Program Description

Kennesaw State University’s Ph.D. with a major in Data Science and Analytics is an advanced degree, which trains individuals to translate large, structured and unstructured, complex data into information to improve decision-making, and become independent researchers. This highly interdisciplinary curriculum includes heavy emphasis on programming, machine learning, artificial intelligence, data mining, statistical modeling, and the mathematical foundations to support these concepts. The program also emphasizes communication skills, data ethics, and application of results to business and research problems. Graduates can pursue a position in the private or public sector as a “practicing” Data Scientist or a position within academia, where they are uniquely qualified to teach the next generation of data scientists.

Program Student Learning Outcomes

Students who successfully complete this program will be able to:

1. Apply, analyze, and synthesize foundational concepts from graph theory, combinatorics, machine learning, big data analytics, and statistical data mining on effective problem-solving, advanced data analysis, algorithmic application, or methodology development.
2. Design, conduct, and manage original research that advances data science methodologies and contributes new knowledge to the field.
3. Develop professional skills to manage or collaborate on research with a profound understanding of ethical considerations in data collection, analysis, and dissemination.

 This program is a part of the College of Computing and Software Engineering .

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Admissions, Enrollment, and Graduation Criteria

Admissions Criteria

The following are program-specific criteria beyond the general Graduate Admissions  requirements. To be considered for admission to this program, the following application materials must be submitted to the KSU Graduate Admissions Office:

• GRE Score Report - Minimum Quantitative score is 160 and a Preferred Analytical Writing Score of 3.5.
• Resume or CV
• Statement of Intent describing how this degree facilitates your career goals. 
• Three Letters of Recommendation  
  • At least one must be from an academic source.
  • At least one must be from a source outside of the academic community.  
• Successful completion of Math courses through Calculus II 
• Proficiency in at least one analytical programming language (e.g., Python, SAS, R).

Admission Criteria for Unique Cases

Currently, there are no exceptions to the admission requirements.

Transfer Credit

No credit from outside institutions is accepted for this degree program.

Enrollment Criteria

This program does not have specific enrollment criteria; however, students are expected to meet the requirements of Academic Policy 4.0 ACADEMIC STANDING, DISMISSAL, & REINSTATEMENT .

Graduation Criteria

Each student is expected to meet the requirements outlined in Academic Policy 5.0 PROGRAM REQUIREMENTS & GRADUATION .

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Program Course Requirements