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Autumn Quarter Class Options

How to Register for Your Courses:

You’ll register through MyUW. View Step #4 on this webpage for detailed instructions.

Additional Information:

  • Many of our courses are offered under advanced topics numbers like 590, 538, 596, 598, and 592. The actual subject/ topic of the course is listed below, but what you’ll see when you register is the advanced topic title. For example, instead of “EE P 596: Deep Learning for Big Visual Data “Advanced Topics in Signal and Image Processing”. You’re allowed up to 16 credits (4 classes) of the same number as long as the topic is different, so don’t worry about duplicate course numbers.
  • Is the class you’re interested in closed? Sign up for NotifyUW, which will send you an email or text message if/when a spot opens up!
  • Only enroll in the credits you intend to complete. Full-time is 10 credits, and we allow a max of 12 (we will ask you to drop excess credits). 

Taking Non-PMP Courses:

  • Students can utilize a max of 3 classes/ 12 credits outside of the PMP curriculum towards their degree
  • Daytime EE courses are considered non-PMP courses
  • Courses must be STEM related or advances your career interests (please check with me first to make sure it will apply!)
  • Only one non-EE class can be at the 300 level. The rest must be at the 400 or 500 level.
  • Not all classes are available for all students. Please view the notes section of the class to check for any restrictions. If you’re not eligible to register for a class outside of ECE, we’re unfortunately unable to make exceptions and you’ll need to contact that department for further assistance.

Course Offerings:

Below are the courses we’re offering with links to additional information for your reference. Keep in mind that some of these documents are in draft form or are syllabi from prior offerings, so there could be some changes to the content/ structure.

EE P 500: Graduate Seminar

  • 1 Credit (A): SLN 14364
  • 2 Credits (B): SLN 14365

EE P 500: Other options (still counts towards your required 5-9 credits of EE P 500)

2 credits (C): Intellectual Property for Engineers

    • SLN 14366, Wednesday 4:30-6:20 pm, Probst and Gardner

1 credit (E) and 2 credits (F): Robotics Mentorship Practicum

NOTE: You can take EE P 500 A, B, C, and E/F simultaneously.

EE P 502: Analytical Methods for Electrical Engineering (intended for new Fall 26 students only)

  • SLN 14370, Wednesday 6:30-9:50 pm, Bonaci

EE P 524: Applied High Performance Computing (synchronous online)

  • SLN 14371, Tuesday 6:30-9:50 pm, Reinhardt

EE P 535: Digital Systems Design with FPGAs

  • SLN 14373, Tuesday and Thursday 4:30-6:20 pm, Makhsous

This class was previously offered under the EE P 538 course number

EE P 545: The Self Driving Car: Intro to AI for Mobile Robots

  • SLN 14374, Tuesday 6:30-9:50 pm, Smith

EE P 568: Deep Learning for Big Visual Data Also view course slides

  • SLN 14376, Wednesday 6:30-9:50 pm, Hwang

EE P 590: Data Structures and Algorithms for ECE Applications

  • SLN 14378, Monday and Wednesday 4:30-6:20 pm, TBD

EE P 595: Computer Systems Security 

  • SLN 14380, Monday 6:30-9:50 pm, Sahabandu

EE P 596: Computer Vision: Deep and Classical Methods

  • SLN 14382, Thursday 6:30-9:50 pm, Birchfield

EE P 596: Foundations of Applied Deep Learning (first class in person, then synchronous online)

  • SLN 14384, Monday 6:30-9:50 pm, Kim

This course was formerly offered as EE P 596: Practical Introduction to Deep Learning Applications and Theory. The course has been expanded into two courses: Foundations of Applied Deep Learning (Fall) and Advanced Methods in Applied Deep Learning (Winter). If you previously took Practical Introduction to Deep Learning Applications and Theory, please do not take the Foundations course as there will be too much overlap. However, you are welcome to take the Winter Advanced Methods course as it will cover new material!

EE P 598: Medical Devices and Digital Transformation

  • SLN 22806, Thursday 6:30-9:50, Daoura

EE P 598: Mastering The Systems Modeling Language (SysML) V1: for Model Based Systems Engineering (MBSE) and the OMG Certified Systems

  • SLN 14386, Monday 6:30-9:50, Soliman

EE 572: Microwave EngineeringLinks to an external site.

  • SLN 13989, Thursday 6:30-9:50, Reynolds

EE P 599: Research in ECE

  • SLN 14387. This isn’t a specific course, but rather credits you enroll in if you work with a professor in their lab. You’ll get in touch with a professor/ lab of interest, and if they agree to work with you, you’ll complete a form to receive a registration add code. More information can be found on our Canvas page!

EE P 598: Engineering Entrepreneurial Systems and Design (graduate section of the 2 credit course Fall ENGINE kick-off course)

  • SLN 13996, Friday 11:30-12:50, Arabshahi