Data Science, Analytics and Engineering (Sustainable Engineering and Built Environment), MS
Learn the data science skills needed for the modern economy while enhancing your expertise in sustainable engineering and the built environment. You'll take high-demand courses and work with colleagues to solve client-driven data science problems.
Quick facts
Locations
Credits
Additional facts
STEM-OPT extension eligible: Yes
International students (F1) can extend U.S. work experience by 24 months.
Accreditation
Accredited by the Higher Learning Commission.
Degree description
Data scientist is consistently ranked among the top jobs in the U.S., and there's an increasing need for all engineers to make use of data science tools such as statistics, machine learning, artificial neural networks and artificial intelligence. Yet the majority of engineering occupations require subject matter expertise beyond data science.
The Master of Science program in data science, analytics and engineering with a concentration in sustainable engineering and the built environment provides you with an advanced education in this high-demand area. A focus on probability and statistics, machine learning, data mining and data engineering is complemented by sustainable engineering and built environment-specific courses to ensure breadth and depth in data science and sustainable engineering and the built environment.
Curriculum
This graduate degree includes courses focused on a specialized topic, so you can advance your skills for further professional opportunities. Explore all courses below.
30 credit hours and a thesis, or
30 credit hours including the required capstone course (FSE 570)
Required Core (9 credit hours) Students choose one: Students choose one: Concentration (9 or 12 credit hours) Electives (6 or 9 credit hours) Culminating Experience (3 or 6 credit hours) Additional Curriculum Information Courses selected for the required core or concentration may not be used as elective coursework on the same plan of study. Students should check with their academic advisor to ensure that the total number of credit hours in their plan of study is equal to 30.
Students choose one:
DSE 501 Statistics for Data Analysts (3)
EEE 554 Probability and Random Processes (3)
HSE 530 Intermediate Statistics for Human Systems Engineering (3)
STP 501 Theory of Statistics I: Distribution Theory 3 (3)
CSE 511 Data Processing at Scale (3)
CSE 512 Distributed Database Systems (3)
IFT 530 Advanced Database Management Systems (3)
CSE 572 Data Mining (3) or DSE 572 Data Mining (3)
CSE 575 Statistical Machine Learning (3)
EEE 549 Statistical Machine Learning: From Theory to Practice (3)
IEE 520 Statistical Learning for Data Mining (3)
IFT 511 Analyzing Big Data (3)
MAE 551 Applied Machine Learning for Mechanical Engineers (3)
STP 550 Statistical Machine Learning (3)
CEE 501 Artificial Intelligence for Civil Engineers (3)
two or three additional courses from an approved list
CEE/CON/EVE 599 Thesis (6)
FSE 570 Data Science Capstone (3)
Students should consult the academic unit for a list of approved electives and concentration course requirements.
Admission requirements
Here are the admission and application details
All students are required to meet general university admission requirements.
U.S. applicants (opens in new window) | International applicants (opens in new window) | English proficiency (opens in new window)
Applicants must fulfill the requirements of both the Graduate College and the Ira A. Fulton Schools of Engineering. Applicants must have earned a bachelor's or master's degree in computing, engineering, mathematics, statistics, operations research, information technology or a 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 a minimum cumulative GPA of 3.00 (scale is 4.00 = "A") in an applicable master's degree program. Applicants are required to submit: Additional Application Information All applicants must demonstrate relevant coursework or experience in the following three areas: In addition, applicants without an undergraduate degree in computer science, computer engineering, software engineering, information technology, industrial engineering, operations research, statistics or a related computing field must show evidence (in their professional resume) of at least one of the following certifications or equivalent experience:
An applicant whose native language is not English must provide proof of English proficiency regardless of current residency by scoring at least 4 on the Internet-based TOEFL (iBT) or a score of 80 if taken before January 21, 2026, in a testing center, 6.5 on the IELTS or 105 on the Duolingo English test.
Application deadlines
| Session | Modality | Deadline | Type |
|---|---|---|---|
| Session A/C | In Person | 12/31 | Priority* |
| Session | Modality | Deadline | Type |
|---|---|---|---|
| Session A/C | In Person | 07/31 | Priority* |
*A priority deadline means that applications submitted and completed before the priority deadline will receive priority consideration. Applications submitted after the priority deadlines will be reviewed in the order in which they were completed and on a space-available basis. An application is complete after all materials are received by Admission Services.
Paying for college
Use our calculator to estimate your full-time or part-time tuition fees for this program prior to any financial aid. Keep in mind that most of our students receive financial aid, which can reduce out-of-pocket costs.
Get an estimateCareer opportunities
Civil, environmental, sustainable or construction management engineers with a background in data science can pursue opportunities in a variety of fields. They manage and analyze data and extract knowledge from large data sets for decision-making in industries that include:
- building
- construction
- environmental remediation
- transportation
- water treatment
Contact information
Use the contact information below to get in touch if you're a current student or have general questions.
Prospective students should fill out the Request for Information form.
School of Sustainable Engineering & Built Envirnmt
|
HLMK 437
sebe.advising@asu.edu
480-965-0595
Frequently asked questions about degree programs
Accelerated programs allow students the opportunity to expedite the completion of their degree.
Accelerated master's
These programs allow students to accelerate their studies to earn a bachelor's plus a master's degree in as few as five years (for some programs).
Each program has requirements students must meet to be eligible for consideration. Students typically receive approval to pursue the accelerated master's during the junior year of their bachelor's degree program. Interested students can learn about eligibility requirements and how to apply.
Concurrent degrees allow students to pursue their own personal or professional interests, earn two distinct degrees and receive two diplomas. To add a concurrent degree to your existing degree, work with your academic advisor.
Joint programs, or jointly conferred degrees, are offered by more than one college and provide opportunities for students to take advantage of the academic strengths of two academic units. Upon graduation, students are awarded one degree and one diploma conferred by two colleges.
ASU adds new programs to Degree Search frequently. Come back often and look for the "New Programs" option.
ASU Online offers programs in an entirely online format with multiple enrollment sessions throughout the year. See https://asuonline.asu.edu/ for more information.
The Western Regional Graduate Program (WRGP) provides a reduced tuition rate to non-resident graduate students who qualify. Visit the WRGP/WICHE webpage for more information: https://graduate.asu.edu/wiche.
