Nov 21, 2024  
2024-2025 Graduate Catalog 
    
2024-2025 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


Required Courses (20 credits)


1. Computer Science core. Select one sequence (6 credits) from:

or

2. Statistic score courses: Select one sequence (6 credits)

or

3. Other courses. Select 4 courses from:

 

Electives (21 credits)


1. Computer science elective. Select 2 courses from: CS 5170  CS 5200  CS 5620  CS 6010  CS 6170  CS 6200  CS 6260  or DATA 6260  CS 6500  or DATA 6500 CS 6630  CS 6800  (Applied Learning Data) CS 7200  or DATA 7200  CS 7300  or DATA 7300

2. MATH elective. Select 1 from: MATH 6410  MATH 6420  MATH 6440  MATH 6460  MATH 6470  MATH 6480  MATH 6490  MATH 6570  MATH 6710  MATH 6720  MATH 6820  MATH 7450  MATH 7460  

3. STAT/OR elective. Select 1 course from:OR 6610  OR 6620  STAT 5020  STAT 5160  STAT 6300  STAT 6340  STAT 6440  STAT 6750  

4. Additional electives. Take at least 9 credits. Select from:CS 5170  CS 5200  CS 5620  CS 6010  CS 6170  CS 6200  CS 6630  CS 6800   (Applied Learning Data) MATH 6410  MATH 6420  MATH 6440  MATH 6460  MATH 6470  MATH 6480  MATH 6490  MATH 6570  MATH 6710  MATH 6720  MATH 6820  MATH 7450  MATH 7460  OR 6610  OR 6620  STAT 5020  STAT 5160  STAT 6300  STAT 6340  STAT 6440  STAT 6750  

 

At most, 3 of the following courses listed above may be counted toward the degree: CS 5200; CS 5620; CS 6010; MATH 6410; MATH 6420; OR 6610; OR 6620; STAT 5020; STAT 5160; STAT 6440; MATH 6820 with topics in STAT and advisor approval 

Other Requirements (3 credits)


Satisfy this requirement by getting graduate coordinator pre-approval for an internship, professional position, or research group. Document the experience by registering for 3 credit hours of internship, directed readings, or a similar course. 

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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