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Every day, the amount of data (from audio to video, and from electronic health records to browsing interests and shopping preferences) continues to increase, and there is a corresponding explosion of demand from industry for engineers who are trained to extract relevant information from such data so that it can be used to improve modern technology and society. This increased demand for qualified data scientists cannot be met with the current pool of qualified engineers. To meet this need, the Master of Science in Electrical and Computer Engineering – Machine Learning and Data Science provides students with focused, rigorous training in the theory, methods, and applications of data science, machine learning and signal, and information processing.
Please Note: Requirements for graduation, course offerings, course availability, track offerings and any other degree requirements are subject to change. Students should consult with an academic advisor prior to registering for any classes.
- A minimum of 28 units is required for the M.S. in Electrical and Computer Engineering – Machine Learning and Data Science degree
- Students are required to pass a digital signal processing test, or take EE 483 – Introduction to Digital Signal Processing as a technical elective (3 units)
- Required courses: 18-20 units
- At least 16 units must be taken in Electrical Engineering
- A minimum cumulative GPA of 3.0 is required for graduation
- A maximum of 4 units of Directed Research, EE 590 or Thesis, EE 594ab may be counted as a technical elective