The department recognizes the fact that a major goal of engineering is to contribute to the welfare of society. This contribution is best made when students have an understanding of the Humanities and the Social Sciences. This understanding is derived from the study of world history; political and economic systems; the ethnic, cultural, and religious diversity of the peoples of the earth; the arts and letters of all cultures; the social and natural sciences; and technology. It is strengthened by a stringent requirement in written communication.

The requirements in the Humanities consist of a minimum of three courses:

• One course in World History
• One course in Fine Arts, Literature, Philosophy, or Religious Studies
• One additional Humanities course

Breadth requirements in the Social Sciences are similarly structured:

• One course from either Economics or Political Science
• One course from Anthropology, Psychology, or Sociology
• One additional Social Science course

In addition, the campus breadth requirement in Ethnic Studies has the option of being incorporated into the above, or standing alone as an additional course.

The engineering curriculum is built on a foundation of courses in mathematics and the basic sciences, which are taken in the first two years at the University. Students acquire a strong grounding in Physics through PHYS 40A, 40B, and 40C. Each of these courses includes an extensive laboratory component. In addition, students obtain a foundation in chemistry through CHEM 1A and 1B, which include laboratories. An additional course in Biology, chosen from an approved list, completes the spectrum of education in the basic sciences.

During the first two years, students take 5 courses in mathematics that cover multivariable differential and integral calculus. These courses, MATH 9A, 9B, 9C, and 10A and 10B, are followed by a course in ordinary differential equations, MATH 46.

Most of the courses in engineering topics are taken after the student has acquired the necessary foundation in mathematics and the basic sciences. However, two lower division courses, EE 001A (Circuit Analysis I) and EE 001B (Circuit Analysis II), are offered in the sophomore year. These two courses introduce basic electrical components and electrical engineering analysis methods. Sophomores also take a course, ME 10 (Statics), through the Mechanical Engineering Department that teaches methods for the equilibrium analysis of structures.

The broad background that is essential for a successful lifelong career in Electrical Engineering is established by the following series of courses. EE 100A (Electronic Circuits I) and EE 100B (Electronic Circuits II) teach the theory of electronic devices and the design and analysis of circuits composed of electronic devices. EE 110A (Signals & Systems I) and EE 110B (Signals & Systems II) teach the concepts of Laplace and Fourier analysis with applications to engineering systems. EE 105 (Modeling & Simulation of Dynamic Systems) teaches state-space and simulation methods for modeling and analyzing dynamic electrical, mechanical, thermal, and fluid systems. EE 115 (Analog Communications) teaches the fundamental theories underlying modern analog communications systems. EE 116 (Electromagnetics) teaches electromagnetic field theory. EE 120A (Logic Design) teaches the theory and methods for the design and analysis of programmable logic devices. EE 120B (Digital Systems) teaches methods and practices for digital system design at the register and processor level. EE 132 (Automatic Control) teaches design and analysis methods for continuous-time control systems. EE 141 (Digital Signal Processing) teaches the theory and methods of digital signal processing.

The following technical electives allow Electrical Engineering students to establish an in depth expertise in focus areas of their choosing: CS 122A, CS 130, CS 143/EE 143, CS 161, CS 168; EE 117, EE 128, EE 133, EE 134, EE 135, EE 136, EE 137, EE 138, EE 139, EE 140, EE 144, EE 146, EE 150, EE 151, EE 152, EE 160.

Most EE courses incorporate design, which addresses real-world problems whose solution requires creativity and consideration of alternatives to achieve stated objectives. Students are introduced to the concepts of design in their sophomore year through EE001A/B.

Design is incorporated into most lower and upper division courses through labs or projects in which students are asked to design a system or a component that satisfies specified constraints. The project is based on material covered in the course. The design may include the following components: a) Converting the design problem into quantifiable statements, b) Formulating the equations that govern the design, c) Converting the equations into computer code, d) Using the code to optimize the design, e) Consideration of realistic constraints, f) Prototype and test, g) Writing a summary report, and h) Presenting results in front of the class. The design project occupies a significant fraction of course time and the final grade, and is usually conducted in teams.

The culmination of the students' design experience is a two-quarter capstone design course, EE175A and B, in which students draw upon various aspects of their previous engineering science and design knowledge to address a meaningful design problem. The first quarter focuses on project (concept) analysis, preliminary evaluation (economical and technical), data and literature collection, and preliminary process design and evaluation. The second quarter (EE 175B) of the capstone design course focuses on the final detailed technical design, fabrication of a prototype, and prototype testing relative to the project specification. The course concludes with a formal oral presentation and written technical report.

At any time during a student's career, they are invited to participate in a circuit prototyping class. This is a non-credit course that teaches soldering, wire wrapping, SMT methods, and printed circuit board (PCB) design and fabrication.

The laboratory courses are based on the ideas that students retain theoretical concepts better when it is reinforced with practical laboratory experience and that students are in the best position to appreciate engineering experiments only when they have familiarity with the underlying theoretical principles. Therefore, EE laboratory courses are directly associated with 23 of 27 EE classes. The only EE classes that do not have a laboratory component are 116, 133, 118, and 150.

Effective use of computers - in the design and analysis of engineering systems - is one of the most important skills required of today's electrical engineers. Efforts are made to utilize computers in all of the electrical engineering courses and laboratories. Students gain three aspects of computer experience:

• Computer programming: An introduction to computer programming is given in CS 10 (Introduction to Computer Science I). This course provides a working knowledge of structured programming in C.
• Computer hardware and interface: Computer architecture, processor design, hardware/software co-design, and hardware interfacing are covered in CS61, EE/CS120A, EE/CS120B, and EE128.
• Use of software packages: The industrial standard MATLAB is used throughout all EE courses. By graduation, students are proficient in the use of MATLAB as an engineering design and analysis tool. The industrial standard PSPICE package is used in all electronic and circuit design classes. The industrial standard XILINX Foundation Tools are used in the 120A/B sequence of logic and digital design classes.

Fundamental and state-of-the-art theory and applications of acquisition, processing, and transmission of digital signals and images over wire, wireless (radio frequency), fiber optics, etc. Example applications include speech processing and recognition, mobile communication using smartphones, fiber optical communication, image enhancement and compression.

Lead Course: EE 141 - Digital Signal Processing 
Technical Electives: 

• EE 115 - Introduction to Communication Systems
• EE 117 - Electromagnetics II
• EE 118 - Radio Frequency Circuit Design
• EE 128 - Sensing and Actuation for Embedded Systems
• EE 146 - Computer Vision
• EE 150 - Digital Communications
• EE 152 - Image Processing
• ENGR 160 - Introduction to Engineering Optimization Techniques

Fundamental theory, design and applications of feedback control systems and autonomous robots capable of making intelligent decisions. Example applications include automotive, marine, aircraft, and satellite control systems; motion planning, control and decision making for autonomous unmanned aerial, ground, surface, and underwater vehicles; autonomous positioning and navigation; advanced robotic manufacturing; and machine vision.

Lead Course: EE 132 - Automatic Control
Technical Electives: 

• EE 128 - Sensing and Actuation for Embedded Systems
• EE 142 - Introduction to Machine Learning and Data Mining
• EE 144 - Introduction to Robotics
• EE 145/ME 145 - Robotic Planning and Kinematics
• EE 146 - Computer Vision
• EE 151 - Introduction to Digital Control
• EE 152 - Image Processing
• ENGR 160 - Introduction to Engineering Optimization Techniques

Theory, design and methodologies of embedded system using microcontrollers, very large scale, nanometer integrated circuits. Example applications include smart home appliances, Internet of Things, microprocessors, analog and mixed signal circuits, RF circuits for cell phones and wireless networks, system-on-chip and wireless networks, system-on-chip.

Lead Course: EE 128 - Sensing and Actuation for Embedded Systems
Technical Electives: 

• EE 135 - Analog Integrated Circuit Layout and Design
• EE 147 - Graphics Processing Unit Computing and Programming 
• EE 165 - Design for Reliability of Integrated Circuits and Systems
• CS 168/EE 168 - Introduction to Very Large Scale Integration (VLSI) Design
• CS 161 - Design and Architecture of Computer Systems
• ENGR 160 - Introduction to Engineering Optimization Techniques

Foundations and applications for acquisition and analysis of multi-modal data, and inference for intelligent pattern recognition, machine learning, and decision making. Examples include, learning from sensor data; pattern recognition, computer vision, and image processing; system approximation and modeling; decision-making under uncertainty; probabilistic robotics; and intelligent transportation systems.

Lead Course: EE 142 - Introduction to Machine Learning and Data Mining
Technical Electives: 

• EE 144 - Introduction to Robotics
• EE 145/ME 145 - Robotic Planning and Kinematics
• EE 146 - Computer Vision
• EE 152 - Image Processing
• ENGR 160- Introduction to Engineering Optimization Techniques

Synthesis and characterization of advanced materials at nanometer scale, theory, design and fabrication of electronic and optoelectronic devices. Example applications include creation of ultra-fast low-power transistors, efficient solar cells for energy generation, high-density memory for smart phones and mobile services, and tiny devices for medical applications.

Lead Course: EE 133 - Solid-State Electronics  
Technical Electives: 

• EE 117 - Electromagnetics II
• EE 136 - Semiconductor Device Processing
• EE 137 - Introduction to Semiconductor Optoelectronic Devices
• EE 138 - Electrical Properties of Materials
• EE 139 - Magnetic Materials
• EE 162 - Introduction to Nanoelectronics

Power electronics, AC and DC power and their conversion, electro-mechanical energy conversion, electric motors, large-scale power generation and transmission systems, long-distance transmission and distribution of electric power, design of motion control drive circuits for robotic and industrial automation systems, and other related topics.

Lead Course: EE 155 - Power System Analysis
Technical Electives:

• EE 117 - Electromagnetics II
• EE 123 - Power Electronics
• EE 128 - Sensing and Actuation for Embedded Systems
• EE 153 - Electric Drives
• ENGR 160 - Introduction to Engineering Optimization Techniques