Master of Science in Business Analytics (MS-BA)


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  Deadline to Apply!

Begin your application today by entering the Graduate Admissions Portal. Submit your application by:

January 15 – Priority deadline for summer entry

March 1 – Final deadline for completing applications. This final deadline will be earlier for international applicants.

Applications completed after January 15 will be considered on a space-available basis. This is also the priority deadline for MS-BA applicants to be considered for competitive assistantships that provide financial assistance. This program admits only once a year, typically starting in late June and ending in early May. 

  Contact Us

Email Ambyr Dack for more information about the admissions process.

Meet Dr. Noyan Ilk, MS-BA program director.

Graduate Programs Office
  850-644-6458
   877-587-5540 (toll free)
  gradprograms@business.fsu.edu

 

Ready yourself for the growing demand.

Fortune reports that by 2030, the number of positions demanding skills in business analytics is expected to increase by 25%, significantly outpacing the nation’s average job growth. If these projections by the U.S. Bureau of Labor Statistics hold true, more than three new business analyst jobs will be created for every one post added to handle other business tasks.

The MS-BA qualifies as a Science, Technology, Engineering or Mathematics (STEM) degree, as defined by the Department of Education. This assures graduates of employer demand and allowing graduates on student visas to extend their U.S. work stay up to two years longer.

Learn to manage and leverage big data by pursuing Florida State University’s one-year, full-time Master of Science in Business Analytics (MS-BA).


  Admission Guidelines

Admission to the Master of Science in Business Analytics program is highly competitive. The decision is based on a portfolio of qualifications, including prior academic experience, work experience, optional entrance exam scores (such as GMAT or GRE) and letters of recommendation. Entrance exam scores, such as from the GMAT or GRE, are optional to submit if you feel they would strengthen your application. Any submitted test scores become part of the application and are used in the admission decision.

Prerequisites

All applicants must have a bachelor’s degree from a regionally accredited institution. Prerequisite coursework should provide a solid background in mathematics, statistics and computing. This would include: (1) at least one college-level course in calculus, (2) at least one college-level course in probability and statistics and (3) at least one college-level course in computer programming using a high-level language such as Python, R, C++, etc. Previous coursework in business is not required, but all applicants are expected to have a general knowledge of economics, finance, accounting, statistics, calculus and management principles.

  Degree Requirements

The  one-year MS-BA degree program requires students to complete 33 credit hours in three semesters. Our robust and intensive program equips students with a solid foundation in machine learning, data management, computing and quantitative methods. Students entering the program should be committed to enhancing their skills in mathematics, statistics and computer programming. This comprehensive training prepares students to be leaders in the analytics field or to apply to related Ph.D. programs. The curriculum uses a variety of mathematical, statistical and computing tools including: (1) calculus and linear algebra, (2) statistical methods (including regression and its extensions) and (3) programming and visualization (Python, SQL, Tableau, etc.)

Program Schedule

The MS-BA offers a three-semester lock-step program that is approximately one calendar year in duration. MS-BA students are required to complete 33 credit hours, which is a combination of 9 core courses (27 credit hours total), 1 elective course (3 credit hours), and 1 credit hour of professional development each semester. The typical study plan is as follows:

Summer

QMB 5616 Probabilistic Optimization for Analytics
ISM 5644 Programming for Analytics
GEB 5932 Professional Development

Fall

QMB 5755 Quantitative Methods in Business Analytics I
ISM 5136 Data Analytics and Mining for Business
ISM 5560 Data Management in Business Analytics
ISM 5565 Foundational Concepts for Business Analytics
GEB 5932 Professional Development

Spring

ISM 5419 Fundamentals of Data Visualization
ISM 5569 Business Analytics Capstone
ISM 5566 Forecasting, Revenue Management and Pricing
GEB 5932 Professional Development
Elective (1 required)

Elective course options will include applications of analytical tools in specific business disciplines, such as marketing, human resources, operations, finance or real estate. Options may include:

ISM 5567 Supply Chain Analytics
ISM #### Algorithms for Business Analytics 
MAN 5375 HR Analytics
MAR 5675 Marketing Analytics
RMI 5257 Data Analytics in Risk Management and Insurance
GEB 5944 Graduate Internship

*Note: Program requirements are subject to change. Elective availability may vary from year to year.

  Application Process

The following items should be submitted through the Florida State Graduate Application portal:

  • Applicant Statement 
  • Current resume/C.V., clearly indicating work experience including dates and positions held, noting full-time or part time employment. Management, business and leadership experience should also be clearly detailed.
  • Three (3) letters of recommendation from employers or former college professors that speak specifically to the applicant’s ability to successfully complete the MS-BA program (submitted by the recommenders in the online application)
  • Florida Residency Declaration if applicable
  • Nonrefundable application fee of $30.00 (see University Application or go to fees.fsu.edu)

The following items should be sent to the Graduate Admissions Office, 222 S. Copeland St./314 Westcott Building, Florida State University, Tallahassee, FL 32306-1410 or to graduateadmissions@fsu.edu:

  • One (1) official transcript from all colleges and universities attended (FSU transcripts not necessary for FSU alumni, students)
  • Official test scores, if applicable: GMAT or GRE scores are optional and should be submitted only if they will enhance the application. Any submitted test scores become part of the application. The code to send GMAT scores to Florida State is PN8K567, and the code to send GRE scores is 5219.

International Applicants

International applicants should visit gradschool.fsu.edu/admissions/international-admissions for information concerning financial responsibilities, degree equivalency, etc. International applicants are responsible for submitting the below documents in addition to the checklist items in the previous section.

English Language Proficiency Exam
International applicants whose native language is not English or who have not completed an undergraduate or graduate degree in an English-speaking country are required to take an English Language Proficiency exam and submit official test results in order to be admitted to Florida State University. The College of Business accepts all of the following examinations taken within the past two (2) years:

  • Test of English as a Foreign Language (TOEFL): a minimum score of 600 on the paper-based test and 100 on the internet-based test (FSU institution code 5219)
  • International English Language Testing System (Academic IELTS): minimum score of 7
  • Pearson Test of English (PTE): minimum score of 66
  • Duolingo: minimum score of 120
  • Cambridge C1 Advanced Level: minimum score of 180
  • Michigan Language Assessment: minimum score of 55

Transcript Evaluation Requirement
The Office of Graduate Admissions requires all international students to submit an official course-by-course evaluation of all academic records from non-U.S. institutions prior to application review. (This verifies degree equivalency and serves in place of additional official or unofficial transcripts.) This evaluation must be done by a member of the National Association of Credential Evaluation Services (NACES): www.naces.org. FSU now offers a partnership with SpanTran, our preferred credential evaluation service, which allows a streamlined process at a discounted rate. More information about this process is available after you submit the first part of your graduate application.

  Program Costs

ESTIMATED PROGRAM COSTS FOR THE 2024-2025 ACADEMIC YEAR

The MS-BA program requires 33 credit hours:

  • Florida residents: $479.32 (tuition plus fees) per credit hour. Total estimate program cost is $15,817.56.
  • Non-Florida Residents: $1,110.72 (tuition plus fees) per credit hour. Total estimate program cost is $36,653.76.

Note: Costs do not include required books and supplies for courses and are subject to change. Fees in table do not include some per-term flat fees for FSUCard and facilities use. For a breakdown of on-campus student fees and their explanations, visit the university’s Tuition Rates page.

Learn more about why our graduate programs are considered A Smart Choice in Value.

Read more about the college’s financial assistance options for graduate students.

You may also visit Florida State's financial aid website for more information on types of financial aid.

  Course Descriptions

GEB 5944 Graduate Internship
This internship offers a working and learning experience in the business industry. S/U grade only. Three credit hours, on campus.

ISM 5136 Data Analytics and Mining for Business
This course will provide a managerial overview of the state of art technologies and techniques that are used to discover rich and existing patterns for generating business value, i.e. “business intelligence” for organizations.

ISM 5419 Fundamentals of Data Visualization
This course covers the tools and techniques needed to properly express the results of descriptive, predictive, and prescriptive analytical procedures. Students focus on identifying and applying the best methods and tools for a particular analytical question and dataset to produce a successful visualization.

ISM 5560 Data Management in Business Analytics
This course will discuss various data-related issues in business analytics and introduce the best practices, underlying principles, and emerging technologies in data management. Specifically, the course will cover 1) foundational data management concepts, 2) best practices in managing big data, and 3) unstructured data management.

ISM 5565 Foundational Concepts for Business Analytics
The primary objective of this course is to prepare graduate students in the Business Analytics graduate program with foundational tools and techniques used in subsequent courses.  The primary (but not exclusive) focus will be on achieving and understanding of the role of applied probability methods in business analytics.

ISM 5566 Forecasting, Revenue Management & Pricing
This course explores how big data can be used for understanding and analyzing customer demand and behavior. First, the class surveys the canonical uses of data to analyze consumer demand — time-series forecasting. There will be a focus on Exponential Smoothing and ARIMA models. Then, we explore the idea that sales is not the same as demand.

ISM 5567 Supply Chain Analytics
This course examines the role that Business Analytics can play in the context of an organization's Operations and Supply Chain functions. The goal of this course is to develop critical skills in the management of Supply Chains.

ISM 5569 Business Analytics Capstone
This course is designed for students in Business Analytics to demonstrate that they have achieved the learning goals established by the program regarding descriptive, predictive, and prescriptive data analysis. Upon completion of ISM 5569, students should be able to analyze real world data with consideration of practical concerns. Specifically, this course is to provide students with an advanced level of analytical skills that will enable them to examine business problems by developing models, analyzing alternatives, and recommending solutions using techniques and tools they have learned in previous Business Analytics courses.

ISM 5644 Programming for Analytics
This is an introductory course intended to introduce students to the basics of computer programming for business analytics. The course will place special emphasis on utilizing Python programming language for data science and analytics related tasks.

ISM #### Algorithms for Business Analytics
This course is an in-depth study of fundamental algorithms employed in business analytics.

MAN 5375 HR Analytics
The course focuses on the analysis and application of a company’s HR data to uncover insights that inform HR strategies, process changes, and investments – with the goal of improving organizational performance (i.e., driving business outcomes). Students will learn about theory and research regarding drivers of employee performance, retention, and engagement, as well as the critical HR metrics that are important for business outcomes.

MAR 5675 Marketing Analytics
The practicing marketing scientist must necessarily have a lot of tools in the toolbox. However it is difficult to learn these tools since they have been adopted from a large number of other fields; like psychology, economics and sociology; each with its own notation. This course then will serve as a survey of the Marketing Analytics field, reducing your startup cost to using the techniques needed by the practicing marketing scientist, and to show how marketing analytic techniques feed into the strategic marketing process and business decision-making in general.

QMB 5616 Probabilistic Optimization for Analytics
This course teaches students techniques to address problems in regression, discriminant analysis, principal component analysis, logistic regression, SEM, etc. Students will utilize methods such as calculus and linear algebra.

QMB 5755 Quantitative Methods in Business Analytics I
This course focuses on deterministic methods of prescriptive analytics.

RMI 5257 Data Analytics in Risk Management and Insurance
In this course we will focus on the use of data and analytical tools in the insurance industry. We will develop a set of tools for analyzing the types of data used by insurers across various functions including loss estimation, loss reserving, underwriting, and claims. Topics will include exploring traditional and new sources of data, legal and ethical considerations, and challenges associated with forecasting and making inferences in the context of risk and uncertainty.