Electrical and Computer Engineering with Concentration in Hardware and Software for Machine Intelligence, MSECE (Seattle)
Graduatemajor2027 catalogEngineeringSeattle32 semester hours totalverified parse
Official catalog page for this program
Fundamental Courses
From the catalog
Complete at least 8 semester hours from the following:
- EECE 5644 — Introduction to Machine Learning and Pattern Recognition
- EECE 7205 — Fundamentals of Computer Engineering
- EECE 7352 — Computer Architecture
- EECE 7353 — VLSI Design
Concentration Courses
16 semester hours.
From the catalog
Complete a minimum of 16 semester hours from the concentration course list below.
Any fundamental course not used to meet the fundamental course requirement can be used toward the concentration course requirement.
Elective Courses
8 semester hours.
From the catalog
Students may complete a maximum of 8 semester hours from either the concentration course list or a maximum of 8 semester hours from the elective course list.
Project
- One of:
- EECE 7945 — Master’s Project
Concentration Courses (2)
12 semester hours.
From the catalog
Complete 12 semester hours from the concentration course list below. Any fundamental course not used to meet the fundamental course requirement can be used toward the concentration course requirement.
Electives
8 semester hours.
From the catalog
Complete 8 semester hours from either concentration courses or from other concentrations.
Thesis
From the catalog
In addition to completing the thesis course, students must successfully complete the thesis submission process, including securing committee and Graduate School of Engineering signatures and submission of an electronic copy of their MS thesis to ProQuest.
Concentration Courses (3)
8 semester hours.
From the catalog
Complete a minimum of 8 semester hours from the concentration course list below. Any fundamental course not used to meet the fundamental course requirement can be used toward the concentration course requirement.
Electives (2)
8 semester hours.
From the catalog
Students may complete a maximum of 8 semester hours from either the concentration course list or a maximum of 8 semester hours from the elective course list.
Optional Co-op Experience
From the catalog
Complete the following (students must complete ENCP 6100 to qualify for co-op experience):
- ENCP 6100 — Introduction to Cooperative Education
- One of:
Concentration Courses (4)
- One of:
- CS 5180 — Reinforcement Learning and Sequential Decision Making
- CS 5335 — Robotic Science and Systems
- CS 7340 — Theory and Methods in Human Computer Interaction
- EECE 5512 — Networked XR Systems
- EECE 5550 — Mobile Robotics
- EECE 5552 — Assistive Robotics
- EECE 5554 — Robotics Sensing and Navigation
- EECE 5612 — Statistical Inference: An Introduction for Engineers and Data Analysts
- EECE 5614 — Reinforcement Learning and Decision Making Under Uncertainty
- EECE 5639 — Computer Vision
- EECE 5640 — High-Performance Computing
- EECE 5641 — Introduction to Software Security
- EECE 5642 — Data Visualization
- EECE 5643 — Simulation and Performance Evaluation
- EECE 5644 — Introduction to Machine Learning and Pattern Recognition
- EECE 5645 — Parallel Processing for Data Analytics
- EECE 5665 — Signal Processing for Global Navigation Satellite Systems
- EECE 5698 — Special Topics in Electrical and Computer Engineering
- EECE 5698 — Special Topics in Electrical and Computer Engineering
- EECE 5698 — Special Topics in Electrical and Computer Engineering
- EECE 5698 — Special Topics in Electrical and Computer Engineering
- EECE 5699 — Computer Hardware and System Security
- EECE 6400 — Special Problems in Electrical and Computer Engineering
- EECE 7150 — Autonomous Field Robotics
- EECE 7204 — Applied Probability and Stochastic Processes
- EECE 7205 — Fundamentals of Computer Engineering
- EECE 7215 — Introduction to Distributed Intelligence
- EECE 7268 — Verifiable Machine Learning
- EECE 7323 — Numerical Optimization Methods
- EECE 7337 — Information Theory
- EECE 7345 — Big Data and Sparsity in Control, Machine Learning, and Optimization
- EECE 7346 — Probabilistic System Modeling and Analysis
- EECE 7352 — Computer Architecture
- EECE 7353 — VLSI Design
- EECE 7368 — High-Level Design of Hardware-Software Systems
- EECE 7370 — Advanced Computer Vision
- EECE 7390 — Computer Hardware Security
- EECE 7397 — Advanced Machine Learning
- EECE 7398 — Advanced Special Topics in Electrical and Computer Engineering
- EECE 7398 — Advanced Special Topics in Electrical and Computer Engineering
- EECE 7398 — Advanced Special Topics in Electrical and Computer Engineering
- EECE 7398 — Advanced Special Topics in Electrical and Computer Engineering
- EECE 7398 — Advanced Special Topics in Electrical and Computer Engineering
- EECE 7398 — Advanced Special Topics in Electrical and Computer Engineering
- EECE 7398 — Advanced Special Topics in Electrical and Computer Engineering
- EECE 7400 — Advanced Special Problems in Electrical and Computer Engineering
- IE 5360 — Digital Manufacturing
- MATH 7233 — Graph Theory
- PHIL 5010 — AI Ethics
Excluded Courses for All MSECE Concentrations
From the catalog
Courses from the following subject areas may not count toward any concentration within the MSECE program:
CSYE, DAMG, INFO, TELE
The following CS courses may not count toward any concentration within the MSECE program:
- One of:
- CS 5010 — Programming Design Paradigm
- CS 5330 — Pattern Recognition and Computer Vision
- CS 5340 — Computer/Human Interaction
- CS 5520 — Mobile Application Development
- CS 5610 — Web Development
- CS 5700 — Fundamentals of Computer Networking
- CS 5800 — Algorithms
- CS 6140 — Machine Learning
- CS 6350 — Empirical Research Methods
GPA requirements
- Minimum 3.000 GPA required
Parsed from the catalog by NU Map; the structured machine copy is in this college's JSON for the 2027 catalog, under electrical-and-computer-engineering-with-concentration-in-hardware-and-software-for-machine-intelligence-msece-seattle, and the official page is the authority.