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PGP in Data Science
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Course Mode
Offline
Duration
1.5 to 2-year
Eligibility
A bachelor's degree in any discipline with a minimum aggregate of 50-60% marks (varies by institution). A strong background in mathematics or statistics is often preferred. Some programs may also require prior knowledge of programming languages like Python or R.
Entrance Exam
CAT (Common Admission Test) XAT (Xavier Aptitude Test) CMAT (Common Management Admission Test) GMAT (Graduate Management Admission Test) University-specific aptitude tests like Praxis Admission Test (PAT)
Type of Course
PG
Course Summary
A Post Graduate Program (PGP) in Data Science is a specialized, industry-focused program designed to equip professionals and graduates with the skills needed to analyze and interpret complex data. The curriculum is typically practical, with an emphasis on hands-on learning, projects, and case studies. Key areas covered include statistics, machine learning, deep learning, data visualization, and programming languages like Python and R. This program is ideal for individuals with a strong background in mathematics, engineering, or computer science who want to transition into a career in the fast-growing field of data science. It provides a quick and effective pathway to a high-demand profession.
📅 Upcoming Admission Deadlines
- pgp-in-data-science with 50% scholarship August 28, 2026
Top Recruiters
Accenture
Amazon
Wipro
TCS
Career Scope
Network Engineer
Electric Engineer
Frontend Engineer
Software Developer
Web Developer
College-wise Fees
Frequently Asked Questions
A PGP (Post Graduate Program) in Data Science is a rigorous, comprehensive academic program designed to train individuals in the principles and practices of data science, including advanced machine learning and AI. It covers foundation and advanced courses to equip students with the skills of full-stack data scientists and AI architects.
Key skills include Programming (using languages like Python or R), Statistics and Probability, Data Manipulation and Analysis, Machine Learning and Deep Learning techniques, and Data Visualization. A strong understanding of these concepts is vital for a data scientist to extract meaningful insights from large datasets.
PGP programs prepare students by providing a deep understanding of data science principles, teaching them how to approach new problems, from problem definition to data analysis and interpretation. They learn to apply methods from statistics, computer science, and mathematics to extract knowledge from data, building models and making predictions to solve real-world business problems.