Lovely Professional University

M.Sc (Data Science) at Lovely Professional University

Lovely Professional University (LPU) is one of the leading educational institutions in India, known for its diverse range of undergraduate, postgraduate, and professional courses. The M.Sc. (Data Science) program offered by LPU is an advanced degree designed to equip students with the essential skills and knowledge required to excel in the field of data science. With the exponential growth of data in various industries, the demand for qualified data scientists is higher than ever. This course is designed to meet that demand, providing students with both theoretical and practical knowledge to analyze and interpret complex data, a crucial skill in today’s data-driven world.

M.Sc (Data Science) Fees Structure 

The course fee for the M.Sc (Data Science) program at Lovely Professional University is designed to be affordable while maintaining the quality of education. Below is the detailed fee structure:

The fee is subject to revision, and students should check the official LPU website or contact the admissions office for the most up-to-date fee information. Scholarships and financial assistance may be available for eligible students.

Eligibility Criteria for M.Sc (Data Science) 

To be eligible for admission to the M.Sc. (Data Science) program at LPU, candidates must meet the following criteria:

Candidates who meet these eligibility criteria are invited to apply for the program.

M.Sc (Data Science) Course Curriculum

The curriculum of the M.Sc. (Data Science) program at Lovely Professional University is designed to provide a comprehensive understanding of the core areas of data science, along with practical experience in handling real-world data. The course covers various aspects of mathematics, statistics, machine learning, and data analysis tools. Below is a breakdown of the key subjects that are included in the program.

The program focuses on building both theoretical knowledge and practical skills, providing students with an opportunity to work on real-life projects, case studies, and internships.