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Data Science, Analytics and Engineering (Computing and Decision Analytics), MS

Learn the data science skills needed for the modern economy while enhancing your expertise in computing and industrial engineering. Take high-demand courses and work with colleagues to solve client-driven data science problems.

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Students present a project on a laptop at a showcase in ASU's Data Science, Analytics and Engineering (Computing and Decision Analytics), MS degree.

Quick facts

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 is 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 computing and decision analytics concentration in the Master of Science program in data science, analytics and engineering provides you with an advanced education in high-demand data science, as well as 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 you have a breadth and depth across data science and these engineering disciplines.

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:
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)

Students choose one:
CSE 511 Data Processing at Scale (3)
CSE 512 Distributed Database Systems (3)
IFT 530 Advanced Database Management Systems (3)

Students choose one:
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)

Concentration (12 credit hours)
Students complete one course in each of the following areas:
data analysis (3)
data assurance and security (3)
machine learning (3)
optimization (3)

Electives (3 or 6 credit hours)

Culminating Experience (3 or 6 credit hours)
CSE, IEE or SER 599 Thesis (6)
FSE 570 Data Science Capstone (3)

Additional Curriculum Information
Students should consult the academic unit for a list of approved electives and concentration course requirements.

Courses selected for the required core or concentration may not be used as elective coursework for the same plan of study. Students should consult with their academic advisor to ensure that the total number of credit hours in their plan of study equals 30.


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 are eligible to apply to the program if they 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:

  1. graduate admission application and application fee
  2. official transcripts
  3. written statement
  4. professional resume
  5. proof of English proficiency

Additional Application Information
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.

Before applying to the MS program, students are required to have completed three semesters or nine credit hours of Calculus I, II and III, and it is recommended that students complete a discrete mathematics course.

Students assigned any additional admission requirements upon admission must complete those courses with a grade of "B" (scale is 4.00 = "A") or higher within two semesters of entering the program. Additional admission requirements courses include:

  • CSE 310 Data Structures and Algorithms
  • IEE 380 Probability and Statistics for Engineering Problem Solving
  • MAT 242 Elementary Linear Algebra

The applicant's undergraduate GPA and depth of preparation in computer science and engineering are the primary factors affecting admission.

Application deadlines

Fall
Session Modality Deadline Type
Session A/C In Person 12/31 Priority*
Spring
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.


Explore expanded study opportunities

This program allows you to obtain both a bachelor's and a master's degree in as little as five years. As a high-achieving student, accelerated bachelor's plus master's degree programs are designed for you to share undergraduate coursework with graduate coursework to accelerate completion of your master's degree. These programs feature the same high-quality curriculum taught by ASU's world-renowned faculty.

This program is offered as an accelerated bachelor's plus master's degree with:

Undergraduate advisor
Elizabeth Wood
480-965-3199
SCAI.4+1@asu.edu
Graduate advisor
Wendy Biresch
480-965-3199
SCAI.4+1@asu.edu
General contact
480-965-3199
Learn more about this program
Undergraduate advisor
Elizabeth Wood
480-965-3199
SCAI.4+1@asu.edu
Graduate advisor
Wendy Biresch
480-965-3199
SCAI.4+1@asu.edu
General contact
480-965-3199
Learn more about this program
Undergraduate advisor
Elizabeth Wood
480-965-3199
SCAI.4+1@asu.edu
Graduate advisor
Wendy Biresch
480-965-3199
SCAI.4+1@asu.edu
General contact
480-965-3199
Learn more about this program

Approval to pursue the accelerated master's is typically granted during the junior year of your bachelor's degree program. If you are interested, you can learn more about eligibility requirements and how to apply.

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 recieve financial aid, which can reduce out-of-pocket costs.

Get an estimate

Career opportunities

Computing and industrial engineers with a background in data science can pursue opportunities in a variety of fields to manage and analyze data, and extract knowledge from large data sets for decision-making, including in the following industries:

  • consulting
  • data and analytics management
  • data engineering
  • information systems
  • manufacturing

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.

Computer Science and Engineering Program | CTRPT 105
scai.grad.admission@asu.edu
480-965-3199
Admission deadlines

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.

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