Hands-On Learning

EEC 1 is a 1-unit project-based course for first-year students. In their first quarter at UC Davis students in this class are introduced to a range of topics within electrical and computer engineering including embedded systems, physical electronics, circuits, communications, signal processing and systems design. 

EEC 10 is a 4-unit project-based course for sophomore students. In this class, students are briefly introduced to several of the topics that will be covered in detail in their upcoming junior and senior years. At the same time, they design a complete system as the course project that requires system-level understanding about interrelation of different fields such as analog circuits, digital systems, signal processing, etc. 

EE-Emerge focuses on ECE students in their junior year, in particular underrepresented-minority and first-generation students. EE-Emerge is structured around a three-quarter sequence that leads up to the demonstration of team projects at Picnic Day. EE-Emerge is supported by Texas Instruments, a global leader in semiconductor and integrated circuit technologies. 

The EEC 134 course was created to satisfy the need for a senior project course for students who are interested in high-frequency electronic systems. The two-quarter-long course emphasizes system level design concepts and strives to provide a hands-on experience. 

EEC 136 is a senior capstone design project course focused on electronic systems. Teams of 3-4 students typically combine sensors, a microcontroller, and a wireless interface to create a system that accomplishes a specific task. Projects vary from year to year and can be developed by the students, are suggested by faculty in the Department of Electrical and Computer Engineering or other departments, or by mentors from industry.

The course involves the design, analysis, implementation, and testing of an application specific processor (ASP) using a modern, large-scale field programmable gate array (FPGA). The team is given a computationally intensive problem and is required to investigate algorithms for solving the problem that can be efficiently implemented on an FPGA.

In EEC193 A/B, students will be introduced to challenges involved in designing and implementing components that are critical to data-driven and artificial intelligence (AI)-based control systems, including but not limited to data preprocessing, sensor fusion, computer vision (semantic segmentation, objection detection), machine learning (ML) based classification, and learning-based control systems. 

The students will be provided with a radio-controlled car chassis and the rules for the contest. The objective of the project is to design and construct an autonomous race car that can negotiate a preset course in the shortest time possible.