Program Overview

Data Science, Analytics and Engineering (Electrical Engineering), MS

The Master of Science program in data science, analytics and engineering with a concentration in electrical engineering provides an advanced education in high-demand data science and electrical engineering. A focus on probability and statistics, machine learning, data mining and data engineering is complemented by electrical engineering-specific courses to ensure breadth and depth in data science and electrical engineering.

Program 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. However, the majority of engineering occupations require subject matter expertise beyond data science.

At a Glance

• College/school: Ira A. Fulton Schools of Engineering
• Location: Tempe
• STEM-OPT extension eligible: Yes

Accelerated Program Options

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.

Degree Requirements

• 30 credit hours and a thesis, or
• 30 credit hours including the required capstone course (FSE 570)
• Required Core (9 credit hours)
  • 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)
• Concentration (9 credit hours)
  • Choose three courses from the following:
    • EEE506 Digital Spectral Analysis (3)
    • EEE508 Digital Image and Video Processing and Compression (3)
    • EEE509 DSP Algorithms and Software (3)
    • EEE510 Multimedia Signal Processing (3)
    • EEE 511 Artificial Neural Computation (3)
    • EEE515 Machine Vision and Pattern Recognition (3)
    • EEE516 Physics-Based Computer Vision (3)
    • EEE 551 Information Theory (3)
    • EEE 554 Probability and Random Processes (3)
    • EEE556 Detection and Estimation Theory (3)
    • EEE559 Wireless Networks (3)
    • EEE 560 Mathematical Foundations of Machine Learning (3)
    • EEE585 Security and Privacy in Networked Systems (3)
    • EEE598 Deep Learning: Foundations and Applications (3)
    • EEE598 Optimization for Engineers (3)
• Electives (6 or 9 credit hours)
• Culminating Experience (3 or 6 credit hours)
  • EEE 599 Thesis (6)
  • FSE 570 Data Science Capstone (3)

Admission Requirements

• General university admission requirements:
  • All students are required to meet general university 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 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:
  • Graduate admission application and application fee
  • Official transcripts
  • Written statement
  • Professional resume
  • Proof of English proficiency

Tuition Information

When it comes to paying for higher education, everyone’s situation is different. Students can learn about ASU tuition and financial aid options to find out which will work best for them.

Application Deadlines

• Fall:
  • Session A/C: In Person, Deadline: 12/31, Type: Priority
• Spring:
  • Session A/C: In Person, Deadline: 07/31, Type: Priority

Career Opportunities

Electrical engineers with a background in data science can pursue opportunities in a variety of fields to manage, analyze and extract data from large data sets, including in the following industries:

• Circuit design
• Energy and power systems
• Semiconductor fabrication
• Signal processing
• Telecommunications

Additional Information

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.