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A DOCTORAL PROGRAM IN DATA SCIENCE WITH AN INTERDISCIPLINARY FOCUS.

The Doctor of Engineering (D.Eng.) degree in Data Science at ÐÔÊÓ½ç is a professional doctorate designed to offer advanced coursework in data science, as well as the ability to engage in an interdisciplinary project using data science.

Many of the problems in data science have very specific applications in industry and there are many interdisciplinary opportunities. With a D.Eng. in Data Science, you will have a significant advantage over those with a M.S. degree in getting senior-level positions in industry, government laboratories, or in academia.

The key factors that make this degree unique include the following:

• You will be able to engage in an interdisciplinary project that spans multiple semesters (18 credit hours). These can be collaborative projects with persons or organizations outside of data science.
  
  
• You will have the ability to take up to 12 credit hours in courses outside of the department. This will provide you with more domain knowledge in the field or industry you want to work in.
  
  
• You can earn industry certifications to satisfy the qualifying examination requirement of the degree. While there is no single, standard certification in the data science profession, several certifications have been created over the years by well-known companies and organizations. Earning these external credentials can make you more attractive to a potential employer. Examples include certifications by IBM and the Data Science Council of America (DASCA).
  
  
• A flexible format provides you with the ability to earn the Data Science, D.Eng. degree both online and in person.

Ph.D. Compared to D.Eng. in Data Science

If you are wondering about which degree would better fit your goals, we have summarized the key differences between the two types of degree programs:

• Ph.D. Program - A Doctor of Philosophy (Ph.D.) program focuses on scholarly research, and graduates of such degrees often aim to become researchers at universities and laboratories.
• D.Eng. Program - A Doctor of Engineering (D.Eng.) degree emphasizes application of knowledge to real-world problems, and is designed for professionals working in industry.

Program Details: Data Science, Doctor of Engineering (D.Eng.)

With a prior master’s degree in Data Science or a closely related field, a minimum of 54 credit hours are required. Students with a prior master’s degree may have foundation and core coursework requirements waived, but may still need to take prerequisite courses which are required by any advanced and elective courses.

The core curriculum for the degree consists of 24 credit hours of coursework. Advanced coursework requirement consists of an additional 24 credit hours. Students must also take 21 credit hours of elective courses, which can be any graduate course not taken previously, but non-DATA-prefixed courses must be approved by the program director. Also, courses outside of the department must be approved by the chairperson of the department that offers that course. The last 18 credit hours are courses related to the doctoral project. Students must pass a qualifying examination, get an accepted project proposal, and defend their project in front of a committee.

Without a prior master’s degree in data science or closely related field, a student must earn a minimum of 84 credit hours, but may need up to 93 credit hours depending on whether the student must take foundation courses.

D.Eng. in Data Science Program Student Learning Outcomes

• Synthesize new useful knowledge from large stores of data.
• Analyze relevant research on new data science methods and applications.
• Apply data science methodologies to solving real-world problems.
• Present findings related to the selected data-based problem.
• Incorporate solutions to ethical issues related to application of Data Science.

Unique Capstone Project

A Capstone Project is required to complete the D.Eng. degree. This is an applied project, in which data science methods are used for a real-world problem. We encourage this problem to be a service-based project, in which the student will work with non-data science faculty members, non-profit organizations, or other such entities, to make use of the latest data science techniques, leverage data, and provide a tangible benefit to the community.

The work on this project will be done over six courses. The first two will focus on the project proposal. To successfully finish these two courses, students will need to get their project proposal approved by the project committee, consisting of their instructor, a separate advisor from the ECaMS department, and one outside member. Once the project is approved, the student will take three subsequent courses that will focus on the project implementation. Finally, the last project course will focus on writing of the project report, dissemination of the results, and an oral presentation in which the project will be defended in front of the project committee.

Admission Requirements

To be fully admitted to the D.Eng. in Data Science, you must meet the following:

• A baccalaureate degree from a regionally accredited institution of higher education. A master’s degree in Data Science or a closely related field is required to waive foundation and core course requirements.
• A minimum undergraduate GPA of 3.0 on a 4.0 scale.
• A completed application for Graduate Admission.
• Professional resume.
• Official transcripts from all institutions of higher education attended.
• A two-page Statement of Purpose.
• Two Letters of Recommendation.
• Undergraduate mathematics coursework in Calculus. With regard to the Calculus requirement, note that intimate, immediate familiarity with Calculus is not expected, but students should have worked with integrals and derivatives at some point in their academic preparation.
• International students are required to have a TOEFL test score greater than 550 (computer-based 213; Internet-based 79)

Transfer of Graduate Credit

A student entering the D.Eng. program in Data Science program with appropriate prior graduate coursework in data science, which was not used as part of a previously earned graduate degree, may have a maximum of 12 credit hours applied to the D.Eng. in Data Science degree. Course credits eligible for transfer consideration must meet the following criteria:

• All transfer credit must have been earned prior to matriculation in the D.Eng. in Data Science program.
• The coursework must have been completed at a regionally-accredited graduate school.
• A minimum grade of B must have been earned for the course.
• The coursework must have an equivalent course(s) in the D.Eng. in Data Science curriculum at ÐÔÊÓ½ç.
• Courses from outside the United States will be considered if they are evaluated as graduate level by the Office of Admission or the Commission on Accreditation of the American Council on Education.
• Credit for prior learning is not awarded for graduate courses.

View the Program Curriculum

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