Data science, analytics and engineering
(MS, PhD)
Our data science, analytics and engineering degree is designed to produce data scientists, analysts, and engineers who can manage data and convert that data into relevant information for making decisions. Our PhD program will train scientists and engineers in development of new systems and algorithms for collecting, cleaning, storing, valuing, aggregating, fusing, summarizing, managing and drawing inferences from high dimension, high volume, heterogeneous data streams for knowledge discovery.
This degree program is a collaboration between the School of Computing and Augmented Intelligence (SCAI) and the School of Mathematical and Statistical Sciences (SoMSS). Our faculty are internationally recognized for their research, conducting many funded, state-of-the-art research projects for both government and industry. They are not only involved in leading-edge research from both methodological and applications perspectives, but they also actively advise students, teach innovation and continuously improve their curriculum.
Data Science, Analytics and Engineering (Computing and Decision Analytics), MS: This concentration in the MS program in data science, analytics and engineering provides an advanced education in high-demand data science and computing and industrial engineering. A focus on probability and statistics, machine learning, data mining and data engineering is complemented by computing and industrial engineering-specific courses to ensure breadth and depth in data science and computing and industrial engineering.
Data Science, Analytics and Engineering, PhD: The PhD program in data science, analytics and engineering engages students in fundamental and applied research as preparation for careers in academia, government or industry. The program’s educational objective is to develop each student’s ability to perform original research in the development and execution of data-driven methods for solving major societal problems. This includes the ability to identify research needs, adapt existing methods and create new methods as needed for data analytics and engineering.
The doctoral program provides a rigorous education with research and educational experiences that allow students to pursue careers in advanced research, teaching or state-of-the-art practice. Graduates demonstrate proficiency with existing methodology and significant accomplishment at advancing the state of the art in their chosen area of data science, analytics and engineering.
PhD Degree requirements
All students must take qualifying exams covering the required core courses within one year of matriculation into 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 take a data engineering or data analytics course and have it meet an elective requirement at the same time. Students will need to take a different elective course to reach the total number of credit hours required for the program. Other coursework may be used with approval of the academic unit to fulfill these requirements.
Please see the ASU Graduate Policies and Procedures for additional information.
Required core (12 credit hours)
- CSE 511 Data Processing at Scale
- CSE 543 Information Assurance and Security
- CSE 572 Data Mining or IEE 520 Statistical Learning for Data Mining or EEE 549 Statistical Machine Learning: From Theory to Practice
- IEE 670 Mathematical Statistics or STP 502 Theory of Statistics II: Inference
Other requirements (9 credit hours)
Data Engineering requirements
- CSE 510 Database Management System Implementation
- CSE 515 Multimedia and Web Databases
- CSE 546 Cloud Computing
Data Analytics requirements
- CSE 575 Statistical Machine Learning
- CSE 578 Data Visualization
- One of IEE 578 Regression Analysis, IEE 620 Optimization I, APM 523 Optimization, or EEE 598 Topic: Convex Optimization
Elective courses (39 credit hours)
Research (12 credit hours)
DSE 792 Research (12)
Culminating experience (12 credit hours)
DSE 799 Dissertation (12)
Data science, analytics and engineering, PhD: Both a written and an oral comprehensive examination are required on or before completion of the 57 credit hours of course work in the program of study. The candidate must also successfully pass the dissertation prospectus and the dissertation oral defense.
Please see the ASU Graduate Policies and Procedures for additional information.
Graduate admissions
Thank you for your interest in pursuing a graduate degree in the School of Computing and Augmented Intelligence. Here you can learn more about the admissions process and application requirements.
Deadline dates
| Program | Fall semester | Spring semester |
|---|---|---|
| Data Science, Analytics and Engineering | January 15 (PhD) | September 15 (PhD) |
Admission requirements
Applicants must fulfill the requirements of both the Graduate College and the Ira A. Fulton Schools of Engineering. Applicants are eligible to apply to the program if they have earned a bachelor’s or master’s degree in engineering, computer science, mathematics, statistics or related field, from a regionally accredited institution. Applicants must have a minimum cumulative GPA of 3.00 (scale is 4.00 = “A”) in the last 60 hours of their first bachelor’s degree program, or applicants must have a minimum cumulative GPA of 3.00 (scale is 4.00 = “A”) in an applicable master’s degree program.
For questions regarding supplemental materials, such as letters of recommendation requirements or your statement of purpose, contact [email protected]. For questions regarding the online graduate application or the status of documents, please contact Graduate Admissions.
Application requirements
Begin by visiting the Graduate Admissions website and completing the Graduate Admissions application and paying the application fee. The fee is nonrefundable and the application will not be processed until the fee is received.
In addition to completing the ASU Graduate Admissions application, the following materials must also be submitted to complete your application package:*
U.S. Residents:
- One set of official transcripts from every college and university attended, including ASU, unless the student graduated from ASU
- Official GRE test scores.** Click here for the average GRE scores for applicants. The ASU institution code is: 4007. If a department code is required use: 000.
- Three letters of recommendation
- Statement of purpose
International Applicants:
- Academic credentials (all international records must be submitted in the original language accompanied by an official English translation). If you have attended a U.S. institution, one set of official transcripts from every college and university attended, except ASU.
- Official GRE General test scores taken within the last five years.** Click here for the average GRE scores for applicants. The ASU institution code is: 4007. If a department code is required use: 000.
- Official TOEFL score, taken within the last two years (please see ASU’s English Proficiency requirements). The TOEFL score must be valid on the first day of class for the term the student is applying for. SCAI requires that TOEFL scores must be above 575 (paper), or 90 (iBT). We also accept IELTS with a minimum overall band scores of 7.0 or the Pearson Test of English (PTE) with a minimum score of 65 or higher. Please see the Graduate Admissions website for TOEFL deadline dates. The ASU institution code is: 4007. If a department code is required use: 000.
- Three letters of recommendation
- Statement of purpose
The required materials should be mailed to:
| If sending by stamped mail: Admission Services Applicant Processing Arizona State University PO Box 871004 Tempe, AZ 85287-1004 |
If sending by FedEx, DHL or UPS: Arizona State University Admission Services Applicant Processing 1150 East University Drive Building C, Room 226 Tempe, AZ 85281 |
Please include the document reference number on all materials sent. Applications are not evaluated until all required documents have been received.