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Arizona State University Ira A. Fulton Schools of Engineering 10 courses 84 total credits
Conduct original research in data-driven methods, statistical learning and data engineering in ASU's data science, analytics and engineering degree, PhD program at Fulton Schools.
| Required Core | 12 credits |
| Electives and Additional Research | 39 credits |
| Research | 12 credits |
| Other Requirements | 9 credits |
| Culminating Experience | 12 credits |
| Total Credits | 84 credits |
Required Core
| Code | Course Title | Credits |
|---|---|---|
| CSE 511 | Data Processing at Scale | 3 |
| CSE 543 | Information Assurance and Security | 3 |
| Total Required Core | 12 credits | |
Required Core - Complete one of the following:
| Code | Course Title | Credits |
|---|---|---|
| CSE 572 | Data Mining | 3 |
| EEE 549 | Statistical Machine Learning: From Theory to Practice | 3 |
| IEE 520 | Statistical Learning for Data Mining | 3 |
Required Core - Complete one of the following:
| Code | Course Title | Credits |
|---|---|---|
| EEE 554 | Probability and Random Processes | 3 |
| IEE 670 | Mathematical Statistics | 3 |
| STP 502 | Theory of Statistics II: Inference | 3 |
Electives and Additional Research
Other Requirements
data engineering coursework or data analytics coursework
Culminating Experience
| Code | Course Title | Credits |
|---|---|---|
| DSE 799 | Dissertation | 12 |
| Total Culminating Experience | 12 credits | |
Additional Curriculum Information
All students must take qualifying exams covering the required core courses within one year of entering the program. The dissertation prospectus should be submitted and its oral defense completed no later than one year following completion of the 60th credit hour and also no later than the fourth year in the program. Students must select coursework from either the data engineering or the data analytics requirements. Students should see the academic unit for the approved course list. Students cannot use a data engineering or data analytics course to meet an elective requirement at the same time; they must take a different elective course to reach the number of credit hours required for the program. Other coursework may be used with the approval of the academic unit to fulfill these requirements. Twelve credit hours of DSE 792 Research are required, and up to 24 credit hours are allowed on the plan of study. Students with more than 12 research credit hours will apply the excess credit hours to their electives and additional research. Electives include: additional DSE 792 Research credit hours (up to 12 credit hours allowed beyond the required 12) approved elective courses, of which up to three credit hours of DSE 790: Reading and Conference are permitted, with approval All students enrolled in the PhD in Data Science, Analytics and Engineering must complete a supervised practical training experience that allows them to apply specific knowledge, research methods, and/or professional competencies in a professional setting. This experience is an integral component of the dissertation curriculum, and successful completion is required to satisfy the dissertation requirements and earn the degree. When approved by the student's supervisory committee and the Graduate College, 30 credit hours from a previously awarded master's degree can be used for this degree. If students do not have a previously awarded master's degree, the 30 hours of coursework are to be made up of electives to reach the required 84 credit hours.
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