbiosis Skills and Professional University, PuneBSc Data Science route; Mathematics or Statistics and selection conditions should be checked
Visvesvaraya Technological University affiliated collegesBE/BTech or CSE Data Science programmes at participating colleges
Galgotias UniversityMSc Data Science route for eligible graduates
Sarala Birla UniversityMSc Data Science route; confirm current eligibility and fee structure
Thapar Institute routeUndergraduate Data Science and AI offering; verify current degree title and admission conditions

Candidates must verify present approval, intake, campus and degree title through official sources. A programme listed in an earlier cycle may change its name, fee or seat count.

College evaluation checklist

Curriculum: Look for statistics, probability, linear algebra, programming, SQL, databases, visualisation, machine learning, data engineering and ethics.

Faculty: Review qualifications, teaching areas, stability and project supervision.

Laboratories: Check computer availability, dataset access, statistical and development software, cloud resources, licences and maintenance.

Projects: Examine whether students build original work, use version control, document testing and participate in technical clubs.

Internships: Ask how internships are obtained, what roles students perform and whether academic credit is monitored.

Placements: Seek branch-specific placement counts, role types, median compensation and recruiter history.

Cost: Calculate tuition and living expenses for the full duration.

Infrastructure that matters

A strong department needs reliable laboratories, adequate computing capacity, legal statistical and development software, fast internet, appropriate cloud or distributed-computing access and project space. Libraries should provide recent books and digital resources.

Equipment alone does not prove quality. Students need regular access, capable instructors and assignments that require genuine use.

Related courses

Closely related choices include Computer Science Engineering, Artificial Intelligence and Data Science, Artificial Intelligence and Machine Learning, Big Data Analytics, Statistics, Applied Mathematics, Business Analytics and Computer Engineering.

Students should avoid selecting a specialisation only because it is fashionable. A broad Data Science or CSE foundation can provide flexibility, while a specialisation is useful when it retains core computing subjects and has suitable faculty.

Continue your Data Science research

Course at a Glance

  • Course AreaComputing and Emerging Technology
  • Study PathwaysB.E./B.Tech, B.Sc., integrated degrees, M.E./M.Tech, M.Sc., certificates and doctoral study
  • Primary FocusStatistics, programming, data management, visualisation, machine learning, analytics, governance and decision support.

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