Ph.D. in Data Science

The Ph.D. in Data Science program will provide the essential skills required to analyze big and complex data sets and equip students with a broad understanding of data challenges and opportunities, along with the research and inquiry skills necessary to independently conduct research and answer questions within their area of concentration.

To meet this goal, courses in the Ph.D. in Data Science Program curriculum are organized around interdisciplinary focal areas in computer science, engineering, mathematics, and statistics. Courses offered within this framework include traditional lecture-style, e-learning, and special topics courses that introduce students to the latest theories, methods, and emerging issues; seminar series; and experiential learning through thesis research, (directed independent study and internship programs). Through this framework, students will gain proficiency in the application of scientific principles such as, critical thinking, experimental design, data preprocessing and wrangling, data visualization, advanced statistical learning/data mining and machine learning, as well as a sense of professional and technical writing, and reporting, responsibility, and integrity.

Curriculum

Students possessing a bachelor's degree will be required to complete a minimum of 72 semester hours of graduate-level work. Students possessing a master’s degree in a related field will be required to complete a minimum of 42 semester hours of graduate-level work beyond their master's degree in addition to meeting other Ph.D. requirements. Up to 30 of the credits earned in pursuit of your master's degree may be transferable to the Ph.D. program as either core courses or elective courses.

To maintain Minimum Satisfactory Academic Progress in and to successfully graduate from this program, students must:

Earn no more than two total C grades of any combination of “C+” or “C.” (C- grades are not acceptable.)
Earn no grades lower than a “C”
Earn an official cumulative GPA (according to matriculation level) of at least 3.000 on Rowan’s 4.000 scale
Successful completion of Qualifying Exam & Successful defense of research thesis dissertation.

The following courses make up the Ph.D. in Data Science.

8-10 Courses / 72 Semester Hours
- Required Courses: 21 Semester Hours
- Elective Courses: 21-30 Semester Hours
- Research Courses: 21 Semester Hours
Foundation Courses: No
Graduation / Exit / Thesis Requirements: Yes

Course Number | Title | S.H. (Credits)
---|---|---
Required Courses: 21 S.H.
CS 02516 | Big Data Tools and Techniques | 3
MATH 01505 | Probability and Mathematical Statistics I | 3
STAT 02515 | Applied Multivariate Data Analysis | 3
| Take one of the following: |
CS 07556 | Machine Learning I | 3
ECE 09555 | Advanced Topics in Pattern Recognition | 3
| Take one of the following: |
MATH 03511 | Operations Research I | 3
ENGR 01511 | Engineering Optimization | 3
| General Coursework (both required) |
XEED 01601 | Effective Teaching in Academic, Corporate and Gov’t Settings | 3
ECE 09702 | Strategic Technical Writing and Winning Grant Proposals | 3
Elective Courses: 21-30 S.H.
CS 02505 | Data Mining I | 3
CS 02530 | Advanced Database Systems: Theory and Programming | 3
CS 02605 | Data Mining II | 3
CS 02620 | Data Warehousing | 3
CS 02625 | Data Quality and Web/Text Mining | 3
CS 02630 | Advanced Topics in Database Systems | 3
CS 07540 | Advanced Design and Analysis of Algorithms | 3
DS 02510 | Visual Analytics | 3
DS 02695 | Advanced Topics in Data Science | 3
ECE 09558 | Reinforcement Learning | 3
ECE 09560 | Artificial Neural Networks | 3
ECE 09566 | Advanced Topics in Systems, Devices, and Algorithms in Bioinformatics | 3
ECE 09568 | Discrete Event Systems | 3
ECE 09585 | Advanced Engineering Cybersecurity | 3
ECE 09586 | Advanced Portable Platform Development | 3
ECE 09595 | Advanced Emerging Topics in Computational Intelligence, Machine Learning and Data Mining | 3
ECE 09655 | Advanced Computational Intelligence and Machine Learning | 3
MATH 01506 | Probability and Mathematical Statistics II | 3
STAT 02510 | Introduction to Statistical Data Analysis | 3
STAT 02511 | Statistical Computing | 3
STAT 02514 | Decision Analysis | 3
STAT 02525 | Design and Analysis of Experiments | 3
STAT 02530 | Applied Survival Analysis | 3
STAT 02585 | Introduction to Bayesian Statistical Methods | 3
Thesis Coursework: 21-30 S.H.
DS 02799 | Doctoral Research and Dissertation | 3

Admission Requirements

The following is a list of items required to begin the application process for the program. There may be additional action or materials required for admission to the program. Upon receipt of the materials below, a representative from the Rowan Global Admissions Processing Office will contact you with confirmation or will indicate any missing items.

Completed Application Form
$65 (U.S.) non-refundable application fee
Bachelor’s degree (or its equivalent) in Mathematics, Statistics, Computer Science, Computational Science, Data Science or related field from an accredited institution of higher learning. Applicant should have taken courses in Probability & Statistics, Data Structures, Multivariate Calculus, and Linear Algebra and should have proficiency in programming languages commonly used in data science, such as Python, R, and/or SQL.
Official transcripts from all colleges attended (regardless of number of credits earned)
Current professional resume. Applicants should include a statement on the professional resume that verifies evidence of applied skills including research proficiency.
Typewritten statement of professional objectives and research interests
Three letters of recommendation. Applicants with Master's degrees completed within the past 5 years should include as one of their recommenders an instructor (or MS thesis advisor) from their Master's program.
Students recommended by a Rowan Thesis advisor who is willing to do research with the student may waive one or more of the requirements above.
Students who do not meet the entrance requirements for the Ph.D. program may be admitted into the Master’s program. Upon completion of the Master’s degree, exceptional candidates can apply to transfer into the Ph.D. program. Students successfully transferred into Ph.D. program will be able to count all their Master’s courses towards satisfying the Ph.D. program requirements.
Minimum undergraduate cumulative GPA of 3.5 (on a 4.0 scale)
Graduate committee may conduct interviews with shortlisted candidates to further assess their suitability for the Ph.D. program

Deadlines, Tuition and Financial Aid

Entry Terms & Deadlines Tuition Financial Aid

The chart below details available entry terms for the Ph.D. in Data Science program as well as corresponding application deadlines. Submitting the Application Form is only the first step to beginning the admission process. All of the required materials listed above must be received on or before the application completion deadline for your desired entry term to be considered for admission to that term. We encourage you to complete the application form and begin submitting your materials at least one month before the deadline indicated.

Entry Term | Application Deadline
---|---
Fall | July 1
Spring | November 1

To view the tuition rate for this program please click the button below to visit the Bursar's website.

Rates

We know paying for tuition can be a challenge. That is why Rowan provides students with the financial resources needed to put their education first by offering grants, loans, work-study, and scholarships.

More Info

Program Outline

Degree Overview:

The Ph.D. in Data Science program at Rowan University aims to equip students with the skills to analyze large and complex datasets. The program provides a broad understanding of data challenges and opportunities, along with the research and inquiry skills needed for independent research. The curriculum is interdisciplinary, drawing from computer science, engineering, mathematics, and statistics. The program incorporates various teaching methods, including traditional lectures, e-learning, special topics courses covering the latest theories and methods, seminar series, and experiential learning through thesis research, directed independent study, and internship programs. Students will develop proficiency in scientific principles such as critical thinking, experimental design, data preprocessing and wrangling, data visualization, advanced statistical learning/data mining, and machine learning. The program also emphasizes professional and technical writing, reporting, responsibility, and integrity.

Outline:

The Ph.D. program requires a minimum of 72 semester hours for students with a bachelor's degree and 42 semester hours for students with a related master's degree (up to 30 master's credits may transfer). The curriculum is structured around required courses, elective courses, and research courses.

Required Courses (21 Semester Hours): These include Big Data Tools and Techniques (CS 02516), Probability and Mathematical Statistics I (MATH 01505), Applied Multivariate Data Analysis (STAT 02515), one course from (CS 07556 Machine Learning I or ECE 09555 Advanced Topics in Pattern Recognition), and one course from (MATH 03511 Operations Research I or ENGR 01511 Engineering Optimization).
Elective Courses (21-30 Semester Hours): A wide range of electives are offered, including courses in data mining, database systems, advanced algorithms, visual analytics, advanced topics in data science, reinforcement learning, artificial neural networks, bioinformatics, cybersecurity, and various statistics courses (Probability and Mathematical Statistics II, Introduction to Statistical Data Analysis, Statistical Computing, Decision Analysis, Design and Analysis of Experiments, Applied Survival Analysis, and Introduction to Bayesian Statistical Methods).
Research Courses (21 Semester Hours): These primarily consist of Doctoral Research and Dissertation (DS 02799), with the number of credit hours varying depending on the research undertaken.

Assessment:

To maintain satisfactory academic progress and graduate, students must:

Earn no more than two total C grades (C+ or C).
Earn no grades lower than a C.
Achieve a cumulative GPA of at least 3.000.
Successfully complete a Qualifying Exam.
Successfully defend their research thesis/dissertation.

Teaching:

The program utilizes a variety of teaching methods, including traditional lectures, e-learning, special topics courses, seminar series, and experiential learning opportunities such as thesis research, directed independent study, and internships.

Other:

Students with a bachelor's degree in Mathematics, Statistics, Computer Science, or a related field from an accredited institution with a minimum GPA of 3.0 are eligible.
Students who don't meet Ph.D. entrance requirements may be admitted to the master's program, with the possibility of transferring to the Ph.D. program upon completion.
A checkpoint at the end of the first year of the Master's program allows for transfer to the Ph.D. program if a 3.3 GPA with no grade lower than a B is achieved.
The program offers Fall and Spring terms for international students.

About University

PhD

Masters

Bachelors

Courses

Rowan University

Overview

Rowan University, located in Glassboro, New Jersey, is a nationally recognized public research institution known for its innovation, academic excellence, and commitment to student success. With a diverse range of undergraduate and graduate programs in engineering, business, sciences, and more, Rowan offers a dynamic, hands-on learning environment that prepares students for global careers.

Rowan warmly welcomes international students, providing dedicated support services, cultural engagement programs, and a vibrant campus community. From application guidance to visa support and international student orientation, Rowan ensures a smooth transition and enriching experience for students from around the world.

Academic Programs

Rowan University offers a diverse range of academic programs, including:

Art (Visual and Performing)
Biological/Biomedical Sciences
Bioinformatics
Business (Accounting, Advertising, Management, Marketing)
Computer Science
Cyber Security
Data Science
Education
Engineering (Chemical, Civil, Electrical, Mechanical)
Humanities & Social Sciences
Mathematics
Pharmaceutical Sciences
Psychology
Public Relations/Strategic Communications

Colleges & Schools

The university is organized into various colleges and schools, each specializing in specific academic areas:

William G. Rohrer College of Business
Ric Edelman College of Communication & Creative Arts
College of Education
Henry M. Rowan College of Engineering
College of Humanities & Social Sciences
College of Performing Arts
College of Science & Mathematics
School of Earth & Environment
Rowan-Virtua School of Osteopathic Medicine (Rowan-Virtua SOM)
Rowan-Virtua School of Translational Biomedical Engineering & Sciences
School of Innovation & Entrepreneurship
Graduate School of Biomedical Sciences

Health & Safety

Rowan University prioritizes the safety and well-being of its students, faculty, and staff through a comprehensive approach to campus security. The Rowan University Department of Public Safety operates 24/7, providing emergency response, crime prevention, and safety education. Through various measures, Rowan University offers a secure learning environment to ensure that students can focus on their education with peace of mind. Key safety measures include:

Rowan Alert System – A real-time notification system for emergencies, weather alerts, and important campus updates.
Emergency Blue Light Phones – Strategically placed across campus to provide direct communication with Public Safety.
Rowan Guardian App – A mobile app that allows students to contact emergency services, send safety alerts, and use a virtual escort feature.
Police and Security Patrols – Campus is monitored by sworn police officers and security personnel to ensure a safe environment.
Card Access Control – Residence halls and many academic buildings require Rowan ID card access to enhance security.
Safety Escorts – Available for students needing assistance traveling on campus at night.
Self-Defense and Safety Training – Public Safety offers personal safety workshops and self-defense training programs.

Housing Options

Rowan University features nine residence halls and six apartment communities in Glassboro, New Jersey. University and affiliated residences provide easy access to campus resources, recreational facilities and social opportunities. Rates vary depending on the residence hall. You can read more here.

Student Life

Rowan University provides a vibrant campus life with opportunities for students to engage in various activities. Students can participate in various sports and recreational activities, including intercollegiate athletics and intramural sports. Additionally, students can enjoy various entertainment and cultural events on campus. Some services, activities and clubs specificly for international students include:

International Student Advisors
Intensive English Language Program
Graduate Student Association
International Club
Cricket Club
El Circulo de Español
The Asian Cultural Association
The Muslim Student Association
Indian Student Association
International Education Week
International New Student Orientation
Iranian Student Association
Tax Services
Writing Workshops
Job Fairs
Trips to Surrounding Cities
& More!

Well-Being Resources

Rowan University understands that international students may face unique mental health challenges, including homesickness, cultural adjustment, and language barriers. That is why Rowan is committed to ensuring that international students feel supported, connected, and at home while studying in the U.S. To support their well-being, the university offers specialized resources tailored to their needs. Key Mental Health Support for International Students include:

Counseling & Psychological Services (CPS) – Provides free, confidential counseling, including individual therapy and support for cultural adjustment, loneliness, and stress management.
International Student Support Groups – Safe spaces where international students can share experiences, discuss challenges, and build friendships.
Let’s Talk Program – Drop-in counseling sessions with therapists, offering informal support for homesickness and emotional concerns.
International Student Services – Provides guidance and cultural integration programs to help students adjust to life in the U.S.
Thrive at Rowan – Mental well-being initiatives that offer mindfulness sessions, stress-relief workshops, and self-care strategies.
Multicultural Events & Clubs – Student organizations and cultural programs that help international students connect with peers and celebrate their heritage.
24/7 Crisis Support – Access to an emergency hotline and on-call counselors for urgent mental health concerns.

Student Success

Rowan University is dedicated to helping students succeed academically by offering a variety of resources and support services. These programs provide tutoring, mentorship, study skills development, and other tools to help students reach their full potential. Key Academic Support Services:

Academic Advising – Each college and school provides academic advisors to help students choose courses, plan their academic path, and stay on track for graduation.
Tutoring Services – Free tutoring is available through the Academic Success Center, offering one-on-one and group tutoring for various subjects.
Writing Center – Helps students improve their writing skills through personalized feedback on essays, research papers, and other assignments.
Mathematics Learning Center – Offers specialized support for students needing help with math courses.
Library & Research Assistance – Campbell Library provides extensive research resources, librarian assistance, and quiet study spaces.
Office of Accessibility Services – Supports students with disabilities by providing academic accommodations and assistive technology.
Success Coaching – Provides personalized coaching to help students with time management, study strategies, and academic planning.
First-Year Experience Program – Helps first-year students transition to college life with academic support, mentorship, and community-building activities.
Honors Program & Research Opportunities – Offers enriched coursework, faculty mentorship, and research projects for high-achieving students.

International

The university has a strong international focus with programs and opportunities for students. International-Focused Programs & Opportunities:

International Student Services – Offers visa support, orientation programs, and cultural integration assistance to help international students transition smoothly into academic and social life at Rowan.
Study Abroad Programs – Provides students with the opportunity to study in various countries through exchange partnerships and faculty-led trips.
English Language Programs (ELP) – Helps non-native English speakers improve language skills through intensive English instruction and academic preparation.
Multicultural & International Student Organizations – A variety of student-led groups celebrate different cultures, promote diversity, and build global connections on campus.
International Research Collaborations – Opportunities for students to participate in global research projects in fields like engineering, business, and environmental science.
Internships & Career Services for International Students – Support in navigating work opportunities, internships, and Optional Practical Training (OPT) for international students seeking career growth in the U.S.
Global Speaker Series & Cultural Events – Regular events featuring international scholars, cultural festivals, and global discussions to encourage cross-cultural learning.

Total programs

324

Admission Requirements

Entry Requirements:

For the Ph.D. in Data Science program at Rowan University, applicants need a Bachelor's degree (or equivalent) in Mathematics, Statistics, Computer Science, Computational Science, Data Science, or a related field from an accredited institution. A minimum undergraduate cumulative GPA of 3.0 (on a 4.0 scale) is required. Applicants should have completed coursework in Probability & Statistics, Data Structures, Multivariate Calculus, and Linear Algebra. Proficiency in programming languages commonly used in data science (Python, R, and/or SQL) is also necessary. A current professional resume demonstrating applied skills and research proficiency is required, along with a typewritten statement of professional objectives and research interests. Three letters of recommendation are needed; applicants with Master's degrees completed within the past 5 years should include a recommender from their Master's program (instructor or thesis advisor). Students recommended by a Rowan Thesis advisor willing to conduct research with them may have some requirements waived. All Master's coursework will then transfer. A minimum cumulative MS GPA of 3.3 with no grade lower than a B is needed to transfer at the end of the first Master's year. International students must submit proof of English language proficiency during the application process. Students with scores too low may be offered conditional admission, allowing them to participate in the English Language Program to improve their skills before entering the university.

Student Stories

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