Embedded Systems Engineering Subplan

From ESE to augmented and virtual reality engineer

“It’s amazing that I use fundamental learnings from my grad program—such as identifying bottlenecks in engineer workloads, or other steps that allow efficient processing in a complex environment—on a daily basis in my work." - Abhishikta Pandit

Read Abhishikta's story
Most of us will casually encounter dozens of embedded systems by mid-morning each day throughout our residences, roadways andÌýworkplaces. Fundamentally, an embedded system is some combination of hardware and software that is designed for a particular function. It senses a real-world condition, does some computing, then produces output data or control of some kind.
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These intelligent machines are a permanent part of our global landscape, and are continuously being expanded and upgraded by a world of forward-thinking engineers and entrepreneurs. Application domains include aerospace and defense, energy, industrial automation, medical, networking and communication, security, transportation and more. Also expected to fuel much more growth is an overarching megatrend referred to as the Internet of Things (IoT), which involves connecting more embedded systems to the internet, enabling countless human-to-machine and machine-to-machine applications ranging from home automation to security and many beyond.
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Fueled by dramatic reductions in size, cost, and power consumption, combined with ever increasing availability of wireless networking technology, the industry estimates that there could be 100 billion connected devices by 2027. Revenue projections for IoT nodes, gateways, platforms, software and services could be as high as $1,149B USD by 2027. This trend ushers in greater hardware and software design challenges for low-power, and effectively managing and securing connected devices, as well as capturing and harnessing vast amounts of data produced by business operations.Ìý
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The Embedded Systems Engineering (ESE) subplan provides comprehensive coverage of essential embedded technologies, current tools and trends. It is structured to provide students with a broad, versatile skillset and coupled with industry input for continuous curriculum updates.
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Through flexible course options, students enrolled in the ESE subplan may pursue a 9-credit hour certificate or a 30-credit hour Professional Master of Science (MSEE) or Master of Engineering (ME) degree. The certificate and degrees are able to be completed online, with the majority of classes having an online section option.Ìý

Students admitted directly to the ESE subplan have course enrollment priority to meet ESE requirements.

ESE Core Courses

  • ECEN 5613ÌýEmbedded System Design
  • ECEN 5623Ìý
  • ECEN 5803Ìý
  • ECEN 5813Ìý
  • ECEN 5823Ìý
  • ECEN 5833Ìý*
  • ECEN 5853Ìý
  • ECEN 5863ÌýÌý

ESE Electives

  • ECEN 5003 Special Topics: Embedded AI?
  • ECEN 5133 Fundamentals of Computer SecurityÌý- no ESE enrollment priority
  • ECEN 5224 High Speed Digital DesignÌý- no ESE enrollment priority
  • ECEN 5593ÌýÌýÌý- no ESE enrollment priority
  • ECEN 5713Ìý*
  • ECEN 5730Ìý
  • ECEN 5763Ìý
  • ECEN 5773Ìý*
  • ECEN 5313ÌýConcurrent Programming - no ESE enrollment priority
  • ECEN 5525 Compiler Construction - no ESE enrollment priority
  • ECEN 5033 Datacenter Scale Computing - no ESE enrollment priority
  • ECENÌý5139 Computer Aided Verification - no ESE enrollment priority

? For Fall 2025, there was a software error in the student catalog, so that the course description, title, etc. are not accurately displaying. ÌýHere is the description for ECEN 5003 Special Topics: ÌýEmbedded AI: Ìý Embedded AI is the integration of Artificial Intelligence (AI) into resource-limited devices or systems, enabling smart, efficient, and real-time decision-making on resource-constrained devices in applications such as wearables, smart home devices, and industrial automation systems. In this course, students will learn key concepts of embedded systems, AI algorithms, and optimization techniques, with a focus on deploying AI models on embedded devices. It emphasizes practical tools, techniques, and applications, preparing students to address modern challenges in AI-powered embedded solutions. No prior background on AI or Machine Learning (ML) is needed, though this is not a replacement for a course which covers the foundational theory of AI/ML.

  • Individual course prerequisites are provided on the respective course pages.
  • Those indicated with an asterisk (*) above have an online section.
  • All courses are 3 credits.

The ESE courses are a subplan in the Professional Master of ScienceÌýdegree. Students must apply and be admitted to the Professional MS program and the ESE subplan. Ìý

ESE MS subplan requirements:

  • Any five ESE core courses
  • Any two ESE elective courses (or additional ESE core courses)
  • Three open 5000-level electives, either ESE core or elective,Ìýother ECEE,Ìýor other technical coursework in College of Engineering and Applied Science departments (must be approved by academic advisor).
    • Students may take one nontechnical elective, if approved by academic advisor.Ìý

Students graduate with a Master of Science in Electrical & Computer Engineering, Subplan: Embedded Systems Engineering

The ESE courses are a subplan in the Professional Master of EngineeringÌýdegree. Students must apply and be admitted to the Professional ME program and the ESE subplan. Ìý

ESE ME subplan requirements:

  • Any five ESE core courses
  • Any two ESE elective courses (or additional ESE core courses)
  • Three open 5000-level electives, either ESE core or elective,Ìýother ECEE,Ìýor other technical or nontechnical coursework in College of Engineering and Applied Science departments (must be approved by academic advisor).

Students graduate with a Master of Engineering in Electrical & Computer Engineering, Subplan: Embedded Systems Engineering