UCLA Electrical and Computer Engineering: A Comprehensive Course Catalog Overview
The UCLA Samueli School of Engineering offers comprehensive undergraduate programs in Electrical Engineering (EE) and Computer Engineering (CE). These programs provide students with a strong foundation in mathematics, science, and engineering principles, preparing them for careers in a wide range of industries or for advanced studies. The curricula are designed to foster critical thinking, problem-solving, and teamwork skills, ensuring graduates are well-equipped to thrive and lead in their chosen fields.
Electrical Engineering Curriculum
The Electrical Engineering curriculum is structured to provide students with a solid grounding in the fundamentals of the discipline, while also allowing them to specialize in areas of interest. The curriculum emphasizes hands-on learning through laboratory work and design projects, culminating in a capstone design course.
Core Areas of Electrical Engineering
The undergraduate curriculum provides all Electrical Engineering majors with preparation in the mathematical and scientific disciplines that lead to a set of courses that span the fundamentals of the three major departmental areas:
- Signals and Systems: This area focuses on the analysis, design, and implementation of systems that process signals, such as audio, video, and data.
- Circuits and Embedded Systems: This area deals with the design and analysis of electrical circuits and the development of embedded systems, which are computer systems integrated into devices for specific control functions.
- Physical Wave Electronics: This area explores the principles of electromagnetics and their application to the design of devices that generate, transmit, and receive electromagnetic waves.
Specialization and Electives
Students are encouraged to make use of their electrical and computer engineering electives and a two-term capstone design course to pursue deeper knowledge within one of these areas according to their interests, whether for graduate study or preparation for employment.
To further tailor their education, students can choose from a variety of elective courses that allow them to specialize in specific areas of interest. Some popular areas of specialization include:
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- Communications Systems: Studies range from basic wave propagation to point-to-point links up to large-scale networks for both wired and wireless applications.
- Control Systems and Optimization: The study of how to control a variety of systems ranging from a single physical system to continental networks, such as the electrical grid.
- Electromagnetic Systems: Topics include the fundamentals of electromagnetic wave propagation in guided systems and free space, antennas, and radio systems.
- Embedded Computing: The study of compact systems that include collections of integrated circuits that interact with the physical world for purposes such as sensing and control in applications as diverse as appliances, automobiles, and medicine.
- Integrated Circuits: The study of how to achieve large-scale integration of thousands to billions of computational, memory, and sensing elements in single or multichip modules.
- Photonics and Plasma Electronics: The study of how to manipulate light and plasmas to create devices such as those that enable high-speed optical communication systems.
- Signal Processing: The study of how to derive meaningful inferences from measured data, such as speech, images, or other data, after conversion from analog to digital form.
- Simulation and Data Analysis: Studies focus on applications related to the processing of big data for both analog/multimedia and digital sources.
- Solid-State and Microelectromechanical Systems (MEMS) Devices: The study of the nanoscale and microscale devices that are the base of modern computation and sensing systems.
Capstone Design Experience
The Electrical Engineering major is a designated capstone major. Undergraduate students complete a design course in which they integrate their knowledge of the discipline and engage in creative design within realistic and professional constraints. Students apply their knowledge and expertise gained in previous mathematics, science, and engineering coursework.
Educational Objectives
Undergraduate education in the department provides students with:
- Fundamental knowledge in mathematics, physical sciences, and electrical engineering.
- The opportunity to specialize in specific areas of interest or career aspiration.
- Intensive training in problem-solving, laboratory skills, and design skills.
- A well-rounded education that includes communication skills, the ability to function well on a team, an appreciation for ethical behavior, and the ability to engage in lifelong learning. This education is meant to prepare students to thrive and to lead.
Computer Engineering Curriculum
The Computer Engineering curriculum, jointly administered by the Computer Science and Electrical and Computer Engineering departments, focuses on the design and implementation of computer systems, encompassing both hardware and software aspects. The curriculum emphasizes the integration of theory and practice, preparing students for careers in the rapidly evolving field of computing.
Core Areas of Computer Engineering
The undergraduate curriculum provides all computer engineering students with preparation in the mathematical and scientific disciplines that lead to a set of courses that span the fundamentals of the discipline in the major areas of data science and embedded networked systems. These collectively provide an understanding of many inventions of importance to our society, such as the Internet of things, human-cyber-physical systems, mobile/wearable/implantable systems, robotic systems, and more generally smart systems at all scales in diverse spheres. The design of hardware, software, and algorithmic elements of such systems represents an already dominant and rapidly growing part of the computer engineering profession.
Specialization Tracks
Students in Computer Engineering can choose to specialize in one of the following tracks:
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- Networked Embedded Systems: This track targets two related trends that have been a significant driver of computing, namely stand-alone embedded devices becoming networked and coupled to physical systems, and the Internet evolving toward a network of things (the IoT). These may broadly be classified as cyber physical systems, and includes a broad category of systems such as smart buildings, autonomous vehicles, and robots, which interact with each other and other systems.
- Data Science: This track targets the trend toward the disruptive impact on computing systems, both at the edge and in the cloud, of massive amounts of sensory data being collected, shared, processed, and used for decision making and control. Application domains such as health, transportation, energy, etc. are being transformed by the abilities of inference-making and decision-making from sensory data that is pervasive, continual, and rich.
Students are also free to design ad hoc tracks.
Capstone Design Experience
The Computer Engineering major is a designated capstone major that is jointly administered by the Computer Science, and Electrical and Computer Engineering, departments. Undergraduate students complete a design course in which they integrate their knowledge of the discipline and engage in creative design within realistic and professional constraints. Students apply their knowledge and expertise gained in previous mathematics, science, and engineering coursework.
Interdisciplinary Opportunities
The technical breadth area requirement provides an opportunity to combine elective courses in electrical and computer engineering and computer science with those from another UCLA Samueli major to produce a specialization in an interdisciplinary domain. This allows students to broaden their knowledge and skills, preparing them for careers that require expertise in multiple fields. Some examples of interdisciplinary domains include:
- Bioengineering and Informatics (BI): Refers to the design of biomedical devices and the analysis of data derived from such devices and instruments.
- Computer Engineering (CE): Concentrates on the part of the hardware/software stack related to the design of new processors and the operation of embedded systems.
- Cyber Physical Systems (CPS): Refer to networked systems that include sensors and actuators that interact with the physical world. They blend embedded systems with networking and control and include, for example, robotic systems and the Internet of things (IoT).
Course Examples
The UCLA Electrical and Computer Engineering course catalog includes a wide range of courses, from introductory to advanced levels. Here are a few examples:
- Electrical Engineering 1: Undergraduate Seminar: Introduction by faculty members and industry lecturers to electrical engineering disciplines through current and emerging applications of autonomous systems and vehicles, biomedical devices, aerospace electronic systems, consumer products, data science, and entertainment products (amusement rides, etc.), as well as energy generation, storage, and transmission.
- Electrical Engineering 2: Physics for Electrical Engineers: Introduction to concepts of modern physics necessary to understand solid-state devices, including elementary quantum theory, Fermi energies, and concepts of electrons in solids. Discussion of electrical properties of semiconductors leading to operation of junction devices.
- Electrical Engineering 3: Introduction to Electrical Engineering: Introduction to field of electrical engineering. Basic circuits techniques with application to explanation of electrical engineering inventions such as telecommunications, electrical grid, automatic computing and control, and enabling device technology.
- Electrical Engineering 10: Circuit Theory I: Introduction to linear circuit analysis. Resistive circuits, capacitors, inductors and ideal transformers, Kirchhoff laws, node and loop analysis, first-order circuits, second-order circuits, Thevenin and Norton theorem, sinusoidal steady state.
- Electrical Engineering M16: Logic Design of Digital Systems: Introduction to digital systems. Specification and implementation of combinational and sequential systems. Standard logic modules and programmable logic arrays.
- Electrical Engineering 100: Electrical and Electronic Circuits: Electrical quantities, linear circuit elements, circuit principles, signal waveforms, transient and steady state circuit behavior, semiconductor diodes and transistors, small signal models, and operational amplifiers.
- Electrical Engineering 101A: Engineering Electromagnetics: Electromagnetic field concepts, waves and phasors, transmission lines and Smith chart, transient responses, vector analysis, introduction to Maxwell equations, static and quasistatic electric and magnetic fields.
- Electrical Engineering 102: Systems and Signals: Elements of differential equations, first and second-order equations, variation of parameters method and method of undetermined coefficients, existence and uniqueness. Systems: input/output description, linearity, time-in-variance, and causality.
- Electrical Engineering 110: Circuit Theory II: Sinusoidal excitation and phasors, AC steady state analysis, AC steady state power, network functions, poles and zeros, frequency response, mutual inductance, ideal transformer, application of Laplace transforms to circuit analysis.
- Electrical Engineering 113: Digital Signal Processing: Relationship between continuous-time and discrete-time signals. Z-transform. Discrete Fourier transform. Fast Fourier transform. Structures for digital filtering. Introduction to digital filter design techniques.
- Electrical Engineering 115A: Analog Electronic Circuits I: Review of physics and operation of diodes and bipolar and MOS transistors. Equivalent circuits and models of semiconductor devices. Analysis and design of single-stage amplifiers. DC biasing circuits. Small-signal analysis. Operational amplifier systems.
- Electrical Engineering M116C: Computer Systems Architecture: Computer system organization and design, implementation of CPU datapath and control, instruction set design, memory hierarchy (caches, main memory, virtual memory) organization and management, input/output subsystems (bus structures, interrupts, DMA), performance evaluation, pipelined processors.
Minor in Data Science
The Data Science minor is intended to expose students to the entire data science life cycle from both foundational and application perspectives. The foundational courses provide the engineering skills to collect, cleanse, and store data; analyze and draw inference from data; and take action and make decisions.
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To apply for the minor, students must have an overall grade-point average of 3.0 or better, have completed or be in the process of completing in the present quarter the two lower-division required courses with the grade B- or better, and file a petition through Message Center. Select two courses from the following list. Electrical and Computer Engineering 183DA and 183DB must both be taken to satisfy the requirement. Each minor course must be taken for a letter grade, and student must have a minimum grade of C in each and an overall grade-point average of 2.0 or better in the minor.
Important Notice
The UCLA General Catalog is published annually in PDF and HTML formats. Every effort has been made to ensure the accuracy of the information presented in the UCLA General Catalog. However, all courses, course descriptions, instructor designations, curricular degree requirements, and fees described herein are subject to change or deletion without notice. Consult this Catalog for the most current, officially approved courses and curricula. Other information about UCLA may be found in materials produced by the schools of Arts and Architecture; Dentistry; Education and Information Studies; Engineering and Applied Science; Law; Management; Medicine; Music; Nursing; Public Affairs; Public Health; and Theater, Film, and Television.
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