Data Science, Analytics and Engineering, MS
Learn the data science skills needed for the modern economy in this unique master's degree program while enhancing your expertise in your chosen engineering or mathematics field. Take high-demand courses and work with your colleagues to solve client-driven data science problems.
Quick facts
Locations
Credits
Additional facts
STEM-OPT extension eligible: No
International students (F1), this program is not eligible for the STEM-OPT extension.
Accreditation
Accredited by the Higher Learning Commission.
ASU is not currently accepting applications for this program. Applicants interested in the MS program in data science, analytics and engineering should apply directly to one of the concentrations: computing and decision analytics, electrical engineering, materials science and engineering, or sustainable engineering and built environment.
Degree description
Data scientists are consistently ranked among the top jobs in the USA, and there is an increasing need for all engineers to make use of data science tools like statistics, machine learning, artificial neural networks, artificial intelligence and data mining. Yet, the majority of engineering occupations require subject matter expertise beyond data science.
The MS program in data science, analytics and engineering enables students to receive an advanced education in high-demand data science and an engineering field in an integrated program. A core curriculum in probability and statistics, machine learning, and data engineering is complemented by concentration-specific courses to ensure breadth and depth in data science and a core engineering discipline.
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) Choose one from the following: Elective (15 or 18 credit hours) Culminating Experience (3 or 6 credit hours) Additional Curriculum Information
DSE 501 Statistics for Data Analysts (3), EEE 554 Probability and Random Processes (3), HSE 530 Intermediate Statistics for Human Systems Engineering (3) or STP 501 Theory of Statistics I: Distribution Theory 3 (3)
CSE 511 Data Processing at Scale (3), CSE 512 Distributed Database Systems (3) or 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)
FSE 570 Data Science Capstone (3)
CSE, IEE or SER 599 Thesis (6)
Students should consult the academic unit for a list of approved electives.
What you'll learn
The following learning outcomes highlight some of the knowledge and skills you'll develop to support your future success.
- Apply technical tools including emerging concepts in machine learning and data science to the analysis of large heterogeneous data sets.
- Create solutions to real engineering problems.
- Apply concepts in machine learning and data science to applications in their selected concentration.
Apply technical tools including emerging concepts in machine learning and data science to the analysis of large heterogeneous data sets.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 they must have 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 the professional resume) of at least one of the following certifications or equivalent experience: Applicants who have obtained a bachelor's degree from an ABET-accredited program at a U.S.-based college or university are not required to take the GRE.
An applicant whose native language is not English must demonstrate proficiency in the English language by scoring at least 90 on the TOEFL iBT, 7 on the IELTS, or 115 on the Duolingo English test regardless of their current residency.
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
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
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CTRPT 105
PSNoMail@asu.edu
480-555-3199
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.
