MS in Analytics

Louisiana State University

Baton Rouge, Louisiana, USA
MS in Analytics
Duration12 Months
LevelMasters Program
  • The Master of Science in Analytics (MSA) at LSU is designed to prepare students to use data-driven methods to contribute to organizational effectiveness and guide decisions
  • The STEM-designated program curriculum emphasizes the use of business analytics, business intelligence, and information technology to solve problems, reduce costs, increase revenues, streamline processes, and improve decision-making
Fees componentsAmount
Tuition & fees2224225 INR
Hostel & Meals549300 INR
Insurance199799 INR
Books and Supplies63865 INR
International Student Service Charg7324 INR
Total820288 INR

Entry Criteria

Class 12thNo specific cutoff mentioned
Bachelors3.0 GPA
  • Applicants must hold a bachelor's degree from an accredited U.S. college or university or its foreign equivalent with a minimum GPA of 3.0 on all undergraduate
  • There are no official prerequisites required to apply. However, previous coursework including mathematics, statistics, engineering, science, computer programming, business, and economics is necessary to be successful. The program is suitable for recent graduates and experienced professionals

ExamsTOEFL: 79

IELTS: 6.5

PTE: 59

GRE: Accepted

GMAT: Accepted
  • The scores must be with a balance between the verbal and quantitative sections

Additional info
  • Chances of gaining admission are better if applicants have any of the following:
    • An undergraduate degree in a field that is very relevant to the MSA degree and shows successful completion of courses in statistics or mathematics. Some examples include any engineering degree, computer science, management science, most other sciences, operations research, production/operations management, economics, statistics, mathematics or industrial/organizational psychology
    • A high GPA (3.5 or higher)
    • GRE or GMAT test scores in the top 25 percent
    • Work experience in business intelligence, business analytics, data mining, data warehousing, database management, computer science, programming, web development, web analytics, risk management, and related fields
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