Electronic Delivery of Gator Engineering, or EDGE, is a great way to earn an online master’s degree in Electrical and Computer Engineering (ECE). This innovative program features the same preeminent instructors as traditional degree tracks—delivered online.
ECE EDGE is also perfect for learners looking for a specific course to support their lifelong engineering professional development. With ECE EDGE, your path is up to you. Students can take one to three courses per semester, or take a semester off with no penalty. The flexibility of the program allows EDGE students build their own curriculum, choosing just the courses and goals that work for them. The degree requires 30 credits or ten 3-credit courses. The current ECE course offerings are listed below but the MS requirements allows up to three courses outside the department. Additional online courses are available in entrepreneurship, innovation, computer science, and other engineering departments. Also, hybrid options are available for taking some courses online and others on campus. If you are interested, ask us how.
Students Interested in Pursuing a Master’s Degree in ECE via EDGE
Students interested in pursuing a Master of Science (MS) degree in the ECE department will need to apply for admission to the UF Graduate School. More information about deadlines and the application process can be found here.
Tuition and Fees
Tuition and fees information can be found here. College of Engineering Achievement Awards may not be applied to tuition and fees for online courses.
Proctoring
ECE-EDGE courses utilizes proctoring services offered by Honorlock and ProctorU. These services offer students a great deal of convenience and flexibility for scheduling exams while assuring a secure exam taking environment. Students may be required to have access to a high resolution camera and/or scanner to upload exam answers. More information about how these proctoring services work can be found here.
Non-Degree Students
Students interested in taking individual courses on a semesterly basis can do so as a non-degree student. Non-degree admission must be requested each semester. In order to be admitted as a non-degree student, you must have a GPA of a 2.5 or higher. Students must receive a letter grade of a B or better in their courses as a non-degree student in order to continue in the program each semester.
APPLICATION PROCESS
The non-degree seeking application deadlines for the ECE department are:
Fall
August 5
Spring
December 16
Summer
April 25
To apply for non-degree status, students must submit the following by the deadline:
Non-Degree Application When starting your application, select the appropriate academic year non-degree application. Be sure to select “FEEDS/EDGE Program” option in the Special Program portion of the application. Applicants interested in claiming Florida residency for tuition purposes must provide the required documentation when submitting the non-degree application. When completing your non-degree seeking application, you will need to indicate which course(s) for which you would like to register. You can find a list of course offerings below.
Copy of Transcripts Non-Degree applicants are required to submit an unofficial copy of their college transcripts as part of the application process. Copies of transcripts should be emailed directly to ECE-EDGE@ece.ufl.edu by the deadline above.
When an admission decision is made, you will receive an email notification from ECE-EDGE. This email will include further instructions on how to complete your registration.
Students can transfer up to 15 credits of UF ECE-EDGE course work towards an ECE Master’s Degree program at UF. A grade of “B” or better must be earned in each individual course in order to be transferred into an ECE Master’s degree (no exceptions). Students must earn a “B” or better in all non-degree seeking courses in order to register as a non-degree seeking student in future semesters. It is advisable to apply to graduate school during your first semester as a non-degree seeking student if your ultimate goal is to pursue a Master’s degree in ECE at UF.
Fundamental analytical techniques for modeling, analyzing, and processing electrical signals and computer data in the presence of noise and randomness. Covers from probability to filtering of random processes, with applications to communications, signal and image processing, data compression, and simulation.
Fundamentals of hardware security and trust for integrated circuits. Cryptographic hardware, invasive and non-invasive attacks, side-channel attacks, physically unclonable functions (PUFs), true random number generation (TRNG), watermarking of Intellectual Property (IP) blocks, FPGA security, counterfeit detection, hardware Trojan detection and prevention in IP cores and integrated circuits.
Advanced very large scale integrated circuit design, testability, and performance evaluation. Use of industrial VLSI software. Building an advanced CMOS VLSI circuit.
Focuses on practical learning of computer hardware security using a hands-on approach. Students will work on a custom-designed hardware platform to understand innards of a computer system and ethically “hack” into it at different levels. They will examine it to understand security vulnerabilities, mount attacks, and implement countermeasures.
Fundamentals in design and quantitative analysis of modern computer architecture and systems, including instruction set architecture, basic and advanced pipelining, superscalar and VLIW instruction-level parallelism, memory hierarchy, storage, and interconnects.
Nonlinear modeling and neural networks. Gradient descent learning in the additive neural model; statistical learning concepts; dynamic neural networks, function approximation and short-term memory; unsupervised learning networks; generative models and statistical representation; autonomous learning using cognitive principles. Importance and challenges of deep learning; applications for image, video, speech recognition.
Advanced very large scale integrated circuit design, testability, and performance evaluation. Use of industrial VLSI software. Building an advanced CMOS VLSI circuit.
Provides a comprehensive overview of safety and security of electronic systems in current and emergent vehicles, including automotive and aerospace systems. Topics covered include: vehicular functional safety practices, standards, and limitations; vehicular security and trust; approaches to trustworthy vehicular communications; robustness, resiliency and reliability.
Develop a deep understanding of operating system concepts and systems programming fundamentals and gain hands-on experience in systems programming by using Pthreads as well as implementing Linux device drivers and testing/verifying systems code for deadlock and race-freedom.
Electric drive systems (EDS) are used extensively in a wide range of applications, including electric vehicles, drones, electric aircraft, robots, wind generators, satellites, spacecraft, etc. This course will introduce the fundamentals of electric drive systems, with a special focus on the steady-state analysis of permanent magnet AC drives, which are used extensively in these applications. Three speakers respectively from Tesla, C-Motive Technologies, and Ford are invited to give students some taste of forefront development on these topics.
The specification, design, implementation, and verification of complex hardware-software systems on chip. Overview of transaction-level modelling (TLM) with refinement down to register-transfer level (RTL). Review of state-of-the-art languages and tools and practice on an FPGA project.
Advanced architecture emphasizing design and quantitative analysis of parallel architecture and systems, including theory, hardware technologies, parallel and scalable architectures, and software constructs.
Fundamental analytical techniques for modeling, analyzing, and processing electrical signals and computer data in the presence of noise and randomness. Covers from probability to filtering of random processes, with applications to communications, signal and image processing, data compression, and simulation.
Fundamentals of hardware security and trust for integrated circuits. Cryptographic hardware, invasive and non-invasive attacks, side-channel attacks, physically unclonable functions (PUFs), true random number generation (TRNG), watermarking of Intellectual Property (IP) blocks, FPGA security, counterfeit detection, hardware Trojan detection and prevention in IP cores and integrated circuits.
Focuses on practical learning of computer hardware security using a hands-on approach. Students will work on a custom-designed hardware platform to understand the innards of a computer system and ethically “hack” into it at different levels. They will examine it to understand vulnerabilities, mount attacks, and implement countermeasures.
Fundamental concepts at introductory graduate level in reconfigurable computing based upon advanced technologies in the field-programmable logic devices. Topics include general concepts, device architectures, design tools, metrics and kernels, system architectures, and application case studies.
This class will be providing a broad introduction to the main principles and abstractions for engineering hardware and software systems, and in-depth studies of their use on computer systems across a variety of designs, be it in operating systems, a client/server application, a database server, or a fault-tolerant disk cluster.
Fundamentals in design and quantitative analysis of modern computer architecture and systems, including set architecture, basic and advanced pipelining, superscalar and VLIW instruction-level parallelism, memory hierarchy, storage, and interconnects.
Nonlinear modeling and neural networks. Gradient descent learning in the additive neural model; statistical learning concepts; dynamic neural networks, function approximation and short-term memory, unsupervised learning networks; generative models and statistical representation; autonomous learning using cognitive principles. Importance and challenges of deep learning; applications for image, video, speech recognition.
Provides a comprehensive overview of safety and security of electronic systems in current and emergent vehicles, including automotive and aerospace systems. Topics covered include: vehicular functional safety practices, standards, and limitations; vehicular security and trust; approaches to trustworthy vehicular communications; robustness, resiliency and reliability.
Develop a deep understanding of operating system concepts and systems programming fundamentals and gain hands-on experience in systems programming by using Pthreads as well as implementing Linux device drivers and testing/verifying systems code for deadlock and race-freedom.
Advanced architecture emphasizing design and quantitative analysis of parallel architecture and systems, including theory, hardware technologies, parallel and scalable architectures, and software constructs.
Fundamental analytical techniques for modeling, analyzing, and processing electrical signals and computer data in the presence of noise and randomness. Covers from probability to filtering of random processes, with applications to communications, signal and image processing, data compression, and simulation.
Fundamentals of hardware security and trust for integrated circuits. Cryptographic hardware, invasive and non-invasive attacks, side-channel attacks, physically unclonable functions (PUFs), true random number generation (TRNG), watermarking of Intellectual Property (IP) blocks, FPGA security, counterfeit detection, hardware Trojan detection and prevention in IP cores and integrated circuits.
Focuses on practical learning of computer hardware security using a hands-on approach. Students will work on a custom-designed hardware platform to understand innards of a computer system and ethically “hack” into it at different levels. They will examine it to understand security vulnerabilities, mount attacks, and implement countermeasures.
Fundamental concepts at introductory graduate level in reconfigurable computing based upon advanced technologies in field-programmable logic devices. Topics include general concepts, device architectures, design tools, metrics and kernels, system architectures, and application case studies.
This class will be providing a broad introduction to the main principles and abstractions for engineering hardware and software systems, and in-depth studies of their use on computer systems across a variety of designs, be it in operating system, a client/server application, a database server, or a fault-tolerant disk cluster.
This course focuses on the design of IoT-based solutions for multi-discipline challenges. The course consists of lectures on the fundamental building blocks and protocols in IoT. Then the course will run as a hands-on, multi-discipline project-oriented course, with project discussions, presentations and demonstrations led by student teams.
Fundamentals in design and quantitative analysis of modern computer architecture and systems, including instruction set architecture, basic and advanced pipelining, superscalar and VLIW instruction-level parallelism, memory hierarchy, storage, and interconnects.
Teaches RF Electronic circuit design for a modern wireless transceiver and the RF circuit theory necessary to guide good design choices. The students learn to use RF IC design tools to design an RF low noise amplifier IC as part of a team final design project.
Advanced very large scale integrated circuit design, testability, and performance evaluation. Use of industrial VLSI software. Building an advanced CMOS VLSI circuit.
Provides a comprehensive overview of safety and security of electronic systems in current and emergent vehicles, including automotive and aerospace systems. Topics covered include: vehicular functional safety practices, standards, and limitations; vehicular security and trust; approaches to trustworthy vehicular communications; robustness, resiliency and reliability.
Develop a deep understanding of operating system concepts and systems programming fundamentals and gain hands-on experience in systems programming by using Pthreads as well as implementing Linux device drivers and testing/verifying systems code for deadlock and race-freedom.
Advanced architecture emphasizing design and quantitative analysis of parallel architecture and systems, including theory, hardware technologies, parallel and scalable architectures, and software constructs.
Fundamental analytical techniques for modeling, analyzing, and processing electrical signals and computer data in the presence of noise and randomness. Covers from probability to filtering of random processes, with applications to communications, signal and image processing, data compression, and simulation.
Focuses on practical learning of computer hardware security using a hands-on approach. Students will work on a custom-designed hardware platform to understand innards of a computer system and ethically “hack” into it at different levels. They will examine it to understand security vulnerabilities, mount attacks, and implement countermeasures.
Fundamental concepts at introductory graduate level in reconfigurable computing based upon advanced technologies in field-programmable logic devices. Topics include general concepts, device architectures, design tools, metrics and kernels, system architectures, and application case studies.
This class will be providing a broad introduction to the main principles and abstractions for engineering hardware and software systems, and in-depth studies of their use on computer systems across a variety of designs, be it in operating system, a client/server application, a database server, or a fault-tolerant disk cluster.
This course focuses on the design of IoT-based solutions for multi-discipline challenges. The course consists of lectures on the fundamental building blocks and protocols in IoT. Then the course will run as a hands-on, multi-discipline project-oriented course, with project discussions, presentations and demonstrations led by student teams.
Fundamentals in design and quantitative analysis of modern computer architecture and systems, including instruction set architecture, basic and advanced pipelining, superscalar and VLIW instruction-level parallelism, memory hierarchy, storage, and interconnects.
Nonlinear modeling and neural networks. Gradient descent learning in the additive neural model; statistical learning concepts; dynamic neural networks, function approximation and short-term memory; unsupervised learning networks; generative models and statistical representation; autonomous learning using cognitive principles. Importance and challenges of deep learning; applications for image, video, speech recognition.
Fundamentals of hardware security and trust for integrated circuits. Cryptographic hardware, invasive and non-invasive attacks, side-channel attacks, physically unclonable functions (PUFs), true random number generation (TRNG), watermarking of Intellectual Property (IP) blocks, FPGA security, counterfeit detection, hardware Trojan detection and prevention in IP cores and integrated circuits.
Advanced very large scale integrated circuit design, testability, and performance evaluation. Use of industrial VLSI software. Building an advanced CMOS VLSI circuit.
Provides a comprehensive overview of safety and security of electronic systems in current and emergent vehicles, including automotive and aerospace systems. Topics covered include: vehicular functional safety practices, standards, and limitations; vehicular security and trust; approaches to trustworthy vehicular communications; robustness, resiliency and reliability.
Develop a deep understanding of operating system concepts and systems programming fundamentals and gain hands-on experience in systems programming by using Pthreads as well as implementing Linux device drivers and testing/verifying systems code for deadlock and race-freedom.
Advanced topics including the modeling of single and three-phase power electronics systems, control design for single and three-phase power electronics systems, reduction and modeling of EMI for power electronics systems and resonant power converters.
Techniques for virtualization of networked computer systems. Virtual machines (classic VMs, application binary interface VMs, para-virtualization), virtual distributed file systems (file system proxies, call-forwarding), and virtual networks (tunneling, virtual private networks).
Fall 2020 Courses
The ECE department will offer EDGE sections for all graduate level courses during the Fall 2020 semester. A complete list of all ECE graduate level courses offered in Fall 2020 can be found at ONE.UF. Students interested in registering for EDGE sections in Fall 2020 should send an email to ECE-Edge@ece.ufl.edu for registration instructions.
Fundamentals of hardware security and trust for integrated circuits. Cryptographic hardware, invasive and non-invasive attacks, side-channel attacks, physically unclonable functions (PUFs), true random number generation (TRNG), watermarking of Intellectual Property (IP) blocks, FPGA security, counterfeit detection, hardware Trojan detection and prevention in IP cores and integrated circuits.
Advanced very large scale integrated circuit design, testability, and performance evaluation. Use of industrial VLSI software. Building an advanced CMOS VLSI circuit.
Methods and principles for the automatic identification/authentication of individuals. Technologies include fingerprint, face, and iris biometrics. Additional topics include biometric system design, performance evaluation, multi-modal biometric systems, and biometric system security.
Develop a deep understanding of operating system concepts and systems programming fundamentals and gain hands-on experience in systems programming by using Pthreads as well as implementing Linux device drivers and testing/verifying systems code for deadlock and race-freedom.
Develop an understanding of the principles of computer security, as it crosses layers of abstraction (application, operating system, hardware and network). Students will learn challenges of building secure computer systems with examples and hands-on assignments. Current research on these challenges will be discussed. Students will review and present conference papers.
Design and analysis of wireless networks including channel characteristics, physical layer, cellular concepts, multiple access control protocols, FEC and ARQ protocols, resource allocation, and wireless standards.
Focuses on practical learning of computer hardware security using a hands-on approach. Students will work on a custom-designed hardware platform to understand innards of a computer system and ethically “hack” into it at different levels. They will examine it to understand security vulnerabilities, mount attacks, and implement countermeasures.
Fundamental concepts at introductory graduate level in reconfigurable computing based upon advanced technologies in field-programmable logic devices. Topics include general concepts, device architectures, design tools, metrics and kernels, system architectures, and application case studies.
This class will be providing a broad introduction to the main principles and abstractions for engineering hardware and software systems, and in-depth studies of their use on computer systems across a variety of designs, be it in operating system, a client/server application, a database server, or a fault-tolerant disk cluster.
Fundamentals in design and quantitative analysis of modern computer architecture and systems, including instruction set architecture, basic and advanced pipelining, superscalar and VLIW instruction-level parallelism, memory hierarchy, storage, and interconnects.
Overview of machine intelligence and the role of machine learning in variety of real-world problems in areas such as biometrics and adaptive filtering. Probability and statistics to handle uncertain data. Learning models from data in both a supervised and unsupervised fashion. Linear models (e.g., linear discriminant analysis) and non-linear models (e.g., neural networks and support vector machines) for classification. Linear dimensionality reduction (e.g., principal components analysis) and non-linear dimensionality reduction (e.g., manifold learning techniques and self-organizing maps).
Fundamentals of hardware security and trust for integrated circuits. Cryptographic hardware, invasive and non-invasive attacks, side-channel attacks, physically unclonable functions (PUFs), true random number generation (TRNG), watermarking of Intellectual Property (IP) blocks, FPGA security, counterfeit detection, hardware Trojan detection and prevention in IP cores and integrated circuits.
Advanced very large scale integrated circuit design, testability, and performance evaluation. Use of industrial VLSI software. Building an advanced CMOS VLSI circuit.
Develop a deep understanding of operating system concepts and systems programming fundamentals and gain hands-on experience in systems programming by using Pthreads as well as implementing Linux device drivers and testing/verifying systems code for deadlock and race-freedom.
Develop an understanding of the principles of computer security, as it crosses layers of abstraction (application, operating system, hardware and network). Students will learn challenges of building secure computer systems with examples and hands-on assignments. Current research on these challenges will be discussed. Students will review and present conference papers.
Optimization of systems using the calculus of variations, dynamic programming, and the maximum principle. Extensive study of the linear plant with a quadratic performance index. Observers and dynamic compensators.
Fundamental concepts at introductory graduate level in reconfigurable computing based upon advanced technologies in field-programmable logic devices. Topics include general concepts, device architectures, design tools, metrics and kernels, system architectures, and application case studies.
This class will be providing a broad introduction to the main principles and abstractions for engineering hardware and software systems, and in-depth studies of their use on computer systems across a variety of designs, be it in operating system, a client/server application, a database server, or a fault-tolerant disk cluster.
Fundamentals in design and quantitative analysis of modern computer architecture and systems, including instruction set architecture, basic and advanced pipelining, superscalar and VLIW instruction-level parallelism, memory hierarchy, storage, and interconnects.
Overview of machine intelligence and the role of machine learning in variety of real-world problems in areas such as biometrics and adaptive filtering. Probability and statistics to handle uncertain data. Learning models from data in both a supervised and unsupervised fashion. Linear models (e.g., linear discriminant analysis) and non-linear models (e.g., neural networks and support vector machines) for classification. Linear dimensionality reduction (e.g., principal components analysis) and non-linear dimensionality reduction (e.g., manifold learning techniques and self-organizing maps).
This lab course focuses on the hands-on learning of computer hardware security. The course will follow a distinctive hands-on teaching approach using a well-designed set of experiments as learning tool. Students will be able to “hack” a system at different levels and analyze different countermeasures for major hardware attacks.
Fundamentals of hardware security and trust for integrated circuits. Cryptographic hardware, invasive and non-invasive attacks, side-channel attacks, physically unclonable functions (PUFs), true random number generation (TRNG), watermarking of Intellectual Property (IP) blocks, FPGA security, counterfeit detection, hardware Trojan detection and prevention in IP cores and integrated circuits.
Advanced very large scale integrated circuit design, testability, and performance evaluation. Use of industrial VLSI software. Building an advanced CMOS VLSI circuit.
Methods and principles for the automatic identification/authentication of individuals. Technologies include fingerprint, face, and iris biometrics. Additional topics include biometric system design, performance evaluation, multi-modal biometric systems, and biometric system security.
Develop a deep understanding of operating system concepts and systems programming fundamentals and gain hands-on experience in systems programming by using Pthreads as well as implementing Linux device drivers and testing/verifying systems code for deadlock and race-freedom.
Develop an understanding of the principles of computer security, as it crosses layers of abstraction (application, operating system, hardware and network). Students will learn challenges of building secure computer systems with examples and hands-on assignments. Current research on these challenges will be discussed. Students will review and present conference papers.
Fundamental concepts at introductory graduate level in reconfigurable computing based upon advanced technologies in field-programmable logic devices. Topics include general concepts, device architectures, design tools, metrics and kernels, system architectures, and application case studies.
Fundamentals in design and quantitative analysis of modern computer architecture and systems, including instruction set architecture, basic and advanced pipelining, superscalar and VLIW instruction-level parallelism, memory hierarchy, storage, and interconnects.
Overview of machine intelligence and the role of machine learning in variety of real-world problems in areas such as biometrics and adaptive filtering. Probability and statistics to handle uncertain data. Learning models from data in both a supervised and unsupervised fashion. Linear models (e.g., linear discriminant analysis) and non-linear models (e.g., neural networks and support vector machines) for classification. Linear dimensionality reduction (e.g., principal components analysis) and non-linear dimensionality reduction (e.g., manifold learning techniques and self-organizing maps).
This lab course focuses on the hands-on learning of computer hardware security. The course will follow a distinctive hands-on teaching approach using a well-designed set of experiments as learning tool. Students will be able to “hack” a system at different levels and analyze different countermeasures for major hardware attacks.
Fundamentals of hardware security and trust for integrated circuits. Cryptographic hardware, invasive and non-invasive attacks, side-channel attacks, physically unclonable functions (PUFs), true random number generation (TRNG), watermarking of Intellectual Property (IP) blocks, FPGA security, counterfeit ICs, hardware Trojans in IP cores and ICs.
