Jul 25, 2025  
2025-2026 Graduate Catalog 
    
2025-2026 Graduate Catalog

Data Science, PhD


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Students completing the Ph.D. in Data Science will demonstrate competency in the core concepts and techniques of data science, which come from both computer science and statistics. At BGSU, students will develop appropriate techniques to analyze structured, unstructured, or dynamic datasets, understand the principles of analytical methods, and articulate the strengths and limitations of analytical methods. Students will learn the skills needed to communicate effectively with technical and non-technical audiences. The program is designed to identify and respond to ethical concerns with the provenance and use of data while developing new techniques for the analysis of complex datasets.

Learning Outcomes

Upon completion of the doctoral degree, students in the Data Science program are expected to be able to:

  • Demonstrate competency in the core concepts and techniques of data science, which come from both computer science and statistics.
  • Demonstrate the ability to use or develop appropriate techniques to analyze structured, unstructured, or dynamic datasets.
  • Demonstrate an understanding of the principles that underlie analytical methods, to articulate the strengths and limitations of analytical methods, and to defend choices to use some methods over others.
  • Demonstrate the ability communicate effectively to technical and non-technical audiences orally, in writing, and with effective visualization.
  • Demonstrate the ability to identify and respond to ethical concerns with the provenance and use of data.
  • Demonstrate the ability to develop new techniques for the analysis of complex datasets or real-time modeling and decision-making, or extend existing techniques to novel and challenging datasets.
  • Demonstrate the ability to organize data using tools appropriate to the problem, code new techniques in the appropriate computer language, optimize for performance and scalability, and distribute new tools to the data science community in a usable form.

Admission Requirements

Master’s degree in Science in Mathematics, Statistics, Computer Science, Data Science, or a closely related field is preferred. Those admitted without sufficient background may be asked to complete the MS in Data Science program first. 

Additional Documents required:

  • Three Letters of Recommendation  from faculty or professionals who know you well
  • Resume
  • Statement of Purpose

International applicants are required to submit scores from the Test of English as a Foreign Language (TOEFL), the International English Language Testing System (IELTS), or the Pearson Test of English Academic (PTEA). Successful completion of ELS 112 will also be accepted for this requirement. 

Additionally, Duolingo test scores will be accepted for applications through Summer 2025. Applicants of the Graduate College who have completed a previous degree (associate, bachelor’s master’s or doctorate) from a U.S. college/university or are from a country (click here for a complete list) in which instruction was delivered in English (and attended the university for at least two years) are exempt from providing these test scores.

Application Requirements

Admissions Categories and Grade Point Average Requirements

International Application Information

Degree Requirements

Curriculum Requirements


Electives (24 credits)


Choose 8 additional courses with at least 2 from Computer Science (CS), at least 1 from Mathematics (MATH), and at least 1 from Operations Research/Statistics (OR/STAT). Courses taken from the listed core requirements that are not counted toward a core requirement may be used as electives; at most 3 starred (*) courses may be counted as electives.

Applied Data Science Experience (3 credits)


Satisfy this requirement by getting Graduate Coordinator approval for a data science related internship or campus job, or joining a research group on campus. Document the experience by registering for 6 credit hours of internship, co-op, or directed readings credit.

Culminating Experience (16 credits)


Minimum Total Credits (60 credits)


Additional Requirements


  • Minimum 3.0 graduate cumulative grade point average
  • Maximum of 10 credits of 5000-level coursework may be counted toward degree requirements
  • Preliminary Examination 
  • Minimum of  16 credits of dissertation research (maximum of 30 credits of dissertation research are applicable to degree requirements)
  • Dissertation Defense and Publication of Manuscript on OhioLINK
  • All requirements must be completed within eight years from the end of the earliest course used to fulfill degree requirements.

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