Welcome to Kennesaw State University's Masters in Data Science and Analytics program, a distinguished academic program designed to prepare future leaders in the field of data-driven innovation. Launched in 2006 and led by a dedicated team of experienced faculty who are experts in their fields, this program offers a comprehensive and hands-on approach to data science education. Emphasizing a balance between theoretical knowledge and practical applications, students are equipped with the skills needed to navigate the evolving landscape of data science successfully. The program fosters a collaborative and supportive learning environment, ensuring that graduates emerge as adept problem solvers ready to tackle the complex challenges inherent in the world of data science and analytics. 

Austin Brown, Director, Master of Science in Data Science and Analytics

Austin Brown

About the Master of Science in Data Science and Analytics

The Master of Science in Data Science and Analytics (MSDSA) program at Kennesaw State University is a dynamic 36-semester-hour graduate degree designed to prepare a diverse student body for successful careers in data science and analytics. This comprehensive program focuses on providing essential knowledge, techniques, and tools through hands-on experiences and collaboration with faculty integrating real-world data into courses. Key program features include:

  • Analytical Programming Proficiency: Mastery of essential programming languages such as R, Python, and SAS, ensuring readiness for the evolving workforce.
  • Corporate Collaboration: Direct collaboration with leading companies each semester through sponsored project courses, providing practical, real-world experience. Past sponsors include Equifax, Travelers, Southern Company, IHG, Shaw Flooring, Truist Bank, Spanx, Atlanticus, and Coke One North America.
  • Distinctive Capstone Options: A range of capstone experiences, including internships, applied research projects, collaboration with faculty on research initiatives, and participation in a Center for Data Science and Analytics-sponsored lab. The emphasis on effective communication and presentation skills sets graduates apart in job searches.

Incoming MSDSA Student FAQs

 

Data Science and Analytics Master's Curriculum

MSDSA Course Roadmap

Program Requirements

Required Courses (12 Credit Hours):

  • STAT 7010 - Mathematical Statistics I
  • STAT 7020 - Statistical Computing and Simulations
  • STAT 7100 - Statistical Methods
  • STAT 7210 - Applied Regression Analysis

Select one from the following (3 Credit Hours):

  • STAT 7125 - Design and Analysis of Human Studies
  • STAT 7220 - Applied Experimetal Design

Select at least two from the following (6 Credit Hours):

  • STAT 7125 - Desing and Analysis of Human Studies (if not selected above)
  • STAT 7220 - Applied Experimental Design (if not selected above)
  • STAT 7225 - Applied Longitudinal Data Analysis
  • STAT 7240 - Applied Data Mining or STAT 8240 - Data Mining I (credit will not be awarded for both)
  • STAT 7310 - Applied Categorical Data Analysis
  • STAT 8220 - Time Series Forecasting
  • STAT 8320 - Applied Multivariate Data Analysis
  • STAT 8330 - Applied Binary Classification

Required Project (6 to 9 Credit Hours):

Minimum of 6 credit hours are required. Students can take any of the courses here multiple times for credits. But maximally 9 credit hours can be applied for the degree. A written report (a project proposal, a project status update, or a final project report) is required by the end of each semester when any amount of the credits are taken. 

  • STAT 7916 - Cooperative Education
  • STAT 7918 - Internship
  • STAT 7940 - Applied analysis Project

Electives (6 to 9 Credit Hours):

Any other 7XXX or 8XXX courses with a DATA or STAT prefix may be used to complete the degree requirements. Courses from other graduate programs (IT, CS, SWE, IS) may be used with approval of the graduate program director. 

Note: up to nine hours may be substituted with the permission of the Program Director. 

Program Total - 36 Credit Hours

 

Course Forecast

Every Semester

  • STAT 7010 -  Mathematical Statistics I
  • STAT 7020 - Statistical Computing and Simulation
  • STAT 7100 - Statistical Methods
  • STAT 7210 - Applied Regression Analysis
  • STAT 7220 - Applied Experimental Design
  • STAT 7900 - Applied Analytics Project Course

Fall Semester

  • STAT 7110 - Quality Control & Process Improvement (Even Numbered Years)
  • STAT 7130 - Programming in R
  • STAT 7235 - Applied Longitudinal Data Analysis (Even Numbered Years)
  • STAT 7240 - Applied Data Mining
  • STAT 7310 - Applied Categorical Data Analysis (Odd Numbered Years)

Spring Semester

  • STAT 7120 - Advanced SAS Programming
  • STAT 8220 - Applied Time Series Analysis (Even Numbered Years)
  • STAT 8320 - Applied Multivariate Data Analysis (Odd Numbered Years)
  • STAT 8330 - Applied Binary Classification
  • DS 7140 - Python for Data Science

As Needed

  • STAT 7125 - Analysis of Human Studies
  • STAT 7916 - Co-Operative Experience
  • STAT 7918 - Internship
  • STAT 7940 - Applied Analysis Project

Admission Requirements and Application

Requirements for Admissions Apply Now View Program Course Catalog

Frequently Asked Questions (FAQ)

  • The depth of understanding of statistics depends on a basic knowledge of calculus. The focus of this program is to develop graduates that have in-depth knowledge of the techniques they will be using. "Plugging into" formulas or computer a routine is not the objective. This approach will enable students to develop meaningful careers and be in demand in the marketplace.
  • No. A complete submission will include the online application, a current resume, all college transcripts, and all international requirements, if applicable. Optional application materials may include, but are not limited to, a recent GRE score report (but not a subject test), a statement of purpose or at least two letters of recommendation. Statements of interest and recommendation letters provide an opportunity for us to get to know you better through your application.  Each component of the application provides critical information about you as a potential student in the program.
  • Yes, you can substitute up to 9 credit hours from other graduate programs with permission from the program director.
  • The entry degree for most positions requiring statistical training is the Master of Science degree. A recent Bureau of Labor Statistics report indicated that 18% of the country's statisticians work for the federal government, 16% for state and local governments and the remainder for private industry. University-based statisticians are a relatively small percentage. Thus, a large percentage of Data Science and Analytics graduate students will likely be placed in the private sector.
  • Yes. We do offer GTA/GRA positions. Calls for GTA applications go out to accepted students at regular intervals in the year as we prepare for each new term. GRA calls go out sporadically as the opportunities arise. Varying levels of support and tuition waivers are available depending on the number of hours one works. Graduate Assistantship Tiers - Graduate College Assistantships. In addition, financial aid and loans are available.
  • No. There is no requirement to take any American Society for Quality certification test. At the end of the first year, students will be ready to take the Green Belt exam and can do so if they choose. At the end of the program, students will have covered the Body of Knowledge for the Black Belt exam. MSDSA is unique in that the Body of Knowledge is addressed for both exams within the MSDSA courses.
  • You will leave this program with skills that you can immediately use in the workplace or to go out and get a job. Our eleven Ph.D. statisticians have knowledge and experience in a wide range of applied settings.      
  • No. We admit students only in the fall and spring terms. 
  • Yes.  Proof of mathematics through Calculus II will be required for the completion of the MSAS program.  However, this proof is not required to apply.  In the past, we have offered conditional acceptances into the program which allows one to get started completing the calculus sequence beginning in the summer term and while taking some courses in the program. This is especially useful if one is looking to change careers to data science from a degree program that did not require calculus.   It is strongly recommended that one completes Calculus II prior to the start of their second year.
  • Yes, this program accepts new students in the spring and fall.
  • Yes. The university provides on-campus housing at both our Kennesaw and Marietta campuses. There is also off campus student housing within a mile of the campus - most of which is on the bus line for the university.
  • Yes. MATH 1190 (Calculus I), MATH 2202 (Calculus II) and MATH 3260 (Linear Algebra) are offered every semester. These would prepare students for the calculus part of the program. Courses in the Minor in Data Science and Analytics (STAT 3010, STAT 3120, STAT 3130, STAT 4120 and STAT 4210) would help students prepare for the statistics part of the program. These are not requirements for admission to the program.
  • Yes. We have introductory pathways into the MSDSA program for career changers.
  • For current tuition costs, visit KSU's Graduate Tuition and Fees page.
  • Graduates of universities outside the United States must be able to document that their degree is the equivalent of a four-year bachelor's degree awarded by an accredited United States college or university. For more information, visit KSU's Graduate College - Admissions for International Students webpage