Master of Science in Electrical and Computer Engineering Overview
As technology evolves at an astounding pace, skilled engineers who can find innovative solutions to emerging problems will find themselves consistently in demand in the global marketplace. Electrical and computer engineers can apply their technical expertise to create the next wave of advanced equipment and improve existing products. The expert faculty at the University of Arizona built the online Master of Science (MS) in Electrical and Computer Engineering with the input of industry leaders to help you gain critical skills and lead the design and development of complex systems.
Ranked among the top 50 electrical and computer engineering departments in the country by U.S. News & World Report, the ECE department at the University of Arizona contributes to the state’s status as a national center of the high-tech industry. Our faculty and students achieve groundbreaking technological solutions that address the pressing needs of industries and communities.
The electrical and computer engineering master’s degree program is a perfect fit for working engineers who want to excel in a design-oriented role by playing a central part in the creation and planning phases for new technologies. Through the flexible, customizable curriculum, you’ll develop well-rounded technical skills while exploring the areas of the discipline that interest you most. Learn from our faculty of cutting-edge thinkers and experienced educators in fields ranging from communications and signal processing to advanced computer systems and networks.
You can choose to take courses in a variety of topical areas. Gain a versatile range of knowledge across multiple technical fields or complete a focused academic plan by taking courses in:
- High-performance Computing
- Digital Signal Processing, Communications, and Control
- Computer Networks
- Software Engineering and Artificial Intelligence
- Circuit Design, VLSI, and CAD
- Computer Vision, Control, and Robotic Systems
- Detection and Estimation
- Holography and Diffractive Optics
- Electromagnetics, Microwaves, and Antennas
- Simulation Modeling and Heterogeneous Systems Design
- Remote Sensing
- Wireless Communications and Networks
Courses can be completed in a 100% online format, with some offering live lectures recorded in the classroom and uploaded to the digital learning platform within the day. The online MS in Electrical and Computer Engineering connects you directly to the same curriculum that defines our traditional, on-campus experience. With the convenience of online learning, you can complete the program on your own schedule while continuing to work full-time.
Prepare for a Career at the Forefront of Technology
Electrical and computer engineers pursue careers focused on developing and implementing the systems that empower organizations to solve vital problems and address emerging challenges. That can mean refining the schematics for a processor to achieve greater speed or monitoring the manufacturing process for the next wave of highly efficient power generation equipment. The University of Arizona online master’s in electrical and computer engineering provides a comprehensive path to professional development for engineers in a variety of industries.
Through our longstanding partnerships with some of the foremost technology companies in the country, including Raytheon, Intel, IBM, Qualcomm, Motorola, Microsoft, Honeywell, Texas Instruments, GM, Agilent, NASA, Boeing, and Pixar, University of Arizona ECE graduates have gone on to pursue advanced positions at innovative organizations.
Top Employers for Electrical Engineers
- Engineering services
- Electric power generation, transmission, and distribution
- Navigational, measuring, electromedical, and control instruments manufacturing
- Research and development in the physical, engineering, and life sciences
- Semiconductor and other electronic component manufacturing
Top Employers for Computer Hardware Engineers
Source: US Bureau of Labor Statistics
- Computer systems design and related services
- Semiconductor and other electronic component manufacturing
- Research and development in the physical, engineering, and life sciences
- Federal government
- Computer and peripheral equipment manufacturing
You can prepare to reach your career goals as an electrical or computer engineer by applying the latest tools and technology to a wide range of challenges. Earning your Master of Science in Electrical and Computer Engineering online will equip you with theoretical knowledge and practical skills that make an impact across multiple industries.
The Master of Science in Electrical and Computer Engineering curriculum is elective based and customizable, giving you the flexibility to build an individual course of study that suits your academic and professional goals. Every course reflects the University of Arizona’s high standards of academic rigor, preparing you to design and implement electrical or computer systems that meet specifications and demonstrate mastery of circuitry and electronics.
All graduate students must submit a Plan of Study detailing their proposed coursework plan by the end of the first year of the program. All Plans of Study must consist of 30 units (10 courses) and will be approved by the Director of Online Programs. You may also submit a revised Plan of Study for approval at any time. The Plan of Study is then finalized and submitted to the Graduate College for approval.
This plan must comprise 30 units of required graduate coursework (500- or 600-level) and fulfill the following requirements:
- All requirements for the master’s degree must be completed within six years to ensure currency of knowledge. Time-to-degree begins with the earliest course listed on the Plan of Study, including credits transferred from other institutions. Work more than six years old is not accepted toward degree requirements.
- Students must maintain a cumulative GPA of 3.0 or higher.
We strongly encourage including a wide breadth of topics in the study plan. Taking a range of courses, rather than focusing on a single topical area, will broaden your skills and knowledge. A varied technical background will deepen your understanding of complex systems so you can adapt to emerging challenges and qualify for more positions as you take the next step in your career.
Master of Science in Electrical and Computer Engineering Course List (30 units)
Mathematical fundamentals for analysis of linear systems. Maps and operators in finite and infinite dimensional linear vector spaces, metric spaces, and inner-product spaces. Introduction to representation theory. Eigensystems. Spectral theorems and singular value decomposition. Continuity, convergence, and separability. Sturm-Louisville theory. Prerequisite(s): Graduate standing or permission of the instructor
Probability, random variables, stochastic processes, correlation functions, and spectra with applications to communications, control, and computers. Prerequisite(s): SIE230 or equivalent
This course addresses modeling, metamodeling, advanced object-oriented system design, model-integrated computing, and integrated systems. Behavioral, structural, and process modeling are among the modeling approaches to be examined. Additional topics include semantic mapping, models of computation, graph rewriting, and domain-specific modeling. In lieu of a midterm and final exam, an individual project will be performed over the course of the semester, constituting a large portion of the grade. Course Requisites: ECE 373. Graduate standing or consent of instructor. Recommend a strong command of C++ or Java programming language.
This course provides an introduction to technical aspects of cyber security. It describes threats and types of attacks against computers and networks to enable students to understand and analyze security requirements and define security policies. Security mechanisms and enforcement issues will be introduced. Students will be immersed in the cyber-security discipline through a combination of intense coursework, open-ended and real-world problems, and hands on experiments. Course Requisites: ECE 578.
This course describes the nature of holographic and lithographically formed diffraction gratings and the tools necessary for their design and analysis. Course topics include a description of the interference and Fourier relations that determine the amplitude of diffracted fields, analysis of volume gratings, properties of holographic recording materials, computer generated holograms, binary gratings, analysis of applications of holography including data storage, imaging systems, photovoltaic energy systems, polarization control elements, and associative memories. We will also have a number of lab demonstrations fabricating holograms in a new type of photopolymer. Course Requisites: OPTI 502, OPTI 505R or ECE 459 or ECE 559.
Discrete-time signals and systems, z-transforms, discrete Fourier transform, fast Fourier transform, digital filter design. Graduate-level requirements include additional homework and a term project. Prerequisite(s): ECE 340, MATH 322
The purpose of the course is to give students a comprehensive introduction to digital communication principles. The major part of the course is devoted to studying how to translate information into a digital signal to be transmitted, and how to retrieve the information back from the received signal in the presence of noise and intersymbol interference (ISI). Various digital modulation schemes are discussed through the concept of signal space. Analytical and simulation models for digital modulation systems are designed and implemented in the presence of noise and ISI. Optimal receiver models for digital base-band and band-pass modulation schemes are covered in detail. Graduate work will include more challenging problem sets and exam problems, and a C/C++ simulation project. Prerequisite(s): ECE340A
Radar fundamentals: radar range equation, waveforms, ambiguity functions. Signal Processing: pulse compression, synthetic aperture radar (SAR)inverse SAR, moving target indication (MTI), Pulse-Doppler radar, space time adaptive processing (STAP).
Modeling, analysis, and design of digital control systems; A/D and D/A conversions, Z-transforms, time and frequency domain representations, stability, microprocessor-based designs. Graduate-level requirements include additional homework and a term project. Prerequisite(s): ECE 340
This course aims to provide a strong foundation for students to understand modern computer system architecture and to apply these insights and principles to future computer designs. It provides basic knowledge, fundamental concepts, design techniques and trade-offs, machine structures, technology factors, software implications, and evaluation methods and tools required for understanding and designing modern computer architectures including multicores, embedded systems, and parallel systems. The course is structured around the three primary building blocks of general-purpose computing systems: processors, memories, and networks. The first part of the course focuses on the fundamentals of each building block. Topics include processor microcoding and pipelining; cache microarchitecture and optimization; and network topology, routing, and flow control. The second part goes into more advanced techniques and will enable students to understand how these three building blocks can be integrated to build a modern computing system. Topics include superscalar execution, branch prediction, out-of-order execution, register renaming, and memory disambiguation; VLIW, vector, and multithreaded processors; memory protection, translation, and virtualization; and memory synchronization, consistency, and coherence. The third part addresses parallel computing, including multicore architectures, datacenters and cloud computing, and others. Graduate-level students will be required to complete a term paper and extra homework. Prerequisite(s): ECE 175, ECE 274, ECE372 or consent of instructor
Current state of the internet; multimedia requirements; quality of service in IP networks; RSVP; real-time protocol (RTP); differentiated-services (Diffserv) architecture; traffic control; traffic policing and admission control; burstiness and traffic characterization; flow control; TCP enhancements; fairness and protection; packet scheduling and buffer management; inter-domain routing (BGP protocol); intra-domain routing (OSPF protocol); hierarchical routing; web caching; medium access control in wireless LANs; mobile ad hoc networking (routing and MAC protocols, power control, topology control); addressing schemes and MAC design for sensor networks; and others.
Offered every two years. Knowledge systems are intelligent systems that totally or partially involve computational representation and processing of knowledge. This class introduces the principles and techniques for engineering and developing of knowledge systems. Alternative computational structures for knowledge representation, procedures and algorithms for computational processing, automated reasoning and inference from knowledge, learning new knowledge, handling uncertainty in information, knowledge-based decision networks, distributed knowledge systems, alternative system architectures and engines. Graduate-level requirements include a more extensive and in-depth project, have to do additional assignment or question on the exam.
In-depth consideration of each of the phases of the software project life code. Object-oriented design and programming. Includes a large-scale software development project involving groups of students. Graduate-level requirements include additional homework and a term project.
This course provides an introduction to the fundamental principles of computer networks and data communications. Emphasis is given on current technologies and architectures for establishing direct link and packet-switched networks, sharing access to a common communication medium, internetworking and routing, end-to-end flow control, congestion control and recourse allocation, and network security. Prerequisite(s): ECE175
Provides an introduction to problems and techniques of artificial intelligence (AI). Automated problem solving, methods, and techniques; search and game strategies, knowledge representation using predicate logic; structured representations of knowledge; automatic theorem proving, system entity structures, frames, and scripts; robotic planning; expert systems; implementing AI systems. Graduate-level requirements include additional assignments. Prerequisite(s): ECE 373 or equivalent course.
View our suggested online courses to explore areas that may be of interest to you. For further guidance on which courses may benefit you professionally, please contact an Admissions Counselor at email@example.com.