Data Science, Analytics and Engineering (Human-Centered Applications), MS
Data Analytics, Data Engineering, Data Science, Human Systems Engineering, Human-Centered, Machine Learning, approved for STEM-OPT extension
Have you encountered accidental biases in smart devices or generative artificial intelligence? Would you like to improve machine learning to best serve human needs? Gain in-demand data science skills while enhancing your expertise in applying this knowledge to human capabilities.
There is an increasing need for all engineers to make use of data science tools such as statistics, machine learning, artificial neural networks and AI. Yet, the majority of engineering occupations require subject matter expertise beyond data science.
In the Master of Science program in data science, analytics and engineering with a concentration in human-centered applications, students receive an advanced education in high-demand data science and gain an understanding of human systems. A focus on probability and statistics, machine learning, data mining and data engineering is complemented by courses that focus on human capabilities and understanding human bias to ensure increased breadth and depth in data science applications. Students learn how to address problems such as biases in machine learning that are due to select input data and how to determine useful human feedback for interactive machine learning. The program also covers ethical issues in machine learning applications, and the use of AI to support human weaknesses without hindering human strengths. In interdisciplinary courses, students can work with colleagues on client-driven data science problems, developing solutions that address human needs and capabilities.
This program may be eligible for an Optional Practical Training extension for up to 24 months. This OPT work authorization period may help international students gain skills and experience in the U.S. Those interested in an OPT extension should review ASU degrees that qualify for the STEM-OPT extension at ASU's International Students and Scholars Center website.
The OPT extension only applies to students on an F-1 visa and does not apply to students completing a degree through ASU Online.
- College/school:
Ira A. Fulton Schools of Engineering
- Location: Polytechnic
- STEM-OPT extension eligible: Yes
This program allows students to obtain both a bachelor's and a master's degree in as little as five years. Accelerated bachelor's plus master's degree programs are designed for high-achieving students who want the opportunity to share undergraduate coursework with graduate coursework to accelerate completion of their 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:
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.
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 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 consult with their academic advisor to ensure that the total number of credit hours in their plan of study equals 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)
HSE 520 Methods and Tools in Applied Cognitive Science (3)
HSE 530 Intermediate Statistics for Human Systems Engineering (3)
HSE 531 Data Analytics: Modeling Human Subjects Data (3)
HSE 542 Foundations of Human Systems Engineering (3)
FSE 570 Data Science Capstone (3)
HSE 599 Thesis (6)
For concentration coursework, students select three courses for a total of nine credit hours.
General university admission requirements:
All students are required to meet general
university admission requirements.
U.S.
applicants | International
applicants | English
proficiency
Applicants must fulfill the requirements of both the Graduate College and the Ira A. Fulton Schools of Engineering.
To be considered for admission to the program, 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 their first bachelor's degree program or 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 nine credit hours of graduate coursework from a U.S. institution; or a cumulative GPA of 3.00 (scale is 4.00 = "A") in an applicable conferred master's degree program from a regionally accredited college or university.
Applicants are required to submit:
- graduate admission application and application fee
- official transcripts
- written statement
- professional resume
- three letters of recommendation
- 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.
All applicants must demonstrate relevant coursework or experience in the following three areas:
- familiarity with MATLAB, Python, SQL, or R, or other relevant programming skills (in the professional resume)
- undergraduate linear algebra (e.g., MAT 242 Elementary Linear Algebra)
- undergraduate statistics or probability (e.g., IEE 380 Probability and Statistics for Engineering Problem Solving, STP 420 Introductory Applied Statistics, STP 421 Probability, EEE 350 Random Signal Analysis)
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:
- AWS-certified cloud practitioner
- Google IT support certificate
- Google data analytics certificate
If the applicant does not meet the minimum GPA requirements, the application may still be considered. In certain cases, demonstrated aptitude through professional experience or additional postbaccalaureate education is considered.
Unofficial transcripts may be submitted at the time of application. If admitted, applicants must then submit official transcripts to ASU Graduate Admission Services.
| Session | Modality | Deadline | Type |
|---|---|---|---|
| Session A/C | In Person | Rolling |
| Session | Modality | Deadline | Type |
|---|---|---|---|
| Session A/C | In Person | Rolling |
Data scientist is consistently listed among the top jobs in the U.S. Human-centered engineers with a background in data science can pursue opportunities in a variety of industries to manage and analyze data and extract knowledge from large data sets for decision-making. Career opportunities include:
- clinical data manager
- computer and information research scientist
- human factors engineer and ergonomist
- statistician
Human Systems Engineering
|
SUTON 201
polygrad@asu.edu
480-727-1874
Program term definitions
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.
