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Online Master of Science in Analytics

Discover LSU’s World-Class Online Degrees

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Total Credit Hours
36

Cost Per Credit Hour
$862

Drive Decisions with Data.

LSU’s Online Master of Science in Analytics in the E. J. Ourso College of Business is offered through the Stephenson Department of Entrepreneurship & Information Systems. It prepares students to use data-driven methods to solve problems, reduce costs, increase revenues, streamline processes, and improve decision-making. Students learn specialized skills and knowledge drawn from the fields of computer science, statistics, operations research, and quality management to achieve results through a mixture of classroom instruction, hands-on exercises, and team-based projects. The MSA graduates are equipped with the skills and expertise to become leaders in top companies across all industries such as Chevron, Dow, Disney, IBM, and SAS.

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Total Credit Hours
36

Cost Per Credit Hour
$862

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Affordability

We offer a variety of ways to help you pay for your degree including financial aid, scholarships, employer tuition reimbursement, and veterans education benefits.

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Dedicated Support

Receive world-class customer service through a personal concierge from application to graduations.

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Convenience

Complete the degree 100% online and on your time while balancing work, family and other responsibilities.

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Learn From The Best

LSU’s professors are recognized as thought leaders in their fields, ensuring that the online experience is as rewarding as that of an on-campus classroom.


Explore This Program

Cost

LSU Online offers several ways to help you pay for your degree including credit for prior learning (PLA), financial aid, and veteran education benefits. Learn More.

Total credit hours per program: 36 credit hours

Cost per credit hour: $862

Total cost with fees: $31,032

Cost per credit hour and fees are subject to change. Exact fees may vary by program. Please consult an Enrollment Concierge for the final program cost.

Course Listings
  • ISDS 7024: Advanced Statistical Analysis | Credit Hours: 3
  • ISDS 4141: Introduction to Data Mining | Credit Hours: 3
  • ISDS 7070: Advanced Business Problems - Python | Credit Hours: 3
  • ISDS 7103: Survey of Operations Research – Stochastic Methods | Credit Hours: 3
  • ISDS 7301: Descriptive Analytics | Credit Hours: 3
  • ISDS 7302: Predictive Analytics | Credit Hours: 3
  • ISDS 7303: Analytics Methods | Credit Hours: 3
  • ISDS 7304: Visual Analytics | Credit Hours: 3
  • ISDS 7075: Ind Readings - Business Forecasting & Applications | Credit Hours: 3
  • ISDS 7510: Database Management | Credit Hours: 3
  • ISDS 7990: Project | Credit Hours: 6
Admission Requirements
  • 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 and graduate work already completed
  • Resume or CV
  • 1-2 page statement of how the MSA fits into your short and long-term career goals
  • GRE or GMAT required
  • 3 letters of recommendation
Career Opportunities
  • Data Analyst
  • Data Scientists
  • Management Analyst
  • Operations Research Analyst
  • Quantitative Analyst/ Modeler
  • Market Research Analyst
Equipment Requirements

The laptop requirements below are set forth so that students may not have any issue loading data or software to their machine.

  • Windows 10 Professional, Enterprise, or Education (Education is available through OnTheHub)
  • 4 Core, X64, 64 Bit processor
  • 16 GB RAM (16 recommended)
  • 500GB Hard drive
  • ATA 100/7,200 RPM hard drive is preferred but a 5,400 will work
  • A graphics card supporting higher resolution than 1024×768 (32-bit). (1 GB dedicated, non-shared, memory card is recommended.)​

By becoming familiar with the types of technologies taught in this program, students are given a head start in their field post-graduation. Apple Systems are not recommended as all software utilized in this course requires the Windows operating system. However, if you do decide to utilize an Apple computer you must have Windows (10 or higher) running prior to starting courses.​ This can be done through a partitioned hard drive or other means of split operating systems.


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