Computer Science, Exams of Theory of Computation

Download Computer Science and more Exams Theory of Computation in PDF only on Docsity! Computer Science 1 Computer Science The Department of Electrical Engineering and Computer Sciences (EECS) offers two graduate programs in Computer Science: the Master of Science (MS), and the Doctor of Philosophy (PhD). Master of Science (MS) The Master of Science (MS) emphasizes research preparation and experience and, for most students, is a chance to lay the groundwork for pursuing a PhD. Doctor of Philosophy (PhD) The Berkeley PhD in EECS combines coursework and original research with some of the finest EECS faculty in the US, preparing for careers in academia or industry. Our alumni (https://eecs.berkeley.edu/people/ alumni/cs-distinguished-alumni/) have gone on to hold amazing positions around the world. Admission to the University Minimum Requirements for Admission The following minimum requirements apply to all graduate programs and will be verified by the Graduate Division: 1. A bachelor’s degree or recognized equivalent from an accredited institution; 2. A grade point average of B or better (3.0); 3. If the applicant has completed a basic degree from a country or political entity (e.g., Quebec) where English is not the official language, adequate proficiency in English to do graduate work, as evidenced by a TOEFL score of at least 90 on the iBT test, 570 on the paper-and-pencil test, or an IELTS Band score of at least 7 on a 9-point scale (note that individual programs may set higher levels for any of these); and 4. Sufficient undergraduate training to do graduate work in the given field. Applicants Who Already Hold a Graduate Degree The Graduate Council views academic degrees not as vocational training certificates, but as evidence of broad training in research methods, independent study, and articulation of learning. Therefore, applicants who already have academic graduate degrees should be able to pursue new subject matter at an advanced level without the need to enroll in a related or similar graduate program. Programs may consider students for an additional academic master’s or professional master’s degree only if the additional degree is in a distinctly different field. Applicants admitted to a doctoral program that requires a master’s degree to be earned at Berkeley as a prerequisite (even though the applicant already has a master’s degree from another institution in the same or a closely allied field of study) will be permitted to undertake the second master’s degree, despite the overlap in field. The Graduate Division will admit students for a second doctoral degree only if they meet the following guidelines: 1. Applicants with doctoral degrees may be admitted for an additional doctoral degree only if that degree program is in a general area of knowledge distinctly different from the field in which they earned their original degree. For example, a physics PhD could be admitted to a doctoral degree program in music or history; however, a student with a doctoral degree in mathematics would not be permitted to add a PhD in statistics. 2. Applicants who hold the PhD degree may be admitted to a professional doctorate or professional master’s degree program if there is no duplication of training involved. Applicants may apply only to one single degree program or one concurrent degree program per admission cycle. Required Documents for Applications 1. Transcripts: Applicants may upload unofficial transcripts with your application for the departmental initial review. Unofficial transcripts must contain specific information including the name of the applicant, name of the school, all courses, grades, units, & degree conferral (if applicable). 2. Letters of recommendation: Applicants may request online letters of recommendation through the online application system. Hard copies of recommendation letters must be sent directly to the program, by the recommender, not the Graduate Admissions. 3. Evidence of English language proficiency: All applicants who have completed a basic degree from a country or political entity in which the official language is not English are required to submit official evidence of English language proficiency. This applies to institutions from Bangladesh, Burma, Nepal, India, Pakistan, Latin America, the Middle East, the People’s Republic of China, Taiwan, Japan, Korea, Southeast Asia, most European countries, and Quebec (Canada). However, applicants who, at the time of application, have already completed at least one year of full-time academic course work with grades of B or better at a US university may submit an official transcript from the US university to fulfill this requirement. The following courses will not fulfill this requirement: • courses in English as a Second Language, • courses conducted in a language other than English, • courses that will be completed after the application is submitted, and • courses of a non-academic nature. Applicants who have previously applied to Berkeley must also submit new test scores that meet the current minimum requirement from one of the standardized tests. Official TOEFL score reports must be sent directly from Educational Test Services (ETS). The institution code for Berkeley is 4833 for Graduate Organizations. Official IELTS score reports must be sent electronically from the testing center to University of California, Berkeley, Graduate Division, Sproul Hall, Rm 318 MC 5900, Berkeley, CA 94720. TOEFL and IELTS score reports are only valid for two years prior to beginning the graduate program at UC Berkeley. Note: score reports can not expire before the month of June. Where to Apply Visit the Berkeley Graduate Division application page (http:// grad.berkeley.edu/admissions/apply/). 2 Computer Science Admission to the Program The following items are required for admission to the Berkeley EECS MS/ PhD program in addition to the University’s general graduate admissions requirements: 1. Statement of Purpose: Why are you applying for this program? What will do you plan to accomplish during this degree program? What do you want to do afterward, and how will this degree help you reach that goal? 2. Personal History Statement: What experiences from your past made you decide to go into this field? And how will your personal history help you succeed in this program and your future goals? 3. GPA: If you attended a university outside the USA, please leave the GPA section blank. 4. Resume: Please also include a full resume/CV listing your experience and education. Complete the online UC Berkeley graduate application: 1. Start your application through this link (http:// www.grad.berkeley.edu/), and fill in each relevant page. 2. Upload the materials above, and send the recommender links several weeks prior to the application deadline to give your recommenders time to submit their letters. Normative Time Requirements Normative time in the EECS department is between 5.5-6 years for the doctoral program. Time to Advancement Curriculum The faculty of the College of Engineering recommends a minimum number of courses taken while in graduate standing. The total minimum is 24 units of coursework, taken for a letter grade and not including 397, 298, 299, 301, 375 and 602. 12 200-level units from one major field within EECS, with a 3.5 grade point average 12 6 units from one minor field within EECS, with a 3.0 grade point average and at least one 200-level course 6 6 100 and 200-level units from one minor field outside EECS, with a 3.0 grade point average 6 Preliminary Exams The EECS preliminary requirement consists of two components. Oral Examination The oral exam serves an advisory role in a student's graduate studies program, giving official feedback from the exam committee of faculty members. Students must be able to demonstrate an integrated grasp of the exam area's body of knowledge in an unstructured framework. Students must pass the oral portion of the preliminary exam within their first two attempts. A third attempt is possible with a petition of support from the student's faculty adviser and final approval by the prelim committee chair. Failure to pass the oral portion of the preliminary exam will result in the student being ineligible to complete the PhD program. The examining committee awards a score in the range of 0-10. The minimum passing score is 6.0. Breadth Courses The breadth courses ensure that students have exposure to areas outside of their concentration. It is expected that students will achieve high academic standards in these courses. CS students must complete courses from three of the following areas, passing each with at least a B+. One course must be selected from the Theory, AI, or Graphics/HCI group; and one course must be selected from the Programming, Systems, or Architecture/VLSI group1. Theory COMPSCI 270 Combinatorial Algorithms and Data Structures 3 COMPSCI 271 Randomness and Computation 3 COMPSCI 273 Foundations of Parallel Computation 3 COMPSCI 274 Computational Geometry 3 COMPSCI 276 Cryptography 3 AI COMPSCI C280 Computer Vision 3 COMPSCI C281A Statistical Learning Theory 3 COMPSCI C281B Advanced Topics in Learning and Decision Making 3 COMPSCI 287 Advanced Robotics 3 COMPSCI 288 Natural Language Processing 4 COMPSCI 289A Introduction to Machine Learning 4 Graphics/HCI COMPSCI 260B Human-Computer Interaction Research 3 Programming COMPSCI 263 Design of Programming Languages 3 COMPSCI 264 Implementation of Programming Languages 4 COMPSCI 265 Compiler Optimization and Code Generation 3 COMPSCI C267 Applications of Parallel Computers 3 EECS 219C Formal Methods: Specification, Verification, and Synthesis 3 Systems COMPSCI 261 Security in Computer Systems 3 COMPSCI 261N Internet and Network Security 4 COMPSCI 262A Advanced Topics in Computer Systems 4 COMPSCI 262B Advanced Topics in Computer Systems 3 COMPSCI 268 Computer Networks 3 COMPSCI 286B Implementation of Data Base Systems 3 Architecture/VLSI COMPSCI 250 VLSI Systems Design 4 EECS 251A Introduction to Digital Design and Integrated Circuits 3 EECS 251LA Introduction to Digital Design and Integrated Circuits Lab 2 EECS 251LB Introduction to Digital Design and Integrated Circuits Lab 2 1 COMPSCI 260B, COMPSCI 263, and EL ENG 219C cannot be used to fulfill this constraint, though they can be used to complete one of the three courses. Qualifying Examination (QE) The QE is an important checkpoint meant to show that a student is on a promising research track toward the PhD degree. It is a University Computer Science 5 EECS C206B Robotic Manipulation and Interaction 4 Units Terms offered: Spring 2023 This course is a sequel to EECS C106A/206A, which covers kinematics, dynamics and control of a single robot. This course will cover dynamics and control of groups of robotic manipulators coordinating with each other and interacting with the environment. Concepts will include an introduction to grasping and the constrained manipulation, contacts and force control for interaction with the environment. We will also cover active perception guided manipulation, as well as the manipulation of non-rigid objects. Throughout, we will emphasize design and human-robot interactions, and applications to applications in manufacturing, service robotics, tele-surgery, and locomotion. Robotic Manipulation and Interaction: Read More [+] Rules & Requirements Prerequisites: Students are expected to have taken EECS C106A / BioE C106A / ME C106A / ME C206A/ EECS C206A or an equivalent course. A strong programming background, knowledge of Python and Matlab, and some coursework in feedback controls (such as EE C128 / ME C134) are also useful. Students who have not taken EECS C106A / BioE C106A / ME C106A / ME C206A/ EECS C206A should have a strong programming background, knowledge of Python and Matlab, and exposure to linear algebra, and Lagrangian dynamics Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture, 1 hour of discussion, and 3 hours of laboratory per week Additional Details Subject/Course Level: Electrical Engin and Computer Sci/Graduate Grading: Letter grade. Instructors: Bajcsy, Sastry Formerly known as: Electrical Engin and Computer Sci 206B Also listed as: MEC ENG C206B Robotic Manipulation and Interaction: Read Less [-] EECS 208 Computational Principles for High- dimensional Data Analysis 4 Units Terms offered: Fall 2022, Fall 2021 Introduction to fundamental geometric and statistical concepts and principles of low-dimensional models for high-dimensional signal and data analysis, spanning basic theory, efficient algorithms, and diverse real-world applications. Systematic study of both sampling complexity and computational complexity for sparse, low-rank, and low-dimensional models – including important cases such as matrix completion, robust principal component analysis, dictionary learning, and deep networks. Computational Principles for High-dimensional Data Analysis: Read More [+] Rules & Requirements Prerequisites: The following courses are recommended undergraduate linear algebra (Math 110), statistics (Stat 134), and probability (EE126). Back-ground in signal processing (ELENG 123), optimization (ELENG C227T), machine learning (CS189/289), and computer vision (COMPSCI C280) may allow you to appreciate better certain aspects of the course material, but not necessary all at once. The course is open to senior undergraduates, with consent from the instructor Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture and 1 hour of discussion per week Additional Details Subject/Course Level: Electrical Engin and Computer Sci/Graduate Grading: Letter grade. Instructor: Ma Computational Principles for High-dimensional Data Analysis: Read Less [-] 6 Computer Science EECS 219C Formal Methods: Specification, Verification, and Synthesis 3 Units Terms offered: Spring 2023, Spring 2022, Spring 2021 Introduction to the theory and practice of formal methods for the design and analysis of systems, with a focus on algorithmic techniques. Covers selected topics in computational logic and automata theory including modeling and specification formalisms, temporal logics, satisfiability solving, model checking, synthesis, learning, and theorem proving. Applications to software and hardware design, cyber-physical systems, robotics, computer security, and other areas will be explored as time permits. Formal Methods: Specification, Verification, and Synthesis: Read More [+] Rules & Requirements Prerequisites: Graduate standing or consent of instructor; COMPSCI 170 is recommended Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture per week Additional Details Subject/Course Level: Electrical Engin and Computer Sci/Graduate Grading: Letter grade. Instructor: Seshia Formerly known as: Electrical Engineering 219C Formal Methods: Specification, Verification, and Synthesis: Read Less [-] EECS 225A Statistical Signal Processing 3 Units Terms offered: Spring 2023, Fall 2021, Fall 2020 This course connects classical statistical signal processing (Hilbert space filtering theory by Wiener and Kolmogorov, state space model, signal representation, detection and estimation, adaptive filtering) with modern statistical and machine learning theory and applications. It focuses on concrete algorithms and combines principled theoretical thinking with real applications. Statistical Signal Processing: Read More [+] Rules & Requirements Prerequisites: EL ENG 120 and EECS 126 Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture per week Additional Details Subject/Course Level: Electrical Engin and Computer Sci/Graduate Grading: Letter grade. Instructors: Jiao, Waller Formerly known as: Electrical Engineering 225A Statistical Signal Processing: Read Less [-] EECS 225B Digital Image Processing 3 Units Terms offered: Fall 2022, Fall 2020, Spring 2020 This course deals with computational methods as applied to digital imagery. It focuses on image sensing and acquisition, image sampling and quantization; spatial transformation, linear and nonlinear filtering; introduction to convolutional neural networks, and GANs; applications of deep learning methods to image processing problems; image enhancement, histogram equalization, image restoration, Weiner filtering, tomography, image reconstruction from projections and partial Fourier information, Radon transform, multiresolution analysis, continuous and discrete wavelet transform and computation, subband coding, image and video compression, sparse signal approximation, dictionary techniques, image and video compression standards, and more. Digital Image Processing: Read More [+] Rules & Requirements Prerequisites: Basic knowledge of signals and systems, convolution, and Fourier Transform Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture per week Additional Details Subject/Course Level: Electrical Engin and Computer Sci/Graduate Grading: Letter grade. Instructor: Zakhor Formerly known as: Electrical Engineering 225B Digital Image Processing: Read Less [-] EECS 227AT Optimization Models in Engineering 4 Units Terms offered: Spring 2023, Fall 2022, Spring 2022 This course offers an introduction to optimization models and their applications, ranging from machine learning and statistics to decision- making and control, with emphasis on numerically tractable problems, such as linear or constrained least-squares optimization. Optimization Models in Engineering: Read More [+] Rules & Requirements Prerequisites: MATH 54 or consent of instructor Credit Restrictions: Students will receive no credit for EECS 227AT after taking EECS 127 or Electrical Engineering 127/227AT. Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture and 1 hour of discussion per week Additional Details Subject/Course Level: Electrical Engin and Computer Sci/Graduate Grading: Letter grade. Instructor: El Ghaoui Formerly known as: Electrical Engineering 227AT Optimization Models in Engineering: Read Less [-] Computer Science 7 EECS 251A Introduction to Digital Design and Integrated Circuits 3 Units Terms offered: Spring 2023, Fall 2022, Spring 2022 An introduction to digital circuit and system design. The material provides a top-down view of the principles, components, and methodologies for large scale digital system design. The underlying CMOS devices and manufacturing technologies are introduced, but quickly abstracted to higher levels to focus the class on design of larger digital modules for both FPGAs (field programmable gate arrays) and ASICs (application specific integrated circuits). The class includes extensive use of industrial grade design automation and verification tools for assignments, labs, and projects. Introduction to Digital Design and Integrated Circuits: Read More [+] Objectives & Outcomes Course Objectives: The Verilog hardware description language is introduced and used. Basic digital system design concepts, Boolean operations/combinational logic, sequential elements and finite-state- machines, are described. Design of larger building blocks such as arithmetic units, interconnection networks, input/output units, as well as memory design (SRAM, Caches, FIFOs) and integration are also covered. Parallelism, pipelining and other micro-architectural optimizations are introduced. A number of physical design issues visible at the architecture level are covered as well, such as interconnects, power, and reliability. Student Learning Outcomes: Although the syllabus is the same as EECS151, the assignments and exams for EECS251A will have harder problems that test deeper understanding expected from a graduate level course. Rules & Requirements Prerequisites: EECS 16A and EECS 16B; COMPSCI 61C; and recommended: EL ENG 105. Students must enroll concurrently in at least one the laboratory flavors EECS 251LA or EECS 251LB. Students wishing to take a second laboratory flavor next term can sign-up only for that laboratory section and receive a letter grade. The prerequisite for “Lab-only” enrollment that term will be EECS 251A from previous terms Credit Restrictions: Students must enroll concurrently in at least one the laboratory flavors Electrical Engineering and Computer Science 251LA or Electrical Engineering and Computer Science 251LB. Students wishing to take a second laboratory flavor next term can sign-up only for that laboratory section and receive a letter grade. The pre-requisite for “Lab- only” enrollment that term will be Electrical Engineering and Computer Science 251A from previous terms. Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture and 1 hour of discussion per week Additional Details Subject/Course Level: Electrical Engin and Computer Sci/Graduate Grading: Letter grade. Instructors: Stojanovic, Wawrzynek Formerly known as: Electrical Engineering 241A Introduction to Digital Design and Integrated Circuits: Read Less [-] EECS 251B Advanced Digital Integrated Circuits and Systems 4 Units Terms offered: Spring 2023, Spring 2022 This course aims to convey a knowledge of advanced concepts of digital circuit and system-on-a-chip design in state-of-the-art technologies. Emphasis is on the circuit and system design and optimization for both energy efficiency and high performance for use in a broad range of applications, from edge computing to datacenters. Special attention will be devoted to the most important challenges facing digital circuit designers in the coming decade. The course is accompanied with practical laboratory exercises that introduce students to modern tool flows. Advanced Digital Integrated Circuits and Systems: Read More [+] Rules & Requirements Prerequisites: Introduction to Digital Design and Integrated Circuits, EECS151 (taken with either EECS151LA or EECS151LB lab) or EECS251A (taken with either EECS251LA or EECS251LB lab) Credit Restrictions: Students will receive no credit for EECS 251B after completing COMPSCI 250, or EL ENG 241B. Hours & Format Fall and/or spring: 15 weeks - 4 hours of lecture and 1 hour of discussion per week Additional Details Subject/Course Level: Electrical Engin and Computer Sci/Graduate Grading: Letter grade. Instructors: Nikoli#, Shao, Wawrzynek, Asanovi#, Stojanovi#, Seshia Advanced Digital Integrated Circuits and Systems: Read Less [-] 10 Computer Science COMPSCI 252A Graduate Computer Architecture 4 Units Terms offered: Spring 2023, Spring 2022, Spring 2021 Graduate survey of contemporary computer organizations covering: early systems, CPU design, instruction sets, control, processors, busses, ALU, memory, I/O interfaces, connection networks, virtual memory, pipelined computers, multiprocessors, and case studies. Term paper or project is required. Graduate Computer Architecture: Read More [+] Rules & Requirements Prerequisites: COMPSCI 61C Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture and 2 hours of discussion per week Additional Details Subject/Course Level: Computer Science/Graduate Grading: Letter grade. Instructors: Asanovi#, Kubiatowicz Formerly known as: Computer Science 252 Graduate Computer Architecture: Read Less [-] COMPSCI 260A User Interface Design and Development 4 Units Terms offered: Spring 2023, Fall 2020, Spring 2020 The design, implementation, and evaluation of user interfaces. User- centered design and task analysis. Conceptual models and interface metaphors. Usability inspection and evaluation methods. Analysis of user study data. Input methods (keyboard, pointing, touch, tangible) and input models. Visual design principles. Interface prototyping and implementation methodologies and tools. Students will develop a user interface for a specific task and target user group in teams. User Interface Design and Development: Read More [+] Rules & Requirements Prerequisites: COMPSCI 61B, COMPSCI 61BL, or consent of instructor Credit Restrictions: Students will receive no credit for Computer Science 260A after taking Computer Science 160. Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture and 1 hour of discussion per week Additional Details Subject/Course Level: Computer Science/Graduate Grading: Letter grade. Instructors: Agrawala, Canny, Hartmann User Interface Design and Development: Read Less [-] COMPSCI 260B Human-Computer Interaction Research 3 Units Terms offered: Fall 2017 This course is a broad introduction to conducting research in Human- Computer Interaction. Students will become familiar with seminal and recent literature; learn to review and critique research papers; re- implement and evaluate important existing systems; and gain experience in conducting research. Topics include input devices, computer-supported cooperative work, crowdsourcing, design tools, evaluation methods, search and mobile interfaces, usable security, help and tutorial systems. Human-Computer Interaction Research: Read More [+] Rules & Requirements Prerequisites: COMPSCI 160 recommended, or consent of instructor Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture per week Additional Details Subject/Course Level: Computer Science/Graduate Grading: Letter grade. Instructor: Hartmann Human-Computer Interaction Research: Read Less [-] COMPSCI 261 Security in Computer Systems 3 Units Terms offered: Spring 2021, Fall 2018, Fall 2017 Graduate survey of modern topics in computer security, including protection, access control, distributed access security, firewalls, secure coding practices, safe languages, mobile code, and case studies from real-world systems. May also cover cryptographic protocols, privacy and anonymity, and/or other topics as time permits. Security in Computer Systems: Read More [+] Rules & Requirements Prerequisites: COMPSCI 162 Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture per week Additional Details Subject/Course Level: Computer Science/Graduate Grading: Letter grade. Instructors: D. Song, Wagner Security in Computer Systems: Read Less [-] Computer Science 11 COMPSCI 261N Internet and Network Security 4 Units Terms offered: Spring 2020, Fall 2016, Spring 2015 Develops a thorough grounding in Internet and network security suitable for those interested in conducting research in the area or those more broadly interested in security or networking. Potential topics include denial-of-service; capabilities; network intrusion detection/prevention; worms; forensics; scanning; traffic analysis; legal issues; web attacks; anonymity; wireless and networked devices; honeypots; botnets; scams; underground economy; attacker infrastructure; research pitfalls. Internet and Network Security: Read More [+] Rules & Requirements Prerequisites: EL ENG 122 or equivalent; and COMPSCI 161 or familiarity with basic security concepts Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture per week Additional Details Subject/Course Level: Computer Science/Graduate Grading: Letter grade. Instructor: Paxson Internet and Network Security: Read Less [-] COMPSCI 262A Advanced Topics in Computer Systems 4 Units Terms offered: Fall 2022, Fall 2021, Fall 2020 Graduate survey of systems for managing computation and information, covering a breadth of topics: early systems; volatile memory management, including virtual memory and buffer management; persistent memory systems, including both file systems and transactional storage managers; storage metadata, physical vs. logical naming, schemas, process scheduling, threading and concurrency control; system support for networking, including remote procedure calls, transactional RPC, TCP, and active messages; security infrastructure; extensible systems and APIs; performance analysis and engineering of large software systems. Homework assignments, exam, and term paper or project required. Advanced Topics in Computer Systems: Read More [+] Rules & Requirements Prerequisites: COMPSCI 162 and entrance exam Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture per week Additional Details Subject/Course Level: Computer Science/Graduate Grading: Letter grade. Instructors: Brewer, Hellerstein Formerly known as: 262 Advanced Topics in Computer Systems: Read Less [-] COMPSCI 262B Advanced Topics in Computer Systems 3 Units Terms offered: Spring 2020, Spring 2009, Fall 2008 Continued graduate survey of large-scale systems for managing information and computation. Topics include basic performance measurement; extensibility, with attention to protection, security, and management of abstract data types; index structures, including support for concurrency and recovery; parallelism, including parallel architectures, query processing and scheduling; distributed data management, including distributed and mobile file systems and databases; distributed caching; large-scale data analysis and search. Homework assignments, exam, and term paper or project required. Advanced Topics in Computer Systems: Read More [+] Rules & Requirements Prerequisites: COMPSCI 262A Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture per week Additional Details Subject/Course Level: Computer Science/Graduate Grading: Letter grade. Instructors: Brewer, Culler, Hellerstein, Joseph Advanced Topics in Computer Systems: Read Less [-] COMPSCI 263 Design of Programming Languages 3 Units Terms offered: Fall 2021, Fall 2019, Spring 2019 Selected topics from: analysis, comparison, and design of programming languages, formal description of syntax and semantics, advanced programming techniques, structured programming, debugging, verification of programs and compilers, and proofs of correctness. Design of Programming Languages: Read More [+] Rules & Requirements Prerequisites: COMPSCI 164 Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture and 1 hour of discussion per week Additional Details Subject/Course Level: Computer Science/Graduate Grading: Letter grade. Instructor: Necula Design of Programming Languages: Read Less [-] 12 Computer Science COMPSCI 264 Implementation of Programming Languages 4 Units Terms offered: Fall 2021, Spring 2011, Spring 2010 Compiler construction. Lexical analysis, syntax analysis. Semantic analysis code generation and optimization. Storage management. Run- time organization. Implementation of Programming Languages: Read More [+] Rules & Requirements Prerequisites: COMPSCI 164; COMPSCI 263 recommended Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture, 1 hour of discussion, and 6 hours of laboratory per week Additional Details Subject/Course Level: Computer Science/Graduate Grading: Letter grade. Instructor: Bodik Implementation of Programming Languages: Read Less [-] COMPSCI 265 Compiler Optimization and Code Generation 3 Units Terms offered: Fall 2009, Spring 2003, Spring 2000 Table-driven and retargetable code generators. Register management. Flow analysis and global optimization methods. Code optimization for advanced languages and architectures. Local code improvement. Optimization by program transformation. Selected additional topics. A term paper or project is required. Compiler Optimization and Code Generation: Read More [+] Rules & Requirements Prerequisites: COMPSCI 164 Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture per week Additional Details Subject/Course Level: Computer Science/Graduate Grading: Letter grade. Instructor: Sen Compiler Optimization and Code Generation: Read Less [-] COMPSCI C267 Applications of Parallel Computers 3 - 4 Units Terms offered: Spring 2023, Spring 2022, Spring 2021 Models for parallel programming. Overview of parallelism in scientific applications and study of parallel algorithms for linear algebra, particles, meshes, sorting, FFT, graphs, machine learning, etc. Survey of parallel machines and machine structures. Programming shared- and distributed-memory parallel computers, GPUs, and cloud platforms. Parallel programming languages, compilers, libraries and toolboxes. Data partitioning techniques. Techniques for synchronization and load balancing. Detailed study and algorithm/program development of medium sized applications. Applications of Parallel Computers: Read More [+] Rules & Requirements Prerequisites: No formal pre-requisites. Prior programming experience with a low-level language such as C, C++, or Fortran is recommended but not required. CS C267 is intended to be useful for students from many departments and with different backgrounds, although we will assume reasonable programming skills in a conventional (non-parallel) language, as well as enough mathematical skills to understand the problems and algorithmic solutions presented Repeat rules: Course may be repeated for credit without restriction. Hours & Format Fall and/or spring: 15 weeks - 3-3 hours of lecture and 1-1 hours of laboratory per week Additional Details Subject/Course Level: Computer Science/Graduate Grading: Letter grade. Instructors: Demmel, Yelick Also listed as: ENGIN C233 Applications of Parallel Computers: Read Less [-] Computer Science 15 COMPSCI C280 Computer Vision 3 Units Terms offered: Spring 2023, Spring 2022, Spring 2021 Paradigms for computational vision. Relation to human visual perception. Mathematical techniques for representing and reasoning, with curves, surfaces and volumes. Illumination and reflectance models. Color perception. Image segmentation and aggregation. Methods for bottom- up three dimensional shape recovery: Line drawing analysis, stereo, shading, motion, texture. Use of object models for prediction and recognition. Computer Vision: Read More [+] Rules & Requirements Prerequisites: MATH 1A; MATH 1B; MATH 53; and MATH 54 (Knowledge of linear algebra and calculus) Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture per week Additional Details Subject/Course Level: Computer Science/Graduate Grading: Letter grade. Instructor: Malik Also listed as: VIS SCI C280 Computer Vision: Read Less [-] COMPSCI C281A Statistical Learning Theory 3 Units Terms offered: Fall 2021, Fall 2020, Fall 2019 Classification regression, clustering, dimensionality, reduction, and density estimation. Mixture models, hierarchical models, factorial models, hidden Markov, and state space models, Markov properties, and recursive algorithms for general probabilistic inference nonparametric methods including decision trees, kernal methods, neural networks, and wavelets. Ensemble methods. Statistical Learning Theory: Read More [+] Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture per week Additional Details Subject/Course Level: Computer Science/Graduate Grading: Letter grade. Instructors: Bartlett, Jordan, Wainwright Also listed as: STAT C241A Statistical Learning Theory: Read Less [-] COMPSCI C281B Advanced Topics in Learning and Decision Making 3 Units Terms offered: Spring 2023, Spring 2022, Spring 2017 Recent topics include: Graphical models and approximate inference algorithms. Markov chain Monte Carlo, mean field and probability propagation methods. Model selection and stochastic realization. Bayesian information theoretic and structural risk minimization approaches. Markov decision processes and partially observable Markov decision processes. Reinforcement learning. Advanced Topics in Learning and Decision Making: Read More [+] Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture per week Additional Details Subject/Course Level: Computer Science/Graduate Grading: Letter grade. Instructors: Bartlett, Jordan, Wainwright Also listed as: STAT C241B Advanced Topics in Learning and Decision Making: Read Less [-] 16 Computer Science COMPSCI 282A Designing, Visualizing and Understanding Deep Neural Networks 4 Units Terms offered: Spring 2023, Fall 2022, Spring 2022 Deep Networks have revolutionized computer vision, language technology, robotics and control. They have growing impact in many other areas of science and engineering. They do not however, follow a closed or compact set of theoretical principles. In Yann Lecun's words they require "an interplay between intuitive insights, theoretical modeling, practical implementations, empirical studies, and scientific analyses." This course attempts to cover that ground. Designing, Visualizing and Understanding Deep Neural Networks: Read More [+] Objectives & Outcomes Student Learning Outcomes: Students will come to understand visualizing deep networks. Exploring the training and use of deep networks with visualization tools. Students will learn design principles and best practices: design motifs that work well in particular domains, structure optimization and parameter optimization. Understanding deep networks. Methods with formal guarantees: generative and adversarial models, tensor factorization. Rules & Requirements Prerequisites: MATH 53 and MATH 54 or equivalent; COMPSCI 70 or STAT 134; COMPSCI 61B or equivalent; COMPSCI 189 or COMPSCI 289A (recommended) Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture and 1 hour of discussion per week Additional Details Subject/Course Level: Computer Science/Graduate Grading: Letter grade. Instructor: Canny Designing, Visualizing and Understanding Deep Neural Networks: Read Less [-] COMPSCI 284A Foundations of Computer Graphics 4 Units Terms offered: Spring 2023, Spring 2022, Spring 2021 Techniques of modeling objects for the purpose of computer rendering: boundary representations, constructive solids geometry, hierarchical scene descriptions. Mathematical techniques for curve and surface representation. Basic elements of a computer graphics rendering pipeline; architecture of modern graphics display devices. Geometrical transformations such as rotation, scaling, translation, and their matrix representations. Homogeneous coordinates, projective and perspective transformations. Foundations of Computer Graphics: Read More [+] Rules & Requirements Prerequisites: COMPSCI 61B or COMPSCI 61BL; programming skills in C, C++, or Java; linear algebra and calculus; or consent of instructor Credit Restrictions: Students will receive no credit for Computer Science 284A after taking 184. Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture and 1 hour of discussion per week Additional Details Subject/Course Level: Computer Science/Graduate Grading: Letter grade. Instructors: Agrawala, Barsky, O'Brien, Ramamoorthi, Sequin Foundations of Computer Graphics: Read Less [-] Computer Science 17 COMPSCI 284B Advanced Computer Graphics Algorithms and Techniques 4 Units Terms offered: Spring 2022, Spring 2019, Spring 2017 This course provides a graduate-level introduction to advanced computer graphics algorithms and techniques. Students should already be familiar with basic concepts such as transformations, scan-conversion, scene graphs, shading, and light transport. Topics covered in this course include global illumination, mesh processing, subdivision surfaces, basic differential geometry, physically based animation, inverse kinematics, imaging and computational photography, and precomputed light transport. Advanced Computer Graphics Algorithms and Techniques: Read More [+] Rules & Requirements Prerequisites: COMPSCI 184 Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture per week Additional Details Subject/Course Level: Computer Science/Graduate Grading: Letter grade. Instructors: O'Brien, Ramamoorthi Formerly known as: Computer Science 283 Advanced Computer Graphics Algorithms and Techniques: Read Less [-] COMPSCI 285 Deep Reinforcement Learning, Decision Making, and Control 3 Units Terms offered: Fall 2022, Fall 2021, Fall 2020 Intersection of control, reinforcement learning, and deep learning. Deep learning methods, which train large parametric function approximators, achieve excellent results on problems that require reasoning about unstructured real-world situations (e.g., computer vision, speech recognition, NLP). Advanced treatment of the reinforcement learning formalism, the most critical model-free reinforcement learning algorithms (policy gradients, value function and Q-function learning, and actor- critic), a discussion of model-based reinforcement learning algorithms, an overview of imitation learning, and a range of advanced topics (e.g., exploration, model-based learning with video prediction, transfer learning, multi-task learning, and meta-learning). Deep Reinforcement Learning, Decision Making, and Control: Read More [+] Objectives & Outcomes Student Learning Outcomes: Provide an opportunity to embark on a research-level final project with support from course staff. Provide hands-on experience with several commonly used RL algorithms; Provide students with an overview of advanced deep reinforcement learning topics, including current research trends; Provide students with foundational knowledge to understand deep reinforcement learning algorithms; Rules & Requirements Prerequisites: COMPSCI 189 or COMPSCI 289A or equivalent Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture per week Additional Details Subject/Course Level: Computer Science/Graduate Grading: Letter grade. Instructors: Levine, Abbeel Deep Reinforcement Learning, Decision Making, and Control: Read Less [-] 20 Computer Science COMPSCI 294 Special Topics 1 - 4 Units Terms offered: Spring 2023, Fall 2022, Spring 2022 Topics will vary from semester to semester. See Computer Science Division announcements. Special Topics: Read More [+] Rules & Requirements Repeat rules: Course may be repeated for credit without restriction. Hours & Format Fall and/or spring: 4 weeks - 3-15 hours of lecture per week 6 weeks - 3-9 hours of lecture per week 8 weeks - 2-6 hours of lecture per week 10 weeks - 2-5 hours of lecture per week 15 weeks - 1-3 hours of lecture per week Additional Details Subject/Course Level: Computer Science/Graduate Grading: Letter grade. Special Topics: Read Less [-] COMPSCI 297 Field Studies in Computer Science 12.0 Units Terms offered: Fall 2022, Spring 2016, Fall 2015 Supervised experience in off-campus companies relevant to specific aspects and applications of electrical engineering and/or computer science. Written report required at the end of the semester. Field Studies in Computer Science: Read More [+] Rules & Requirements Repeat rules: Course may be repeated for credit without restriction. Hours & Format Fall and/or spring: 15 weeks - 1-12 hours of independent study per week Summer: 6 weeks - 1-30 hours of independent study per week 8 weeks - 1.5-22.5 hours of independent study per week 10 weeks - 1-18 hours of independent study per week Additional Details Subject/Course Level: Computer Science/Graduate Grading: Offered for satisfactory/unsatisfactory grade only. Field Studies in Computer Science: Read Less [-] COMPSCI 298 Group Studies Seminars, or Group Research 1 - 4 Units Terms offered: Spring 2023, Fall 2022, Spring 2022 Advanced study in various subjects through seminars on topics to be selected each year, informal group studies of special problems, group participation in comprehensive design problems, or group research on complete problems for analysis and experimentation. Group Studies Seminars, or Group Research: Read More [+] Rules & Requirements Repeat rules: Course may be repeated for credit without restriction. Students may enroll in multiple sections of this course within the same semester. Hours & Format Fall and/or spring: 15 weeks - 1-4 hours of lecture per week Additional Details Subject/Course Level: Computer Science/Graduate Grading: The grading option will be decided by the instructor when the class is offered. Group Studies Seminars, or Group Research: Read Less [-] COMPSCI 299 Individual Research 1 - 12 Units Terms offered: Fall 2022, Summer 2017 Second 6 Week Session, Fall 2016 Investigations of problems in computer science. Individual Research: Read More [+] Rules & Requirements Repeat rules: Course may be repeated for credit without restriction. Hours & Format Fall and/or spring: 15 weeks - 0-1 hours of independent study per week Summer: 6 weeks - 8-30 hours of independent study per week 8 weeks - 6-22.5 hours of independent study per week 10 weeks - 1.5-18 hours of independent study per week Additional Details Subject/Course Level: Computer Science/Graduate Grading: Offered for satisfactory/unsatisfactory grade only. Individual Research: Read Less [-] Computer Science 21 COMPSCI 300 Teaching Practice 1 - 6 Units Terms offered: Fall 2012, Fall 2011, Spring 2011 Supervised teaching practice, in either a one-on-one tutorial or classroom discussion setting. Teaching Practice: Read More [+] Rules & Requirements Repeat rules: Course may be repeated for credit without restriction. Hours & Format Fall and/or spring: 15 weeks - 0 hours of independent study per week Summer: 6 weeks - 1-5 hours of independent study per week 8 weeks - 1-4 hours of independent study per week Additional Details Subject/Course Level: Computer Science/Professional course for teachers or prospective teachers Grading: Offered for satisfactory/unsatisfactory grade only. Teaching Practice: Read Less [-] COMPSCI 302 Designing Computer Science Education 3 Units Terms offered: Spring 2023, Spring 2022, Spring 2021 Discussion and review of research and practice relating to the teaching of computer science: knowledge organization and misconceptions, curriculum and topic organization, evaluation, collaborative learning, technology use, and administrative issues. As part of a semester- long project to design a computer science course, participants invent and refine a variety of homework and exam activities, and evaluate alternatives for textbooks, grading and other administrative policies, and innovative uses of technology. Designing Computer Science Education: Read More [+] Rules & Requirements Prerequisites: COMPSCI 301 and two semesters of GSI experience Hours & Format Fall and/or spring: 15 weeks - 2 hours of lecture per week Additional Details Subject/Course Level: Computer Science/Professional course for teachers or prospective teachers Grading: Letter grade. Instructor: Garcia Designing Computer Science Education: Read Less [-] COMPSCI 370 Adaptive Instruction Methods in Computer Science 3 Units Terms offered: Spring 2023, Fall 2022, Spring 2022 This is a course for aspiring teachers or those who want to instruct with expertise from evidence-based research and proven equity-oriented practices. It provides pedagogical training by introducing the big ideas of teaching and learning, and illustrating how to put them into practice. The course is divided into three sections—instructing the individual; a group; and psycho-social factors that affect learning at any level. These sections are designed to enhance any intern’s, tutor’s, or TA’s teaching skillset. Class is discussion based, and covers theoretical and practical pedagogical aspects to teaching in STEM. An integral feature of the course involves providing weekly tutoring sessions. Adaptive Instruction Methods in Computer Science: Read More [+] Rules & Requirements Prerequisites: Prerequisite satisfied Concurrently: experience tutoring or as an academic intern; or concurrently serving as an academic intern while taking course Hours & Format Fall and/or spring: 15 weeks - 2 hours of lecture per week Additional Details Subject/Course Level: Computer Science/Professional course for teachers or prospective teachers Grading: Letter grade. Instructor: Hunn Adaptive Instruction Methods in Computer Science: Read Less [-] COMPSCI 375 Teaching Techniques for Computer Science 2 Units Terms offered: Spring 2023, Fall 2022, Spring 2022 Discussion and practice of techniques for effective teaching, focusing on issues most relevant to teaching assistants in computer science courses. Teaching Techniques for Computer Science: Read More [+] Rules & Requirements Prerequisites: Consent of instructor Repeat rules: Course may be repeated for credit without restriction. Hours & Format Fall and/or spring: 10 weeks - 3 hours of discussion per week Summer: 8 weeks - 4 hours of discussion per week Additional Details Subject/Course Level: Computer Science/Professional course for teachers or prospective teachers Grading: Offered for satisfactory/unsatisfactory grade only. Instructors: Barsky, Garcia, Harvey Teaching Techniques for Computer Science: Read Less [-] 22 Computer Science COMPSCI 399 Professional Preparation: Supervised Teaching of Computer Science 1 or 2 Units Terms offered: Spring 2020, Fall 2018, Fall 2016 Discussion, problem review and development, guidance of computer science laboratory sections, course development, supervised practice teaching. Professional Preparation: Supervised Teaching of Computer Science: Read More [+] Rules & Requirements Prerequisites: Appointment as graduate student instructor Repeat rules: Course may be repeated for credit without restriction. Hours & Format Fall and/or spring: 15 weeks - 1-2 hours of independent study per week Summer: 8 weeks - 1-2 hours of independent study per week Additional Details Subject/Course Level: Computer Science/Professional course for teachers or prospective teachers Grading: Offered for satisfactory/unsatisfactory grade only. Professional Preparation: Supervised Teaching of Computer Science: Read Less [-] COMPSCI 602 Individual Study for Doctoral Students 1 - 8 Units Terms offered: Fall 2015, Fall 2014, Spring 2014 Individual study in consultation with the major field adviser, intended to provide an opportunity for qualified students to prepare themselves for the various examinations required of candidates for the Ph.D. (and other doctoral degrees). Individual Study for Doctoral Students: Read More [+] Rules & Requirements Credit Restrictions: Course does not satisfy unit or residence requirements for doctoral degree. Repeat rules: Course may be repeated for credit without restriction. Hours & Format Fall and/or spring: 15 weeks - 0 hours of independent study per week Summer: 8 weeks - 6-45 hours of independent study per week Additional Details Subject/Course Level: Computer Science/Graduate examination preparation Grading: Offered for satisfactory/unsatisfactory grade only. Individual Study for Doctoral Students: Read Less [-] Electrical Engineering Expand all course descriptions [+]Collapse all course descriptions [-] EL ENG 206A Introduction to Robotics 4 Units Terms offered: Fall 2017, Fall 2016, Fall 2015 An introduction to the kinematics, dynamics, and control of robot manipulators, robotic vision, and sensing. The course will cover forward and inverse kinematics of serial chain manipulators, the manipulator Jacobian, force relations, dynamics and control-position, and force control. Proximity, tactile, and force sensing. Network modeling, stability, and fidelity in teleoperation and medical applications of robotics. Introduction to Robotics: Read More [+] Rules & Requirements Prerequisites: 120 or equivalent, or consent of instructor Credit Restrictions: Students will receive no credit for 206A after taking C125/Bioengineering C125 or EE C106A Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture, 1 hour of discussion, and 3 hours of laboratory per week Additional Details Subject/Course Level: Electrical Engineering/Graduate Grading: Letter grade. Instructor: Bajcsy Formerly known as: Electrical Engineering 215A Introduction to Robotics: Read Less [-] Computer Science 25 EL ENG C220A Advanced Control Systems I 3 Units Terms offered: Fall 2022, Fall 2021, Fall 2020 Input-output and state space representation of linear continuous and discrete time dynamic systems. Controllability, observability, and stability. Modeling and identification. Design and analysis of single and multi- variable feedback control systems in transform and time domain. State observer. Feedforward/preview control. Application to engineering systems. Advanced Control Systems I: Read More [+] Rules & Requirements Repeat rules: Course may be repeated for credit without restriction. Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture and 1 hour of discussion per week Additional Details Subject/Course Level: Electrical Engineering/Graduate Grading: Letter grade. Instructors: Borrelli, Horowitz, Tomizuka, Tomlin Also listed as: MEC ENG C232 Advanced Control Systems I: Read Less [-] EL ENG C220B Experiential Advanced Control Design I 3 Units Terms offered: Fall 2022, Fall 2021, Fall 2020 Experience-based learning in the design of SISO and MIMO feedback controllers for linear systems. The student will master skills needed to apply linear control design and analysis tools to classical and modern control problems. In particular, the participant will be exposed to and develop expertise in two key control design technologies: frequency- domain control synthesis and time-domain optimization-based approach. Experiential Advanced Control Design I: Read More [+] Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture and 2 hours of laboratory per week Additional Details Subject/Course Level: Electrical Engineering/Graduate Grading: Letter grade. Also listed as: MEC ENG C231A Experiential Advanced Control Design I: Read Less [-] EL ENG C220C Experiential Advanced Control Design II 3 Units Terms offered: Spring 2023, Spring 2022, Fall 2021, Spring 2021 Experience-based learning in design, analysis, & verification of automatic control for uncertain systems. The course emphasizes use of practical algorithms, including thorough computer implementation for representative problems. The student will master skills needed to apply advanced model-based control analysis, design, and estimation to a variety of industrial applications. First-principles analysis is provided to explain and support the algorithms & methods. The course emphasizes model-based state estimation, including the Kalman filter, and particle filter. Optimal feedback control of uncertain systems is also discussed (the linear quadratic Gaussian problem) as well as considerations of transforming continuous-time to discrete time. Experiential Advanced Control Design II: Read More [+] Rules & Requirements Prerequisites: Undergraduate controls course (e.g. MECENG 132, ELENG 128) Recommended: MECENG C231A/ELENG C220B and either MECENG C232/ELENG C220A or ELENG 221A Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture and 1 hour of discussion per week Additional Details Subject/Course Level: Electrical Engineering/Graduate Grading: Letter grade. Instructor: Mueller Also listed as: MEC ENG C231B Experiential Advanced Control Design II: Read Less [-] 26 Computer Science EL ENG C220D Input/Output Methods for Compositional System Analysis 2 Units Terms offered: Prior to 2007 Introduction to input/output concepts from control theory, systems as operators in signal spaces, passivity and small-gain theorems, dissipativity theory, integral quadratic constraints. Compositional stabilility and performance certification for interconnected systems from subsystems input/output properties. Case studies in multi-agent systems, biological networks, Internet congestion control, and adaptive control. Input/Output Methods for Compositional System Analysis: Read More [+] Objectives & Outcomes Course Objectives: Standard computational tools for control synthesis and verification do not scale well to large-scale, networked systems in emerging applications. This course presents a compositional methodology suitable when the subsystems are amenable to analytical and computational methods but the interconnection, taken as a whole, is beyond the reach of these methods. The main idea is to break up the task of certifying desired stability and performance properties into subproblems of manageable size using input/ output properties. Students learn about the fundamental theory, as well as relevant algorithms and applications in several domains. Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture per week Additional Details Subject/Course Level: Electrical Engineering/Graduate Grading: Letter grade. Instructors: Arcak, Packard Also listed as: MEC ENG C220D Input/Output Methods for Compositional System Analysis: Read Less [-] EL ENG 221A Linear System Theory 4 Units Terms offered: Fall 2022, Fall 2021, Fall 2020 Basic system concepts; state-space and I/O representation. Properties of linear systems. Controllability, observability, minimality, state and output- feedback. Stability. Observers. Characteristic polynomial. Nyquist test. Linear System Theory: Read More [+] Rules & Requirements Prerequisites: EL ENG 120; and MATH 110 recommended Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture and 2 hours of recitation per week Additional Details Subject/Course Level: Electrical Engineering/Graduate Grading: Letter grade. Linear System Theory: Read Less [-] EL ENG 222 Nonlinear Systems--Analysis, Stability and Control 3 Units Terms offered: Spring 2017, Spring 2016, Spring 2015 Basic graduate course in non-linear systems. Second Order systems. Numerical solution methods, the describing function method, linearization. Stability - direct and indirect methods of Lyapunov. Applications to the Lure problem - Popov, circle criterion. Input-Output stability. Additional topics include: bifurcations of dynamical systems, introduction to the "geometric" theory of control for nonlinear systems, passivity concepts and dissipative dynamical systems. Nonlinear Systems--Analysis, Stability and Control: Read More [+] Rules & Requirements Prerequisites: EL ENG 221A (may be taken concurrently) Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture per week Additional Details Subject/Course Level: Electrical Engineering/Graduate Grading: Letter grade. Nonlinear Systems--Analysis, Stability and Control: Read Less [-] EL ENG C222 Nonlinear Systems 3 Units Terms offered: Spring 2023, Spring 2022, Spring 2021 Basic graduate course in nonlinear systems. Nonlinear phenomena, planar systems, bifurcations, center manifolds, existence and uniqueness theorems. Lyapunov’s direct and indirect methods, Lyapunov-based feedback stabilization. Input-to-state and input-output stability, and dissipativity theory. Computation techniques for nonlinear system analysis and design. Feedback linearization and sliding mode control methods. Nonlinear Systems: Read More [+] Rules & Requirements Prerequisites: MATH 54 (undergraduate level ordinary differential equations and linear algebra) Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture per week Additional Details Subject/Course Level: Electrical Engineering/Graduate Grading: Letter grade. Instructors: Arcak, Tomlin, Kameshwar Also listed as: MEC ENG C237 Nonlinear Systems: Read Less [-] Computer Science 27 EL ENG 223 Stochastic Systems: Estimation and Control 3 Units Terms offered: Fall 2022, Spring 2021, Spring 2020 Parameter and state estimation. System identification. Nonlinear filtering. Stochastic control. Adaptive control. Stochastic Systems: Estimation and Control: Read More [+] Rules & Requirements Prerequisites: EL ENG 226A (which students are encouraged to take concurrently) Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture per week Additional Details Subject/Course Level: Electrical Engineering/Graduate Grading: Letter grade. Stochastic Systems: Estimation and Control: Read Less [-] EL ENG 224A Digital Communications 4 Units Terms offered: Fall 2010, Fall 2009, Fall 2008 Introduction to the basic principles of the design and analysis of modern digital communication systems. Topics include source coding; channel coding; baseband and passband modulation techniques; receiver design; channel equalization; information theoretic techniques; block, convolutional, and trellis coding techniques; multiuser communications and spread spectrum; multi-carrier techniques and FDM; carrier and symbol synchronization. Applications to design of digital telephone modems, compact disks, and digital wireless communication systems are illustrated. The concepts are illustrated by a sequence of MATLAB exercises. Digital Communications: Read More [+] Rules & Requirements Prerequisites: EL ENG 120 and EL ENG 126 Hours & Format Fall and/or spring: 15 weeks - 4 hours of lecture and 1 hour of discussion per week Additional Details Subject/Course Level: Electrical Engineering/Graduate Grading: Letter grade. Formerly known as: 224 Digital Communications: Read Less [-] EL ENG 224B Fundamentals of Wireless Communication 3 Units Terms offered: Spring 2013, Spring 2012, Spring 2010 Introduction of the fundamentals of wireless communication. Modeling of the wireless multipath fading channel and its basic physical parameters. Coherent and noncoherent reception. Diversity techniques over time, frequency, and space. Spread spectrum communication. Multiple access and interference management in wireless networks. Frequency re- use, sectorization. Multiple access techniques: TDMA, CDMA, OFDM. Capacity of wireless channels. Opportunistic communication. Multiple antenna systems: spatial multiplexing, space-time codes. Examples from existing wireless standards. Fundamentals of Wireless Communication: Read More [+] Rules & Requirements Prerequisites: EL ENG 121 and EL ENG 226A Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture per week Additional Details Subject/Course Level: Electrical Engineering/Graduate Grading: Letter grade. Instructor: Tse Fundamentals of Wireless Communication: Read Less [-] EL ENG 225D Audio Signal Processing in Humans and Machines 3 Units Terms offered: Fall 2022, Fall 2021, Spring 2014 Introduction to relevant signal processing and basics of pattern recognition. Introduction to coding, synthesis, and recognition. Models of speech and music production and perception. Signal processing for speech analysis. Pitch perception and auditory spectral analysis with applications to speech and music. Vocoders and music synthesizers. Statistical speech recognition, including introduction to Hidden Markov Model and Neural Network approaches. Audio Signal Processing in Humans and Machines: Read More [+] Rules & Requirements Prerequisites: EL ENG 123 and STAT 200A; or graduate standing and consent of instructor Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture per week Additional Details Subject/Course Level: Electrical Engineering/Graduate Grading: Letter grade. Instructor: Morgan Audio Signal Processing in Humans and Machines: Read Less [-] 30 Computer Science EL ENG 229A Information Theory and Coding 3 Units Terms offered: Fall 2022, Fall 2021, Fall 2020 Fundamental bounds of Shannon theory and their application. Source and channel coding theorems. Galois field theory, algebraic error- correction codes. Private and public-key cryptographic systems. Information Theory and Coding: Read More [+] Rules & Requirements Prerequisites: STAT 200A; and EL ENG 226 recommended Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture per week Additional Details Subject/Course Level: Electrical Engineering/Graduate Grading: Letter grade. Instructors: Anantharam, Tse Formerly known as: 229 Information Theory and Coding: Read Less [-] EL ENG 229B Error Control Coding 3 Units Terms offered: Spring 2019, Spring 2016, Fall 2013 Error control codes are an integral part of most communication and recording systems where they are primarily used to provide resiliency to noise. In this course, we will cover the basics of error control coding for reliable digital transmission and storage. We will discuss the major classes of codes that are important in practice, including Reed Muller codes, cyclic codes, Reed Solomon codes, convolutional codes, concatenated codes, turbo codes, and low density parity check codes. The relevant background material from finite field and polynomial algebra will be developed as part of the course. Overview of topics: binary linear block codes; Reed Muller codes; Galois fields; linear block codes over a finite field; cyclic codes; BCH and Reed Solomon codes; convolutional codes and trellis based decoding, message passing decoding algorithms; trellis based soft decision decoding of block codes; turbo codes; low density parity check codes. Error Control Coding: Read More [+] Rules & Requirements Prerequisites: 126 or equivalent (some familiarity with basic probability). Prior exposure to information theory not necessary Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture per week Additional Details Subject/Course Level: Electrical Engineering/Graduate Grading: Letter grade. Instructor: Anatharam Error Control Coding: Read Less [-] EL ENG 230A Integrated-Circuit Devices 4 Units Terms offered: Spring 2023, Fall 2022, Spring 2022 Overview of electronic properties of semiconductors. Metal- semiconductor contacts, pn junctions, bipolar transistors, and MOS field- effect transistors. Properties that are significant to device operation for integrated circuits. Silicon device fabrication technology. Integrated-Circuit Devices: Read More [+] Rules & Requirements Prerequisites: 40 or 100 Credit Restrictions: Students will receive no credit for Electrical Engineering 230A after taking Electrical Engineering 130. Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture and 1 hour of discussion per week Additional Details Subject/Course Level: Electrical Engineering/Graduate Grading: Letter grade. Formerly known as: Electrical Engineering 230M Integrated-Circuit Devices: Read Less [-] EL ENG 230B Solid State Devices 4 Units Terms offered: Fall 2020, Spring 2019, Spring 2018 Physical principles and operational characteristics of semiconductor devices. Emphasis is on MOS field-effect transistors and their behaviors dictated by present and probable future technologies. Metal-oxide- semiconductor systems, short-channel and high field effects, device modeling, and impact on analog, digital circuits. Solid State Devices: Read More [+] Rules & Requirements Prerequisites: EL ENG 130 Credit Restrictions: Students will receive no credit for EL ENG 230B after completing EL ENG 231, or EL ENG W230B. A deficient grade in EL ENG 230B may be removed by taking EL ENG W230B. Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture and 1 hour of discussion per week Additional Details Subject/Course Level: Electrical Engineering/Graduate Grading: Letter grade. Instructors: Subramanian, King Liu, Salahuddin Formerly known as: Electrical Engineering 231 Solid State Devices: Read Less [-] Computer Science 31 EL ENG 230C Solid State Electronics 3 Units Terms offered: Fall 2018, Fall 2017, Fall 2016 Crystal structure and symmetries. Energy-band theory. Cyclotron resonance. Tensor effective mass. Statistics of electronic state population. Recombination theory. Carrier transport theory. Interface properties. Optical processes and properties. Solid State Electronics: Read More [+] Rules & Requirements Prerequisites: EL ENG 131; and PHYSICS 137B Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture per week Additional Details Subject/Course Level: Electrical Engineering/Graduate Grading: Letter grade. Instructors: Bokor, Salahuddin Formerly known as: Electrical Engineering 230 Solid State Electronics: Read Less [-] EL ENG W230A Integrated-Circuit Devices 4 Units Terms offered: Spring 2019, Spring 2018, Spring 2017 Overview of electronic properties of semiconductors. Metal- semiconductor contacts, pn junctions, bipolar transistors, and MOS field- effect transistors. Properties that are significant to device operation for integrated circuits. Silicon device fabrication technology. Integrated-Circuit Devices: Read More [+] Rules & Requirements Prerequisites: MAS-IC students only Credit Restrictions: Students will receive no credit for Electrical Engineering W230A after taking Electrical Engineering 130, Electrical Engineering W130 or Electrical Engineering 230A. Hours & Format Fall and/or spring: 15 weeks - 3 hours of web-based lecture and 1 hour of web-based discussion per week Summer: 10 weeks - 4.5 hours of web-based lecture and 1.5 hours of web-based discussion per week Online: This is an online course. Additional Details Subject/Course Level: Electrical Engineering/Graduate Grading: Letter grade. Instructors: Javey, Subramanian, King Liu Formerly known as: Electrical Engineering W130 Integrated-Circuit Devices: Read Less [-] EL ENG W230B Solid State Devices 4 Units Terms offered: Fall 2015 Physical principles and operational characteristics of semiconductor devices. Emphasis is on MOS field-effect transistors and their behaviors dictated by present and probable future technologies. Metal-oxide- semiconductor systems, short-channel and high field effects, device modeling, and impact on analog, digital circuits. Solid State Devices: Read More [+] Rules & Requirements Prerequisites: EL ENG W230A; MAS-IC students only Credit Restrictions: Students will receive no credit for EE W230B after taking EE 230B. Hours & Format Fall and/or spring: 15 weeks - 3 hours of web-based lecture and 1 hour of web-based discussion per week Summer: 10 weeks - 4.5 hours of web-based lecture and 1.5 hours of web-based discussion per week Online: This is an online course. Additional Details Subject/Course Level: Electrical Engineering/Graduate Grading: Letter grade. Instructors: Subramanian, King Liu, Salahuddin Formerly known as: Electrical Engineering W231 Solid State Devices: Read Less [-] EL ENG 232 Lightwave Devices 4 Units Terms offered: Spring 2023, Spring 2022, Spring 2021 This course is designed to give an introduction and overview of the fundamentals of optoelectronic devices. Topics such as optical gain and absorption spectra, quantization effects, strained quantum wells, optical waveguiding and coupling, and hetero p-n junction will be covered. This course will focus on basic physics and design principles of semiconductor diode lasers, light emitting diodes, photodetectors and integrated optics. Practical applications of the devices will be also discussed. Lightwave Devices: Read More [+] Rules & Requirements Prerequisites: EL ENG 130; PHYSICS 137A; and EL ENG 117 recommended Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture and 1 hour of discussion per week Additional Details Subject/Course Level: Electrical Engineering/Graduate Grading: Letter grade. Instructor: Wu Lightwave Devices: Read Less [-] 32 Computer Science EL ENG C235 Nanoscale Fabrication 4 Units Terms offered: Spring 2023, Spring 2022, Spring 2016, Spring 2015, Spring 2013 This course discusses various top-down and bottom-up approaches to synthesizing and processing nanostructured materials. The topics include fundamentals of self assembly, nano-imprint lithography, electron beam lithography, nanowire and nanotube synthesis, quantum dot synthesis (strain patterned and colloidal), postsynthesis modification (oxidation, doping, diffusion, surface interactions, and etching techniques). In addition, techniques to bridging length scales such as heterogeneous integration will be discussed. We will discuss new electronic, optical, thermal, mechanical, and chemical properties brought forth by the very small sizes. Nanoscale Fabrication: Read More [+] Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture and 1 hour of discussion per week Additional Details Subject/Course Level: Electrical Engineering/Graduate Grading: Letter grade. Instructor: Chang-Hasnain Also listed as: NSE C203 Nanoscale Fabrication: Read Less [-] EL ENG 236A Quantum and Optical Electronics 3 Units Terms offered: Fall 2022, Spring 2021, Fall 2019 Interaction of radiation with atomic and semiconductor systems, density matrix treatment, semiclassical laser theory (Lamb's), laser resonators, specific laser systems, laser dynamics, Q-switching and mode-locking, noise in lasers and optical amplifiers. Nonlinear optics, phase-conjugation, electrooptics, acoustooptics and magnetooptics, coherent optics, stimulated Raman and Brillouin scattering. Quantum and Optical Electronics: Read More [+] Rules & Requirements Prerequisites: EL ENG 117A and PHYSICS 137A Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture per week Additional Details Subject/Course Level: Electrical Engineering/Graduate Grading: Letter grade. Quantum and Optical Electronics: Read Less [-] EL ENG C239 Partially Ionized Plasmas 3 Units Terms offered: Spring 2010, Spring 2009, Spring 2007 Introduction to partially ionized, chemically reactive plasmas, including collisional processes, diffusion, sources, sheaths, boundaries, and diagnostics. DC, RF, and microwave discharges. Applications to plasma- assisted materials processing and to plasma wall interactions. Partially Ionized Plasmas: Read More [+] Rules & Requirements Prerequisites: An upper division course in electromagnetics or fluid dynamics Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture per week Additional Details Subject/Course Level: Electrical Engineering/Graduate Grading: Letter grade. Formerly known as: 239 Also listed as: AST C239 Partially Ionized Plasmas: Read Less [-] EL ENG 240A Analog Integrated Circuits 4 Units Terms offered: Spring 2023, Fall 2022, Fall 2021 Single and multiple stage transistor amplifiers. Operational amplifiers. Feedback amplifiers, 2-port formulation, source, load, and feedback network loading. Frequency response of cascaded amplifiers, gain- bandwidth exchange, compensation, dominant pole techniques, root locus. Supply and temperature independent biasing and references. Selected applications of analog circuits such as analog-to-digital converters, switched capacitor filters, and comparators. Hardware laboratory and design project. Analog Integrated Circuits: Read More [+] Rules & Requirements Prerequisites: EL ENG 105 Credit Restrictions: Students will receive no credit for EL ENG 240A after completing EL ENG 140, or EL ENG W240A. A deficient grade in EL ENG 240A may be removed by taking EL ENG W240A. Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture, 1 hour of discussion, and 3 hours of laboratory per week Additional Details Subject/Course Level: Electrical Engineering/Graduate Grading: Letter grade. Instructors: Sanders, Nguyen Analog Integrated Circuits: Read Less [-] Computer Science 35 EL ENG W240C Analysis and Design of VLSI Analog-Digital Interface Integrated Circuits 3 Units Terms offered: Spring 2017, Spring 2016 Architectural and circuit level design and analysis of integrated analog- to-digital and digital-to-analog interfaces in modern CMOS and BiCMOS VLSI technology. Analog-digital converters, digital-analog converters, sample/hold amplifiers, continuous and switched-capacitor filters. Low power mixed signal design techniques. Data communications systems including interface circuity. CAD tools for analog design for simulation and synthesis. Analysis and Design of VLSI Analog-Digital Interface Integrated Circuits: Read More [+] Rules & Requirements Prerequisites: EL ENG W240A; MAS-IC students only Credit Restrictions: Students will receive no credit for EE W240C after taking EE 240C. Hours & Format Fall and/or spring: 15 weeks - 3 hours of web-based lecture per week Summer: 10 weeks - 4.5 hours of web-based lecture per week Online: This is an online course. Additional Details Subject/Course Level: Electrical Engineering/Graduate Grading: Letter grade. Instructor: Boser Formerly known as: Electrical Engineering W247 Analysis and Design of VLSI Analog-Digital Interface Integrated Circuits: Read Less [-] EL ENG 241B Advanced Digital Integrated Circuits 3 Units Terms offered: Spring 2021, Spring 2020, Spring 2019 Analysis and design of MOS and bipolar large-scale integrated circuits at the circuit level. Fabrication processes, device characteristics, parasitic effects static and dynamic digital circuits for logic and memory functions. Calculation of speed and power consumption from layout and fabrication parameters. ROM, RAM, EEPROM circuit design. Use of SPICE and other computer aids. Advanced Digital Integrated Circuits: Read More [+] Rules & Requirements Prerequisites: EL ENG 141 Credit Restrictions: Students will receive no credit for EL ENG 241B after completing EL ENG 241, or EL ENG W241B. A deficient grade in EL ENG 241B may be removed by taking EL ENG W241B. Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture per week Additional Details Subject/Course Level: Electrical Engineering/Graduate Grading: Letter grade. Instructors: Nikolic, Rabaey Formerly known as: Electrical Engineering 241 Advanced Digital Integrated Circuits: Read Less [-] Computer Science 1 Computer Science The Department of Electrical Engineering and Computer Sciences (EECS) offers two graduate programs in Computer Science: the Master of Science (MS), and the Doctor of Philosophy (PhD). Master of Science (MS) The Master of Science (MS) emphasizes research preparation and experience and, for most students, is a chance to lay the groundwork for pursuing a PhD. Doctor of Philosophy (PhD) The Berkeley PhD in EECS combines coursework and original research with some of the finest EECS faculty in the US, preparing for careers in academia or industry. Our alumni (https://eecs.berkeley.edu/people/ alumni/cs-distinguished-alumni/) have gone on to hold amazing positions around the world. Admission to the University Minimum Requirements for Admission The following minimum requirements apply to all graduate programs and will be verified by the Graduate Division: 1. A bachelor’s degree or recognized equivalent from an accredited institution; 2. A grade point average of B or better (3.0); 3. If the applicant has completed a basic degree from a country or political entity (e.g., Quebec) where English is not the official language, adequate proficiency in English to do graduate work, as evidenced by a TOEFL score of at least 90 on the iBT test, 570 on the paper-and-pencil test, or an IELTS Band score of at least 7 on a 9-point scale (note that individual programs may set higher levels for any of these); and 4. Sufficient undergraduate training to do graduate work in the given field. Applicants Who Already Hold a Graduate Degree The Graduate Council views academic degrees not as vocational training certificates, but as evidence of broad training in research methods, independent study, and articulation of learning. Therefore, applicants who already have academic graduate degrees should be able to pursue new subject matter at an advanced level without the need to enroll in a related or similar graduate program. Programs may consider students for an additional academic master’s or professional master’s degree only if the additional degree is in a distinctly different field. Applicants admitted to a doctoral program that requires a master’s degree to be earned at Berkeley as a prerequisite (even though the applicant already has a master’s degree from another institution in the same or a closely allied field of study) will be permitted to undertake the second master’s degree, despite the overlap in field. The Graduate Division will admit students for a second doctoral degree only if they meet the following guidelines: 1. Applicants with doctoral degrees may be admitted for an additional doctoral degree only if that degree program is in a general area of knowledge distinctly different from the field in which they earned their original degree. For example, a physics PhD could be admitted to a doctoral degree program in music or history; however, a student with a doctoral degree in mathematics would not be permitted to add a PhD in statistics. 2. Applicants who hold the PhD degree may be admitted to a professional doctorate or professional master’s degree program if there is no duplication of training involved. Applicants may apply only to one single degree program or one concurrent degree program per admission cycle. Required Documents for Applications 1. Transcripts: Applicants may upload unofficial transcripts with your application for the departmental initial review. Unofficial transcripts must contain specific information including the name of the applicant, name of the school, all courses, grades, units, & degree conferral (if applicable). 2. Letters of recommendation: Applicants may request online letters of recommendation through the online application system. Hard copies of recommendation letters must be sent directly to the program, by the recommender, not the Graduate Admissions. 3. Evidence of English language proficiency: All applicants who have completed a basic degree from a country or political entity in which the official language is not English are required to submit official evidence of English language proficiency. This applies to institutions from Bangladesh, Burma, Nepal, India, Pakistan, Latin America, the Middle East, the People’s Republic of China, Taiwan, Japan, Korea, Southeast Asia, most European countries, and Quebec (Canada). However, applicants who, at the time of application, have already completed at least one year of full-time academic course work with grades of B or better at a US university may submit an official transcript from the US university to fulfill this requirement. The following courses will not fulfill this requirement: • courses in English as a Second Language, • courses conducted in a language other than English, • courses that will be completed after the application is submitted, and • courses of a non-academic nature. Applicants who have previously applied to Berkeley must also submit new test scores that meet the current minimum requirement from one of the standardized tests. Official TOEFL score reports must be sent directly from Educational Test Services (ETS). The institution code for Berkeley is 4833 for Graduate Organizations. Official IELTS score reports must be sent electronically from the testing center to University of California, Berkeley, Graduate Division, Sproul Hall, Rm 318 MC 5900, Berkeley, CA 94720. TOEFL and IELTS score reports are only valid for two years prior to beginning the graduate program at UC Berkeley. Note: score reports can not expire before the month of June. Where to Apply Visit the Berkeley Graduate Division application page (http:// grad.berkeley.edu/admissions/apply/). 2 Computer Science Admission to the Program The following items are required for admission to the Berkeley EECS MS/ PhD program in addition to the University’s general graduate admissions requirements: 1. Statement of Purpose: Why are you applying for this program? What will do you plan to accomplish during this degree program? What do you want to do afterward, and how will this degree help you reach that goal? 2. Personal History Statement: What experiences from your past made you decide to go into this field? And how will your personal history help you succeed in this program and your future goals? 3. GPA: If you attended a university outside the USA, please leave the GPA section blank. 4. Resume: Please also include a full resume/CV listing your experience and education. Complete the online UC Berkeley graduate application: 1. Start your application through this link (http:// www.grad.berkeley.edu/), and fill in each relevant page. 2. Upload the materials above, and send the recommender links several weeks prior to the application deadline to give your recommenders time to submit their letters. Normative Time Requirements Normative time in the EECS department is between 5.5-6 years for the doctoral program. Time to Advancement Curriculum The faculty of the College of Engineering recommends a minimum number of courses taken while in graduate standing. The total minimum is 24 units of coursework, taken for a letter grade and not including 397, 298, 299, 301, 375 and 602. 12 200-level units from one major field within EECS, with a 3.5 grade point average 12 6 units from one minor field within EECS, with a 3.0 grade point average and at least one 200-level course 6 6 100 and 200-level units from one minor field outside EECS, with a 3.0 grade point average 6 Preliminary Exams The EECS preliminary requirement consists of two components. Oral Examination The oral exam serves an advisory role in a student's graduate studies program, giving official feedback from the exam committee of faculty members. Students must be able to demonstrate an integrated grasp of the exam area's body of knowledge in an unstructured framework. Students must pass the oral portion of the preliminary exam within their first two attempts. A third attempt is possible with a petition of support from the student's faculty adviser and final approval by the prelim committee chair. Failure to pass the oral portion of the preliminary exam will result in the student being ineligible to complete the PhD program. The examining committee awards a score in the range of 0-10. The minimum passing score is 6.0. Breadth Courses The breadth courses ensure that students have exposure to areas outside of their concentration. It is expected that students will achieve high academic standards in these courses. CS students must complete courses from three of the following areas, passing each with at least a B+. One course must be selected from the Theory, AI, or Graphics/HCI group; and one course must be selected from the Programming, Systems, or Architecture/VLSI group1. Theory COMPSCI 270 Combinatorial Algorithms and Data Structures 3 COMPSCI 271 Randomness and Computation 3 COMPSCI 273 Foundations of Parallel Computation 3 COMPSCI 274 Computational Geometry 3 COMPSCI 276 Cryptography 3 AI COMPSCI C280 Computer Vision 3 COMPSCI C281A Statistical Learning Theory 3 COMPSCI C281B Advanced Topics in Learning and Decision Making 3 COMPSCI 287 Advanced Robotics 3 COMPSCI 288 Natural Language Processing 4 COMPSCI 289A Introduction to Machine Learning 4 Graphics/HCI COMPSCI 260B Human-Computer Interaction Research 3 Programming COMPSCI 263 Design of Programming Languages 3 COMPSCI 264 Implementation of Programming Languages 4 COMPSCI 265 Compiler Optimization and Code Generation 3 COMPSCI C267 Applications of Parallel Computers 3 EECS 219C Formal Methods: Specification, Verification, and Synthesis 3 Systems COMPSCI 261 Security in Computer Systems 3 COMPSCI 261N Internet and Network Security 4 COMPSCI 262A Advanced Topics in Computer Systems 4 COMPSCI 262B Advanced Topics in Computer Systems 3 COMPSCI 268 Computer Networks 3 COMPSCI 286B Implementation of Data Base Systems 3 Architecture/VLSI COMPSCI 250 VLSI Systems Design 4 EECS 251A Introduction to Digital Design and Integrated Circuits 3 EECS 251LA Introduction to Digital Design and Integrated Circuits Lab 2 EECS 251LB Introduction to Digital Design and Integrated Circuits Lab 2 1 COMPSCI 260B, COMPSCI 263, and EL ENG 219C cannot be used to fulfill this constraint, though they can be used to complete one of the three courses. Qualifying Examination (QE) The QE is an important checkpoint meant to show that a student is on a promising research track toward the PhD degree. It is a University Computer Science 5 EECS C206B Robotic Manipulation and Interaction 4 Units Terms offered: Spring 2023 This course is a sequel to EECS C106A/206A, which covers kinematics, dynamics and control of a single robot. This course will cover dynamics and control of groups of robotic manipulators coordinating with each other and interacting with the environment. Concepts will include an introduction to grasping and the constrained manipulation, contacts and force control for interaction with the environment. We will also cover active perception guided manipulation, as well as the manipulation of non-rigid objects. Throughout, we will emphasize design and human-robot interactions, and applications to applications in manufacturing, service robotics, tele-surgery, and locomotion. Robotic Manipulation and Interaction: Read More [+] Rules & Requirements Prerequisites: Students are expected to have taken EECS C106A / BioE C106A / ME C106A / ME C206A/ EECS C206A or an equivalent course. A strong programming background, knowledge of Python and Matlab, and some coursework in feedback controls (such as EE C128 / ME C134) are also useful. Students who have not taken EECS C106A / BioE C106A / ME C106A / ME C206A/ EECS C206A should have a strong programming background, knowledge of Python and Matlab, and exposure to linear algebra, and Lagrangian dynamics Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture, 1 hour of discussion, and 3 hours of laboratory per week Additional Details Subject/Course Level: Electrical Engin and Computer Sci/Graduate Grading: Letter grade. Instructors: Bajcsy, Sastry Formerly known as: Electrical Engin and Computer Sci 206B Also listed as: MEC ENG C206B Robotic Manipulation and Interaction: Read Less [-] EECS 208 Computational Principles for High- dimensional Data Analysis 4 Units Terms offered: Fall 2022, Fall 2021 Introduction to fundamental geometric and statistical concepts and principles of low-dimensional models for high-dimensional signal and data analysis, spanning basic theory, efficient algorithms, and diverse real-world applications. Systematic study of both sampling complexity and computational complexity for sparse, low-rank, and low-dimensional models – including important cases such as matrix completion, robust principal component analysis, dictionary learning, and deep networks. Computational Principles for High-dimensional Data Analysis: Read More [+] Rules & Requirements Prerequisites: The following courses are recommended undergraduate linear algebra (Math 110), statistics (Stat 134), and probability (EE126). Back-ground in signal processing (ELENG 123), optimization (ELENG C227T), machine learning (CS189/289), and computer vision (COMPSCI C280) may allow you to appreciate better certain aspects of the course material, but not necessary all at once. The course is open to senior undergraduates, with consent from the instructor Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture and 1 hour of discussion per week Additional Details Subject/Course Level: Electrical Engin and Computer Sci/Graduate Grading: Letter grade. Instructor: Ma Computational Principles for High-dimensional Data Analysis: Read Less [-] 6 Computer Science EECS 219C Formal Methods: Specification, Verification, and Synthesis 3 Units Terms offered: Spring 2023, Spring 2022, Spring 2021 Introduction to the theory and practice of formal methods for the design and analysis of systems, with a focus on algorithmic techniques. Covers selected topics in computational logic and automata theory including modeling and specification formalisms, temporal logics, satisfiability solving, model checking, synthesis, learning, and theorem proving. Applications to software and hardware design, cyber-physical systems, robotics, computer security, and other areas will be explored as time permits. Formal Methods: Specification, Verification, and Synthesis: Read More [+] Rules & Requirements Prerequisites: Graduate standing or consent of instructor; COMPSCI 170 is recommended Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture per week Additional Details Subject/Course Level: Electrical Engin and Computer Sci/Graduate Grading: Letter grade. Instructor: Seshia Formerly known as: Electrical Engineering 219C Formal Methods: Specification, Verification, and Synthesis: Read Less [-] EECS 225A Statistical Signal Processing 3 Units Terms offered: Spring 2023, Fall 2021, Fall 2020 This course connects classical statistical signal processing (Hilbert space filtering theory by Wiener and Kolmogorov, state space model, signal representation, detection and estimation, adaptive filtering) with modern statistical and machine learning theory and applications. It focuses on concrete algorithms and combines principled theoretical thinking with real applications. Statistical Signal Processing: Read More [+] Rules & Requirements Prerequisites: EL ENG 120 and EECS 126 Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture per week Additional Details Subject/Course Level: Electrical Engin and Computer Sci/Graduate Grading: Letter grade. Instructors: Jiao, Waller Formerly known as: Electrical Engineering 225A Statistical Signal Processing: Read Less [-] EECS 225B Digital Image Processing 3 Units Terms offered: Fall 2022, Fall 2020, Spring 2020 This course deals with computational methods as applied to digital imagery. It focuses on image sensing and acquisition, image sampling and quantization; spatial transformation, linear and nonlinear filtering; introduction to convolutional neural networks, and GANs; applications of deep learning methods to image processing problems; image enhancement, histogram equalization, image restoration, Weiner filtering, tomography, image reconstruction from projections and partial Fourier information, Radon transform, multiresolution analysis, continuous and discrete wavelet transform and computation, subband coding, image and video compression, sparse signal approximation, dictionary techniques, image and video compression standards, and more. Digital Image Processing: Read More [+] Rules & Requirements Prerequisites: Basic knowledge of signals and systems, convolution, and Fourier Transform Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture per week Additional Details Subject/Course Level: Electrical Engin and Computer Sci/Graduate Grading: Letter grade. Instructor: Zakhor Formerly known as: Electrical Engineering 225B Digital Image Processing: Read Less [-] EECS 227AT Optimization Models in Engineering 4 Units Terms offered: Spring 2023, Fall 2022, Spring 2022 This course offers an introduction to optimization models and their applications, ranging from machine learning and statistics to decision- making and control, with emphasis on numerically tractable problems, such as linear or constrained least-squares optimization. Optimization Models in Engineering: Read More [+] Rules & Requirements Prerequisites: MATH 54 or consent of instructor Credit Restrictions: Students will receive no credit for EECS 227AT after taking EECS 127 or Electrical Engineering 127/227AT. Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture and 1 hour of discussion per week Additional Details Subject/Course Level: Electrical Engin and Computer Sci/Graduate Grading: Letter grade. Instructor: El Ghaoui Formerly known as: Electrical Engineering 227AT Optimization Models in Engineering: Read Less [-] Computer Science 7 EECS 251A Introduction to Digital Design and Integrated Circuits 3 Units Terms offered: Spring 2023, Fall 2022, Spring 2022 An introduction to digital circuit and system design. The material provides a top-down view of the principles, components, and methodologies for large scale digital system design. The underlying CMOS devices and manufacturing technologies are introduced, but quickly abstracted to higher levels to focus the class on design of larger digital modules for both FPGAs (field programmable gate arrays) and ASICs (application specific integrated circuits). The class includes extensive use of industrial grade design automation and verification tools for assignments, labs, and projects. Introduction to Digital Design and Integrated Circuits: Read More [+] Objectives & Outcomes Course Objectives: The Verilog hardware description language is introduced and used. Basic digital system design concepts, Boolean operations/combinational logic, sequential elements and finite-state- machines, are described. Design of larger building blocks such as arithmetic units, interconnection networks, input/output units, as well as memory design (SRAM, Caches, FIFOs) and integration are also covered. Parallelism, pipelining and other micro-architectural optimizations are introduced. A number of physical design issues visible at the architecture level are covered as well, such as interconnects, power, and reliability. Student Learning Outcomes: Although the syllabus is the same as EECS151, the assignments and exams for EECS251A will have harder problems that test deeper understanding expected from a graduate level course. Rules & Requirements Prerequisites: EECS 16A and EECS 16B; COMPSCI 61C; and recommended: EL ENG 105. Students must enroll concurrently in at least one the laboratory flavors EECS 251LA or EECS 251LB. Students wishing to take a second laboratory flavor next term can sign-up only for that laboratory section and receive a letter grade. The prerequisite for “Lab-only” enrollment that term will be EECS 251A from previous terms Credit Restrictions: Students must enroll concurrently in at least one the laboratory flavors Electrical Engineering and Computer Science 251LA or Electrical Engineering and Computer Science 251LB. Students wishing to take a second laboratory flavor next term can sign-up only for that laboratory section and receive a letter grade. The pre-requisite for “Lab- only” enrollment that term will be Electrical Engineering and Computer Science 251A from previous terms. Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture and 1 hour of discussion per week Additional Details Subject/Course Level: Electrical Engin and Computer Sci/Graduate Grading: Letter grade. Instructors: Stojanovic, Wawrzynek Formerly known as: Electrical Engineering 241A Introduction to Digital Design and Integrated Circuits: Read Less [-] EECS 251B Advanced Digital Integrated Circuits and Systems 4 Units Terms offered: Spring 2023, Spring 2022 This course aims to convey a knowledge of advanced concepts of digital circuit and system-on-a-chip design in state-of-the-art technologies. Emphasis is on the circuit and system design and optimization for both energy efficiency and high performance for use in a broad range of applications, from edge computing to datacenters. Special attention will be devoted to the most important challenges facing digital circuit designers in the coming decade. The course is accompanied with practical laboratory exercises that introduce students to modern tool flows. Advanced Digital Integrated Circuits and Systems: Read More [+] Rules & Requirements Prerequisites: Introduction to Digital Design and Integrated Circuits, EECS151 (taken with either EECS151LA or EECS151LB lab) or EECS251A (taken with either EECS251LA or EECS251LB lab) Credit Restrictions: Students will receive no credit for EECS 251B after completing COMPSCI 250, or EL ENG 241B. Hours & Format Fall and/or spring: 15 weeks - 4 hours of lecture and 1 hour of discussion per week Additional Details Subject/Course Level: Electrical Engin and Computer Sci/Graduate Grading: Letter grade. Instructors: Nikoli#, Shao, Wawrzynek, Asanovi#, Stojanovi#, Seshia Advanced Digital Integrated Circuits and Systems: Read Less [-] 10 Computer Science COMPSCI 252A Graduate Computer Architecture 4 Units Terms offered: Spring 2023, Spring 2022, Spring 2021 Graduate survey of contemporary computer organizations covering: early systems, CPU design, instruction sets, control, processors, busses, ALU, memory, I/O interfaces, connection networks, virtual memory, pipelined computers, multiprocessors, and case studies. Term paper or project is required. Graduate Computer Architecture: Read More [+] Rules & Requirements Prerequisites: COMPSCI 61C Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture and 2 hours of discussion per week Additional Details Subject/Course Level: Computer Science/Graduate Grading: Letter grade. Instructors: Asanovi#, Kubiatowicz Formerly known as: Computer Science 252 Graduate Computer Architecture: Read Less [-] COMPSCI 260A User Interface Design and Development 4 Units Terms offered: Spring 2023, Fall 2020, Spring 2020 The design, implementation, and evaluation of user interfaces. User- centered design and task analysis. Conceptual models and interface metaphors. Usability inspection and evaluation methods. Analysis of user study data. Input methods (keyboard, pointing, touch, tangible) and input models. Visual design principles. Interface prototyping and implementation methodologies and tools. Students will develop a user interface for a specific task and target user group in teams. User Interface Design and Development: Read More [+] Rules & Requirements Prerequisites: COMPSCI 61B, COMPSCI 61BL, or consent of instructor Credit Restrictions: Students will receive no credit for Computer Science 260A after taking Computer Science 160. Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture and 1 hour of discussion per week Additional Details Subject/Course Level: Computer Science/Graduate Grading: Letter grade. Instructors: Agrawala, Canny, Hartmann User Interface Design and Development: Read Less [-] COMPSCI 260B Human-Computer Interaction Research 3 Units Terms offered: Fall 2017 This course is a broad introduction to conducting research in Human- Computer Interaction. Students will become familiar with seminal and recent literature; learn to review and critique research papers; re- implement and evaluate important existing systems; and gain experience in conducting research. Topics include input devices, computer-supported cooperative work, crowdsourcing, design tools, evaluation methods, search and mobile interfaces, usable security, help and tutorial systems. Human-Computer Interaction Research: Read More [+] Rules & Requirements Prerequisites: COMPSCI 160 recommended, or consent of instructor Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture per week Additional Details Subject/Course Level: Computer Science/Graduate Grading: Letter grade. Instructor: Hartmann Human-Computer Interaction Research: Read Less [-] COMPSCI 261 Security in Computer Systems 3 Units Terms offered: Spring 2021, Fall 2018, Fall 2017 Graduate survey of modern topics in computer security, including protection, access control, distributed access security, firewalls, secure coding practices, safe languages, mobile code, and case studies from real-world systems. May also cover cryptographic protocols, privacy and anonymity, and/or other topics as time permits. Security in Computer Systems: Read More [+] Rules & Requirements Prerequisites: COMPSCI 162 Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture per week Additional Details Subject/Course Level: Computer Science/Graduate Grading: Letter grade. Instructors: D. Song, Wagner Security in Computer Systems: Read Less [-] Computer Science 11 COMPSCI 261N Internet and Network Security 4 Units Terms offered: Spring 2020, Fall 2016, Spring 2015 Develops a thorough grounding in Internet and network security suitable for those interested in conducting research in the area or those more broadly interested in security or networking. Potential topics include denial-of-service; capabilities; network intrusion detection/prevention; worms; forensics; scanning; traffic analysis; legal issues; web attacks; anonymity; wireless and networked devices; honeypots; botnets; scams; underground economy; attacker infrastructure; research pitfalls. Internet and Network Security: Read More [+] Rules & Requirements Prerequisites: EL ENG 122 or equivalent; and COMPSCI 161 or familiarity with basic security concepts Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture per week Additional Details Subject/Course Level: Computer Science/Graduate Grading: Letter grade. Instructor: Paxson Internet and Network Security: Read Less [-] COMPSCI 262A Advanced Topics in Computer Systems 4 Units Terms offered: Fall 2022, Fall 2021, Fall 2020 Graduate survey of systems for managing computation and information, covering a breadth of topics: early systems; volatile memory management, including virtual memory and buffer management; persistent memory systems, including both file systems and transactional storage managers; storage metadata, physical vs. logical naming, schemas, process scheduling, threading and concurrency control; system support for networking, including remote procedure calls, transactional RPC, TCP, and active messages; security infrastructure; extensible systems and APIs; performance analysis and engineering of large software systems. Homework assignments, exam, and term paper or project required. Advanced Topics in Computer Systems: Read More [+] Rules & Requirements Prerequisites: COMPSCI 162 and entrance exam Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture per week Additional Details Subject/Course Level: Computer Science/Graduate Grading: Letter grade. Instructors: Brewer, Hellerstein Formerly known as: 262 Advanced Topics in Computer Systems: Read Less [-] COMPSCI 262B Advanced Topics in Computer Systems 3 Units Terms offered: Spring 2020, Spring 2009, Fall 2008 Continued graduate survey of large-scale systems for managing information and computation. Topics include basic performance measurement; extensibility, with attention to protection, security, and management of abstract data types; index structures, including support for concurrency and recovery; parallelism, including parallel architectures, query processing and scheduling; distributed data management, including distributed and mobile file systems and databases; distributed caching; large-scale data analysis and search. Homework assignments, exam, and term paper or project required. Advanced Topics in Computer Systems: Read More [+] Rules & Requirements Prerequisites: COMPSCI 262A Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture per week Additional Details Subject/Course Level: Computer Science/Graduate Grading: Letter grade. Instructors: Brewer, Culler, Hellerstein, Joseph Advanced Topics in Computer Systems: Read Less [-] COMPSCI 263 Design of Programming Languages 3 Units Terms offered: Fall 2021, Fall 2019, Spring 2019 Selected topics from: analysis, comparison, and design of programming languages, formal description of syntax and semantics, advanced programming techniques, structured programming, debugging, verification of programs and compilers, and proofs of correctness. Design of Programming Languages: Read More [+] Rules & Requirements Prerequisites: COMPSCI 164 Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture and 1 hour of discussion per week Additional Details Subject/Course Level: Computer Science/Graduate Grading: Letter grade. Instructor: Necula Design of Programming Languages: Read Less [-] 12 Computer Science COMPSCI 264 Implementation of Programming Languages 4 Units Terms offered: Fall 2021, Spring 2011, Spring 2010 Compiler construction. Lexical analysis, syntax analysis. Semantic analysis code generation and optimization. Storage management. Run- time organization. Implementation of Programming Languages: Read More [+] Rules & Requirements Prerequisites: COMPSCI 164; COMPSCI 263 recommended Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture, 1 hour of discussion, and 6 hours of laboratory per week Additional Details Subject/Course Level: Computer Science/Graduate Grading: Letter grade. Instructor: Bodik Implementation of Programming Languages: Read Less [-] COMPSCI 265 Compiler Optimization and Code Generation 3 Units Terms offered: Fall 2009, Spring 2003, Spring 2000 Table-driven and retargetable code generators. Register management. Flow analysis and global optimization methods. Code optimization for advanced languages and architectures. Local code improvement. Optimization by program transformation. Selected additional topics. A term paper or project is required. Compiler Optimization and Code Generation: Read More [+] Rules & Requirements Prerequisites: COMPSCI 164 Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture per week Additional Details Subject/Course Level: Computer Science/Graduate Grading: Letter grade. Instructor: Sen Compiler Optimization and Code Generation: Read Less [-] COMPSCI C267 Applications of Parallel Computers 3 - 4 Units Terms offered: Spring 2023, Spring 2022, Spring 2021 Models for parallel programming. Overview of parallelism in scientific applications and study of parallel algorithms for linear algebra, particles, meshes, sorting, FFT, graphs, machine learning, etc. Survey of parallel machines and machine structures. Programming shared- and distributed-memory parallel computers, GPUs, and cloud platforms. Parallel programming languages, compilers, libraries and toolboxes. Data partitioning techniques. Techniques for synchronization and load balancing. Detailed study and algorithm/program development of medium sized applications. Applications of Parallel Computers: Read More [+] Rules & Requirements Prerequisites: No formal pre-requisites. Prior programming experience with a low-level language such as C, C++, or Fortran is recommended but not required. CS C267 is intended to be useful for students from many departments and with different backgrounds, although we will assume reasonable programming skills in a conventional (non-parallel) language, as well as enough mathematical skills to understand the problems and algorithmic solutions presented Repeat rules: Course may be repeated for credit without restriction. Hours & Format Fall and/or spring: 15 weeks - 3-3 hours of lecture and 1-1 hours of laboratory per week Additional Details Subject/Course Level: Computer Science/Graduate Grading: Letter grade. Instructors: Demmel, Yelick Also listed as: ENGIN C233 Applications of Parallel Computers: Read Less [-] Computer Science 15 COMPSCI C280 Computer Vision 3 Units Terms offered: Spring 2023, Spring 2022, Spring 2021 Paradigms for computational vision. Relation to human visual perception. Mathematical techniques for representing and reasoning, with curves, surfaces and volumes. Illumination and reflectance models. Color perception. Image segmentation and aggregation. Methods for bottom- up three dimensional shape recovery: Line drawing analysis, stereo, shading, motion, texture. Use of object models for prediction and recognition. Computer Vision: Read More [+] Rules & Requirements Prerequisites: MATH 1A; MATH 1B; MATH 53; and MATH 54 (Knowledge of linear algebra and calculus) Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture per week Additional Details Subject/Course Level: Computer Science/Graduate Grading: Letter grade. Instructor: Malik Also listed as: VIS SCI C280 Computer Vision: Read Less [-] COMPSCI C281A Statistical Learning Theory 3 Units Terms offered: Fall 2021, Fall 2020, Fall 2019 Classification regression, clustering, dimensionality, reduction, and density estimation. Mixture models, hierarchical models, factorial models, hidden Markov, and state space models, Markov properties, and recursive algorithms for general probabilistic inference nonparametric methods including decision trees, kernal methods, neural networks, and wavelets. Ensemble methods. Statistical Learning Theory: Read More [+] Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture per week Additional Details Subject/Course Level: Computer Science/Graduate Grading: Letter grade. Instructors: Bartlett, Jordan, Wainwright Also listed as: STAT C241A Statistical Learning Theory: Read Less [-] COMPSCI C281B Advanced Topics in Learning and Decision Making 3 Units Terms offered: Spring 2023, Spring 2022, Spring 2017 Recent topics include: Graphical models and approximate inference algorithms. Markov chain Monte Carlo, mean field and probability propagation methods. Model selection and stochastic realization. Bayesian information theoretic and structural risk minimization approaches. Markov decision processes and partially observable Markov decision processes. Reinforcement learning. Advanced Topics in Learning and Decision Making: Read More [+] Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture per week Additional Details Subject/Course Level: Computer Science/Graduate Grading: Letter grade. Instructors: Bartlett, Jordan, Wainwright Also listed as: STAT C241B Advanced Topics in Learning and Decision Making: Read Less [-] 16 Computer Science COMPSCI 282A Designing, Visualizing and Understanding Deep Neural Networks 4 Units Terms offered: Spring 2023, Fall 2022, Spring 2022 Deep Networks have revolutionized computer vision, language technology, robotics and control. They have growing impact in many other areas of science and engineering. They do not however, follow a closed or compact set of theoretical principles. In Yann Lecun's words they require "an interplay between intuitive insights, theoretical modeling, practical implementations, empirical studies, and scientific analyses." This course attempts to cover that ground. Designing, Visualizing and Understanding Deep Neural Networks: Read More [+] Objectives & Outcomes Student Learning Outcomes: Students will come to understand visualizing deep networks. Exploring the training and use of deep networks with visualization tools. Students will learn design principles and best practices: design motifs that work well in particular domains, structure optimization and parameter optimization. Understanding deep networks. Methods with formal guarantees: generative and adversarial models, tensor factorization. Rules & Requirements Prerequisites: MATH 53 and MATH 54 or equivalent; COMPSCI 70 or STAT 134; COMPSCI 61B or equivalent; COMPSCI 189 or COMPSCI 289A (recommended) Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture and 1 hour of discussion per week Additional Details Subject/Course Level: Computer Science/Graduate Grading: Letter grade. Instructor: Canny Designing, Visualizing and Understanding Deep Neural Networks: Read Less [-] COMPSCI 284A Foundations of Computer Graphics 4 Units Terms offered: Spring 2023, Spring 2022, Spring 2021 Techniques of modeling objects for the purpose of computer rendering: boundary representations, constructive solids geometry, hierarchical scene descriptions. Mathematical techniques for curve and surface representation. Basic elements of a computer graphics rendering pipeline; architecture of modern graphics display devices. Geometrical transformations such as rotation, scaling, translation, and their matrix representations. Homogeneous coordinates, projective and perspective transformations. Foundations of Computer Graphics: Read More [+] Rules & Requirements Prerequisites: COMPSCI 61B or COMPSCI 61BL; programming skills in C, C++, or Java; linear algebra and calculus; or consent of instructor Credit Restrictions: Students will receive no credit for Computer Science 284A after taking 184. Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture and 1 hour of discussion per week Additional Details Subject/Course Level: Computer Science/Graduate Grading: Letter grade. Instructors: Agrawala, Barsky, O'Brien, Ramamoorthi, Sequin Foundations of Computer Graphics: Read Less [-] Computer Science 17 COMPSCI 284B Advanced Computer Graphics Algorithms and Techniques 4 Units Terms offered: Spring 2022, Spring 2019, Spring 2017 This course provides a graduate-level introduction to advanced computer graphics algorithms and techniques. Students should already be familiar with basic concepts such as transformations, scan-conversion, scene graphs, shading, and light transport. Topics covered in this course include global illumination, mesh processing, subdivision surfaces, basic differential geometry, physically based animation, inverse kinematics, imaging and computational photography, and precomputed light transport. Advanced Computer Graphics Algorithms and Techniques: Read More [+] Rules & Requirements Prerequisites: COMPSCI 184 Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture per week Additional Details Subject/Course Level: Computer Science/Graduate Grading: Letter grade. Instructors: O'Brien, Ramamoorthi Formerly known as: Computer Science 283 Advanced Computer Graphics Algorithms and Techniques: Read Less [-] COMPSCI 285 Deep Reinforcement Learning, Decision Making, and Control 3 Units Terms offered: Fall 2022, Fall 2021, Fall 2020 Intersection of control, reinforcement learning, and deep learning. Deep learning methods, which train large parametric function approximators, achieve excellent results on problems that require reasoning about unstructured real-world situations (e.g., computer vision, speech recognition, NLP). Advanced treatment of the reinforcement learning formalism, the most critical model-free reinforcement learning algorithms (policy gradients, value function and Q-function learning, and actor- critic), a discussion of model-based reinforcement learning algorithms, an overview of imitation learning, and a range of advanced topics (e.g., exploration, model-based learning with video prediction, transfer learning, multi-task learning, and meta-learning). Deep Reinforcement Learning, Decision Making, and Control: Read More [+] Objectives & Outcomes Student Learning Outcomes: Provide an opportunity to embark on a research-level final project with support from course staff. Provide hands-on experience with several commonly used RL algorithms; Provide students with an overview of advanced deep reinforcement learning topics, including current research trends; Provide students with foundational knowledge to understand deep reinforcement learning algorithms; Rules & Requirements Prerequisites: COMPSCI 189 or COMPSCI 289A or equivalent Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture per week Additional Details Subject/Course Level: Computer Science/Graduate Grading: Letter grade. Instructors: Levine, Abbeel Deep Reinforcement Learning, Decision Making, and Control: Read Less [-] 20 Computer Science COMPSCI 294 Special Topics 1 - 4 Units Terms offered: Spring 2023, Fall 2022, Spring 2022 Topics will vary from semester to semester. See Computer Science Division announcements. Special Topics: Read More [+] Rules & Requirements Repeat rules: Course may be repeated for credit without restriction. Hours & Format Fall and/or spring: 4 weeks - 3-15 hours of lecture per week 6 weeks - 3-9 hours of lecture per week 8 weeks - 2-6 hours of lecture per week 10 weeks - 2-5 hours of lecture per week 15 weeks - 1-3 hours of lecture per week Additional Details Subject/Course Level: Computer Science/Graduate Grading: Letter grade. Special Topics: Read Less [-] COMPSCI 297 Field Studies in Computer Science 12.0 Units Terms offered: Fall 2022, Spring 2016, Fall 2015 Supervised experience in off-campus companies relevant to specific aspects and applications of electrical engineering and/or computer science. Written report required at the end of the semester. Field Studies in Computer Science: Read More [+] Rules & Requirements Repeat rules: Course may be repeated for credit without restriction. Hours & Format Fall and/or spring: 15 weeks - 1-12 hours of independent study per week Summer: 6 weeks - 1-30 hours of independent study per week 8 weeks - 1.5-22.5 hours of independent study per week 10 weeks - 1-18 hours of independent study per week Additional Details Subject/Course Level: Computer Science/Graduate Grading: Offered for satisfactory/unsatisfactory grade only. Field Studies in Computer Science: Read Less [-] COMPSCI 298 Group Studies Seminars, or Group Research 1 - 4 Units Terms offered: Spring 2023, Fall 2022, Spring 2022 Advanced study in various subjects through seminars on topics to be selected each year, informal group studies of special problems, group participation in comprehensive design problems, or group research on complete problems for analysis and experimentation. Group Studies Seminars, or Group Research: Read More [+] Rules & Requirements Repeat rules: Course may be repeated for credit without restriction. Students may enroll in multiple sections of this course within the same semester. Hours & Format Fall and/or spring: 15 weeks - 1-4 hours of lecture per week Additional Details Subject/Course Level: Computer Science/Graduate Grading: The grading option will be decided by the instructor when the class is offered. Group Studies Seminars, or Group Research: Read Less [-] COMPSCI 299 Individual Research 1 - 12 Units Terms offered: Fall 2022, Summer 2017 Second 6 Week Session, Fall 2016 Investigations of problems in computer science. Individual Research: Read More [+] Rules & Requirements Repeat rules: Course may be repeated for credit without restriction. Hours & Format Fall and/or spring: 15 weeks - 0-1 hours of independent study per week Summer: 6 weeks - 8-30 hours of independent study per week 8 weeks - 6-22.5 hours of independent study per week 10 weeks - 1.5-18 hours of independent study per week Additional Details Subject/Course Level: Computer Science/Graduate Grading: Offered for satisfactory/unsatisfactory grade only. Individual Research: Read Less [-] Computer Science 21 COMPSCI 300 Teaching Practice 1 - 6 Units Terms offered: Fall 2012, Fall 2011, Spring 2011 Supervised teaching practice, in either a one-on-one tutorial or classroom discussion setting. Teaching Practice: Read More [+] Rules & Requirements Repeat rules: Course may be repeated for credit without restriction. Hours & Format Fall and/or spring: 15 weeks - 0 hours of independent study per week Summer: 6 weeks - 1-5 hours of independent study per week 8 weeks - 1-4 hours of independent study per week Additional Details Subject/Course Level: Computer Science/Professional course for teachers or prospective teachers Grading: Offered for satisfactory/unsatisfactory grade only. Teaching Practice: Read Less [-] COMPSCI 302 Designing Computer Science Education 3 Units Terms offered: Spring 2023, Spring 2022, Spring 2021 Discussion and review of research and practice relating to the teaching of computer science: knowledge organization and misconceptions, curriculum and topic organization, evaluation, collaborative learning, technology use, and administrative issues. As part of a semester- long project to design a computer science course, participants invent and refine a variety of homework and exam activities, and evaluate alternatives for textbooks, grading and other administrative policies, and innovative uses of technology. Designing Computer Science Education: Read More [+] Rules & Requirements Prerequisites: COMPSCI 301 and two semesters of GSI experience Hours & Format Fall and/or spring: 15 weeks - 2 hours of lecture per week Additional Details Subject/Course Level: Computer Science/Professional course for teachers or prospective teachers Grading: Letter grade. Instructor: Garcia Designing Computer Science Education: Read Less [-] COMPSCI 370 Adaptive Instruction Methods in Computer Science 3 Units Terms offered: Spring 2023, Fall 2022, Spring 2022 This is a course for aspiring teachers or those who want to instruct with expertise from evidence-based research and proven equity-oriented practices. It provides pedagogical training by introducing the big ideas of teaching and learning, and illustrating how to put them into practice. The course is divided into three sections—instructing the individual; a group; and psycho-social factors that affect learning at any level. These sections are designed to enhance any intern’s, tutor’s, or TA’s teaching skillset. Class is discussion based, and covers theoretical and practical pedagogical aspects to teaching in STEM. An integral feature of the course involves providing weekly tutoring sessions. Adaptive Instruction Methods in Computer Science: Read More [+] Rules & Requirements Prerequisites: Prerequisite satisfied Concurrently: experience tutoring or as an academic intern; or concurrently serving as an academic intern while taking course Hours & Format Fall and/or spring: 15 weeks - 2 hours of lecture per week Additional Details Subject/Course Level: Computer Science/Professional course for teachers or prospective teachers Grading: Letter grade. Instructor: Hunn Adaptive Instruction Methods in Computer Science: Read Less [-] COMPSCI 375 Teaching Techniques for Computer Science 2 Units Terms offered: Spring 2023, Fall 2022, Spring 2022 Discussion and practice of techniques for effective teaching, focusing on issues most relevant to teaching assistants in computer science courses. Teaching Techniques for Computer Science: Read More [+] Rules & Requirements Prerequisites: Consent of instructor Repeat rules: Course may be repeated for credit without restriction. Hours & Format Fall and/or spring: 10 weeks - 3 hours of discussion per week Summer: 8 weeks - 4 hours of discussion per week Additional Details Subject/Course Level: Computer Science/Professional course for teachers or prospective teachers Grading: Offered for satisfactory/unsatisfactory grade only. Instructors: Barsky, Garcia, Harvey Teaching Techniques for Computer Science: Read Less [-] 22 Computer Science COMPSCI 399 Professional Preparation: Supervised Teaching of Computer Science 1 or 2 Units Terms offered: Spring 2020, Fall 2018, Fall 2016 Discussion, problem review and development, guidance of computer science laboratory sections, course development, supervised practice teaching. Professional Preparation: Supervised Teaching of Computer Science: Read More [+] Rules & Requirements Prerequisites: Appointment as graduate student instructor Repeat rules: Course may be repeated for credit without restriction. Hours & Format Fall and/or spring: 15 weeks - 1-2 hours of independent study per week Summer: 8 weeks - 1-2 hours of independent study per week Additional Details Subject/Course Level: Computer Science/Professional course for teachers or prospective teachers Grading: Offered for satisfactory/unsatisfactory grade only. Professional Preparation: Supervised Teaching of Computer Science: Read Less [-] COMPSCI 602 Individual Study for Doctoral Students 1 - 8 Units Terms offered: Fall 2015, Fall 2014, Spring 2014 Individual study in consultation with the major field adviser, intended to provide an opportunity for qualified students to prepare themselves for the various examinations required of candidates for the Ph.D. (and other doctoral degrees). Individual Study for Doctoral Students: Read More [+] Rules & Requirements Credit Restrictions: Course does not satisfy unit or residence requirements for doctoral degree. Repeat rules: Course may be repeated for credit without restriction. Hours & Format Fall and/or spring: 15 weeks - 0 hours of independent study per week Summer: 8 weeks - 6-45 hours of independent study per week Additional Details Subject/Course Level: Computer Science/Graduate examination preparation Grading: Offered for satisfactory/unsatisfactory grade only. Individual Study for Doctoral Students: Read Less [-] Electrical Engineering Expand all course descriptions [+]Collapse all course descriptions [-] EL ENG 206A Introduction to Robotics 4 Units Terms offered: Fall 2017, Fall 2016, Fall 2015 An introduction to the kinematics, dynamics, and control of robot manipulators, robotic vision, and sensing. The course will cover forward and inverse kinematics of serial chain manipulators, the manipulator Jacobian, force relations, dynamics and control-position, and force control. Proximity, tactile, and force sensing. Network modeling, stability, and fidelity in teleoperation and medical applications of robotics. Introduction to Robotics: Read More [+] Rules & Requirements Prerequisites: 120 or equivalent, or consent of instructor Credit Restrictions: Students will receive no credit for 206A after taking C125/Bioengineering C125 or EE C106A Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture, 1 hour of discussion, and 3 hours of laboratory per week Additional Details Subject/Course Level: Electrical Engineering/Graduate Grading: Letter grade. Instructor: Bajcsy Formerly known as: Electrical Engineering 215A Introduction to Robotics: Read Less [-] Computer Science 25 EL ENG C220A Advanced Control Systems I 3 Units Terms offered: Fall 2022, Fall 2021, Fall 2020 Input-output and state space representation of linear continuous and discrete time dynamic systems. Controllability, observability, and stability. Modeling and identification. Design and analysis of single and multi- variable feedback control systems in transform and time domain. State observer. Feedforward/preview control. Application to engineering systems. Advanced Control Systems I: Read More [+] Rules & Requirements Repeat rules: Course may be repeated for credit without restriction. Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture and 1 hour of discussion per week Additional Details Subject/Course Level: Electrical Engineering/Graduate Grading: Letter grade. Instructors: Borrelli, Horowitz, Tomizuka, Tomlin Also listed as: MEC ENG C232 Advanced Control Systems I: Read Less [-] EL ENG C220B Experiential Advanced Control Design I 3 Units Terms offered: Fall 2022, Fall 2021, Fall 2020 Experience-based learning in the design of SISO and MIMO feedback controllers for linear systems. The student will master skills needed to apply linear control design and analysis tools to classical and modern control problems. In particular, the participant will be exposed to and develop expertise in two key control design technologies: frequency- domain control synthesis and time-domain optimization-based approach. Experiential Advanced Control Design I: Read More [+] Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture and 2 hours of laboratory per week Additional Details Subject/Course Level: Electrical Engineering/Graduate Grading: Letter grade. Also listed as: MEC ENG C231A Experiential Advanced Control Design I: Read Less [-] EL ENG C220C Experiential Advanced Control Design II 3 Units Terms offered: Spring 2023, Spring 2022, Fall 2021, Spring 2021 Experience-based learning in design, analysis, & verification of automatic control for uncertain systems. The course emphasizes use of practical algorithms, including thorough computer implementation for representative problems. The student will master skills needed to apply advanced model-based control analysis, design, and estimation to a variety of industrial applications. First-principles analysis is provided to explain and support the algorithms & methods. The course emphasizes model-based state estimation, including the Kalman filter, and particle filter. Optimal feedback control of uncertain systems is also discussed (the linear quadratic Gaussian problem) as well as considerations of transforming continuous-time to discrete time. Experiential Advanced Control Design II: Read More [+] Rules & Requirements Prerequisites: Undergraduate controls course (e.g. MECENG 132, ELENG 128) Recommended: MECENG C231A/ELENG C220B and either MECENG C232/ELENG C220A or ELENG 221A Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture and 1 hour of discussion per week Additional Details Subject/Course Level: Electrical Engineering/Graduate Grading: Letter grade. Instructor: Mueller Also listed as: MEC ENG C231B Experiential Advanced Control Design II: Read Less [-] 26 Computer Science EL ENG C220D Input/Output Methods for Compositional System Analysis 2 Units Terms offered: Prior to 2007 Introduction to input/output concepts from control theory, systems as operators in signal spaces, passivity and small-gain theorems, dissipativity theory, integral quadratic constraints. Compositional stabilility and performance certification for interconnected systems from subsystems input/output properties. Case studies in multi-agent systems, biological networks, Internet congestion control, and adaptive control. Input/Output Methods for Compositional System Analysis: Read More [+] Objectives & Outcomes Course Objectives: Standard computational tools for control synthesis and verification do not scale well to large-scale, networked systems in emerging applications. This course presents a compositional methodology suitable when the subsystems are amenable to analytical and computational methods but the interconnection, taken as a whole, is beyond the reach of these methods. The main idea is to break up the task of certifying desired stability and performance properties into subproblems of manageable size using input/ output properties. Students learn about the fundamental theory, as well as relevant algorithms and applications in several domains. Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture per week Additional Details Subject/Course Level: Electrical Engineering/Graduate Grading: Letter grade. Instructors: Arcak, Packard Also listed as: MEC ENG C220D Input/Output Methods for Compositional System Analysis: Read Less [-] EL ENG 221A Linear System Theory 4 Units Terms offered: Fall 2022, Fall 2021, Fall 2020 Basic system concepts; state-space and I/O representation. Properties of linear systems. Controllability, observability, minimality, state and output- feedback. Stability. Observers. Characteristic polynomial. Nyquist test. Linear System Theory: Read More [+] Rules & Requirements Prerequisites: EL ENG 120; and MATH 110 recommended Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture and 2 hours of recitation per week Additional Details Subject/Course Level: Electrical Engineering/Graduate Grading: Letter grade. Linear System Theory: Read Less [-] EL ENG 222 Nonlinear Systems--Analysis, Stability and Control 3 Units Terms offered: Spring 2017, Spring 2016, Spring 2015 Basic graduate course in non-linear systems. Second Order systems. Numerical solution methods, the describing function method, linearization. Stability - direct and indirect methods of Lyapunov. Applications to the Lure problem - Popov, circle criterion. Input-Output stability. Additional topics include: bifurcations of dynamical systems, introduction to the "geometric" theory of control for nonlinear systems, passivity concepts and dissipative dynamical systems. Nonlinear Systems--Analysis, Stability and Control: Read More [+] Rules & Requirements Prerequisites: EL ENG 221A (may be taken concurrently) Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture per week Additional Details Subject/Course Level: Electrical Engineering/Graduate Grading: Letter grade. Nonlinear Systems--Analysis, Stability and Control: Read Less [-] EL ENG C222 Nonlinear Systems 3 Units Terms offered: Spring 2023, Spring 2022, Spring 2021 Basic graduate course in nonlinear systems. Nonlinear phenomena, planar systems, bifurcations, center manifolds, existence and uniqueness theorems. Lyapunov’s direct and indirect methods, Lyapunov-based feedback stabilization. Input-to-state and input-output stability, and dissipativity theory. Computation techniques for nonlinear system analysis and design. Feedback linearization and sliding mode control methods. Nonlinear Systems: Read More [+] Rules & Requirements Prerequisites: MATH 54 (undergraduate level ordinary differential equations and linear algebra) Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture per week Additional Details Subject/Course Level: Electrical Engineering/Graduate Grading: Letter grade. Instructors: Arcak, Tomlin, Kameshwar Also listed as: MEC ENG C237 Nonlinear Systems: Read Less [-] Computer Science 27 EL ENG 223 Stochastic Systems: Estimation and Control 3 Units Terms offered: Fall 2022, Spring 2021, Spring 2020 Parameter and state estimation. System identification. Nonlinear filtering. Stochastic control. Adaptive control. Stochastic Systems: Estimation and Control: Read More [+] Rules & Requirements Prerequisites: EL ENG 226A (which students are encouraged to take concurrently) Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture per week Additional Details Subject/Course Level: Electrical Engineering/Graduate Grading: Letter grade. Stochastic Systems: Estimation and Control: Read Less [-] EL ENG 224A Digital Communications 4 Units Terms offered: Fall 2010, Fall 2009, Fall 2008 Introduction to the basic principles of the design and analysis of modern digital communication systems. Topics include source coding; channel coding; baseband and passband modulation techniques; receiver design; channel equalization; information theoretic techniques; block, convolutional, and trellis coding techniques; multiuser communications and spread spectrum; multi-carrier techniques and FDM; carrier and symbol synchronization. Applications to design of digital telephone modems, compact disks, and digital wireless communication systems are illustrated. The concepts are illustrated by a sequence of MATLAB exercises. Digital Communications: Read More [+] Rules & Requirements Prerequisites: EL ENG 120 and EL ENG 126 Hours & Format Fall and/or spring: 15 weeks - 4 hours of lecture and 1 hour of discussion per week Additional Details Subject/Course Level: Electrical Engineering/Graduate Grading: Letter grade. Formerly known as: 224 Digital Communications: Read Less [-] EL ENG 224B Fundamentals of Wireless Communication 3 Units Terms offered: Spring 2013, Spring 2012, Spring 2010 Introduction of the fundamentals of wireless communication. Modeling of the wireless multipath fading channel and its basic physical parameters. Coherent and noncoherent reception. Diversity techniques over time, frequency, and space. Spread spectrum communication. Multiple access and interference management in wireless networks. Frequency re- use, sectorization. Multiple access techniques: TDMA, CDMA, OFDM. Capacity of wireless channels. Opportunistic communication. Multiple antenna systems: spatial multiplexing, space-time codes. Examples from existing wireless standards. Fundamentals of Wireless Communication: Read More [+] Rules & Requirements Prerequisites: EL ENG 121 and EL ENG 226A Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture per week Additional Details Subject/Course Level: Electrical Engineering/Graduate Grading: Letter grade. Instructor: Tse Fundamentals of Wireless Communication: Read Less [-] EL ENG 225D Audio Signal Processing in Humans and Machines 3 Units Terms offered: Fall 2022, Fall 2021, Spring 2014 Introduction to relevant signal processing and basics of pattern recognition. Introduction to coding, synthesis, and recognition. Models of speech and music production and perception. Signal processing for speech analysis. Pitch perception and auditory spectral analysis with applications to speech and music. Vocoders and music synthesizers. Statistical speech recognition, including introduction to Hidden Markov Model and Neural Network approaches. Audio Signal Processing in Humans and Machines: Read More [+] Rules & Requirements Prerequisites: EL ENG 123 and STAT 200A; or graduate standing and consent of instructor Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture per week Additional Details Subject/Course Level: Electrical Engineering/Graduate Grading: Letter grade. Instructor: Morgan Audio Signal Processing in Humans and Machines: Read Less [-] 30 Computer Science EL ENG 229A Information Theory and Coding 3 Units Terms offered: Fall 2022, Fall 2021, Fall 2020 Fundamental bounds of Shannon theory and their application. Source and channel coding theorems. Galois field theory, algebraic error- correction codes. Private and public-key cryptographic systems. Information Theory and Coding: Read More [+] Rules & Requirements Prerequisites: STAT 200A; and EL ENG 226 recommended Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture per week Additional Details Subject/Course Level: Electrical Engineering/Graduate Grading: Letter grade. Instructors: Anantharam, Tse Formerly known as: 229 Information Theory and Coding: Read Less [-] EL ENG 229B Error Control Coding 3 Units Terms offered: Spring 2019, Spring 2016, Fall 2013 Error control codes are an integral part of most communication and recording systems where they are primarily used to provide resiliency to noise. In this course, we will cover the basics of error control coding for reliable digital transmission and storage. We will discuss the major classes of codes that are important in practice, including Reed Muller codes, cyclic codes, Reed Solomon codes, convolutional codes, concatenated codes, turbo codes, and low density parity check codes. The relevant background material from finite field and polynomial algebra will be developed as part of the course. Overview of topics: binary linear block codes; Reed Muller codes; Galois fields; linear block codes over a finite field; cyclic codes; BCH and Reed Solomon codes; convolutional codes and trellis based decoding, message passing decoding algorithms; trellis based soft decision decoding of block codes; turbo codes; low density parity check codes. Error Control Coding: Read More [+] Rules & Requirements Prerequisites: 126 or equivalent (some familiarity with basic probability). Prior exposure to information theory not necessary Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture per week Additional Details Subject/Course Level: Electrical Engineering/Graduate Grading: Letter grade. Instructor: Anatharam Error Control Coding: Read Less [-] EL ENG 230A Integrated-Circuit Devices 4 Units Terms offered: Spring 2023, Fall 2022, Spring 2022 Overview of electronic properties of semiconductors. Metal- semiconductor contacts, pn junctions, bipolar transistors, and MOS field- effect transistors. Properties that are significant to device operation for integrated circuits. Silicon device fabrication technology. Integrated-Circuit Devices: Read More [+] Rules & Requirements Prerequisites: 40 or 100 Credit Restrictions: Students will receive no credit for Electrical Engineering 230A after taking Electrical Engineering 130. Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture and 1 hour of discussion per week Additional Details Subject/Course Level: Electrical Engineering/Graduate Grading: Letter grade. Formerly known as: Electrical Engineering 230M Integrated-Circuit Devices: Read Less [-] EL ENG 230B Solid State Devices 4 Units Terms offered: Fall 2020, Spring 2019, Spring 2018 Physical principles and operational characteristics of semiconductor devices. Emphasis is on MOS field-effect transistors and their behaviors dictated by present and probable future technologies. Metal-oxide- semiconductor systems, short-channel and high field effects, device modeling, and impact on analog, digital circuits. Solid State Devices: Read More [+] Rules & Requirements Prerequisites: EL ENG 130 Credit Restrictions: Students will receive no credit for EL ENG 230B after completing EL ENG 231, or EL ENG W230B. A deficient grade in EL ENG 230B may be removed by taking EL ENG W230B. Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture and 1 hour of discussion per week Additional Details Subject/Course Level: Electrical Engineering/Graduate Grading: Letter grade. Instructors: Subramanian, King Liu, Salahuddin Formerly known as: Electrical Engineering 231 Solid State Devices: Read Less [-] Computer Science 31 EL ENG 230C Solid State Electronics 3 Units Terms offered: Fall 2018, Fall 2017, Fall 2016 Crystal structure and symmetries. Energy-band theory. Cyclotron resonance. Tensor effective mass. Statistics of electronic state population. Recombination theory. Carrier transport theory. Interface properties. Optical processes and properties. Solid State Electronics: Read More [+] Rules & Requirements Prerequisites: EL ENG 131; and PHYSICS 137B Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture per week Additional Details Subject/Course Level: Electrical Engineering/Graduate Grading: Letter grade. Instructors: Bokor, Salahuddin Formerly known as: Electrical Engineering 230 Solid State Electronics: Read Less [-] EL ENG W230A Integrated-Circuit Devices 4 Units Terms offered: Spring 2019, Spring 2018, Spring 2017 Overview of electronic properties of semiconductors. Metal- semiconductor contacts, pn junctions, bipolar transistors, and MOS field- effect transistors. Properties that are significant to device operation for integrated circuits. Silicon device fabrication technology. Integrated-Circuit Devices: Read More [+] Rules & Requirements Prerequisites: MAS-IC students only Credit Restrictions: Students will receive no credit for Electrical Engineering W230A after taking Electrical Engineering 130, Electrical Engineering W130 or Electrical Engineering 230A. Hours & Format Fall and/or spring: 15 weeks - 3 hours of web-based lecture and 1 hour of web-based discussion per week Summer: 10 weeks - 4.5 hours of web-based lecture and 1.5 hours of web-based discussion per week Online: This is an online course. Additional Details Subject/Course Level: Electrical Engineering/Graduate Grading: Letter grade. Instructors: Javey, Subramanian, King Liu Formerly known as: Electrical Engineering W130 Integrated-Circuit Devices: Read Less [-] EL ENG W230B Solid State Devices 4 Units Terms offered: Fall 2015 Physical principles and operational characteristics of semiconductor devices. Emphasis is on MOS field-effect transistors and their behaviors dictated by present and probable future technologies. Metal-oxide- semiconductor systems, short-channel and high field effects, device modeling, and impact on analog, digital circuits. Solid State Devices: Read More [+] Rules & Requirements Prerequisites: EL ENG W230A; MAS-IC students only Credit Restrictions: Students will receive no credit for EE W230B after taking EE 230B. Hours & Format Fall and/or spring: 15 weeks - 3 hours of web-based lecture and 1 hour of web-based discussion per week Summer: 10 weeks - 4.5 hours of web-based lecture and 1.5 hours of web-based discussion per week Online: This is an online course. Additional Details Subject/Course Level: Electrical Engineering/Graduate Grading: Letter grade. Instructors: Subramanian, King Liu, Salahuddin Formerly known as: Electrical Engineering W231 Solid State Devices: Read Less [-] EL ENG 232 Lightwave Devices 4 Units Terms offered: Spring 2023, Spring 2022, Spring 2021 This course is designed to give an introduction and overview of the fundamentals of optoelectronic devices. Topics such as optical gain and absorption spectra, quantization effects, strained quantum wells, optical waveguiding and coupling, and hetero p-n junction will be covered. This course will focus on basic physics and design principles of semiconductor diode lasers, light emitting diodes, photodetectors and integrated optics. Practical applications of the devices will be also discussed. Lightwave Devices: Read More [+] Rules & Requirements Prerequisites: EL ENG 130; PHYSICS 137A; and EL ENG 117 recommended Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture and 1 hour of discussion per week Additional Details Subject/Course Level: Electrical Engineering/Graduate Grading: Letter grade. Instructor: Wu Lightwave Devices: Read Less [-] 32 Computer Science EL ENG C235 Nanoscale Fabrication 4 Units Terms offered: Spring 2023, Spring 2022, Spring 2016, Spring 2015, Spring 2013 This course discusses various top-down and bottom-up approaches to synthesizing and processing nanostructured materials. The topics include fundamentals of self assembly, nano-imprint lithography, electron beam lithography, nanowire and nanotube synthesis, quantum dot synthesis (strain patterned and colloidal), postsynthesis modification (oxidation, doping, diffusion, surface interactions, and etching techniques). In addition, techniques to bridging length scales such as heterogeneous integration will be discussed. We will discuss new electronic, optical, thermal, mechanical, and chemical properties brought forth by the very small sizes. Nanoscale Fabrication: Read More [+] Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture and 1 hour of discussion per week Additional Details Subject/Course Level: Electrical Engineering/Graduate Grading: Letter grade. Instructor: Chang-Hasnain Also listed as: NSE C203 Nanoscale Fabrication: Read Less [-] EL ENG 236A Quantum and Optical Electronics 3 Units Terms offered: Fall 2022, Spring 2021, Fall 2019 Interaction of radiation with atomic and semiconductor systems, density matrix treatment, semiclassical laser theory (Lamb's), laser resonators, specific laser systems, laser dynamics, Q-switching and mode-locking, noise in lasers and optical amplifiers. Nonlinear optics, phase-conjugation, electrooptics, acoustooptics and magnetooptics, coherent optics, stimulated Raman and Brillouin scattering. Quantum and Optical Electronics: Read More [+] Rules & Requirements Prerequisites: EL ENG 117A and PHYSICS 137A Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture per week Additional Details Subject/Course Level: Electrical Engineering/Graduate Grading: Letter grade. Quantum and Optical Electronics: Read Less [-] EL ENG C239 Partially Ionized Plasmas 3 Units Terms offered: Spring 2010, Spring 2009, Spring 2007 Introduction to partially ionized, chemically reactive plasmas, including collisional processes, diffusion, sources, sheaths, boundaries, and diagnostics. DC, RF, and microwave discharges. Applications to plasma- assisted materials processing and to plasma wall interactions. Partially Ionized Plasmas: Read More [+] Rules & Requirements Prerequisites: An upper division course in electromagnetics or fluid dynamics Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture per week Additional Details Subject/Course Level: Electrical Engineering/Graduate Grading: Letter grade. Formerly known as: 239 Also listed as: AST C239 Partially Ionized Plasmas: Read Less [-] EL ENG 240A Analog Integrated Circuits 4 Units Terms offered: Spring 2023, Fall 2022, Fall 2021 Single and multiple stage transistor amplifiers. Operational amplifiers. Feedback amplifiers, 2-port formulation, source, load, and feedback network loading. Frequency response of cascaded amplifiers, gain- bandwidth exchange, compensation, dominant pole techniques, root locus. Supply and temperature independent biasing and references. Selected applications of analog circuits such as analog-to-digital converters, switched capacitor filters, and comparators. Hardware laboratory and design project. Analog Integrated Circuits: Read More [+] Rules & Requirements Prerequisites: EL ENG 105 Credit Restrictions: Students will receive no credit for EL ENG 240A after completing EL ENG 140, or EL ENG W240A. A deficient grade in EL ENG 240A may be removed by taking EL ENG W240A. Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture, 1 hour of discussion, and 3 hours of laboratory per week Additional Details Subject/Course Level: Electrical Engineering/Graduate Grading: Letter grade. Instructors: Sanders, Nguyen Analog Integrated Circuits: Read Less [-] Computer Science 35 EL ENG W240C Analysis and Design of VLSI Analog-Digital Interface Integrated Circuits 3 Units Terms offered: Spring 2017, Spring 2016 Architectural and circuit level design and analysis of integrated analog- to-digital and digital-to-analog interfaces in modern CMOS and BiCMOS VLSI technology. Analog-digital converters, digital-analog converters, sample/hold amplifiers, continuous and switched-capacitor filters. Low power mixed signal design techniques. Data communications systems including interface circuity. CAD tools for analog design for simulation and synthesis. Analysis and Design of VLSI Analog-Digital Interface Integrated Circuits: Read More [+] Rules & Requirements Prerequisites: EL ENG W240A; MAS-IC students only Credit Restrictions: Students will receive no credit for EE W240C after taking EE 240C. Hours & Format Fall and/or spring: 15 weeks - 3 hours of web-based lecture per week Summer: 10 weeks - 4.5 hours of web-based lecture per week Online: This is an online course. Additional Details Subject/Course Level: Electrical Engineering/Graduate Grading: Letter grade. Instructor: Boser Formerly known as: Electrical Engineering W247 Analysis and Design of VLSI Analog-Digital Interface Integrated Circuits: Read Less [-] EL ENG 241B Advanced Digital Integrated Circuits 3 Units Terms offered: Spring 2021, Spring 2020, Spring 2019 Analysis and design of MOS and bipolar large-scale integrated circuits at the circuit level. Fabrication processes, device characteristics, parasitic effects static and dynamic digital circuits for logic and memory functions. Calculation of speed and power consumption from layout and fabrication parameters. ROM, RAM, EEPROM circuit design. Use of SPICE and other computer aids. Advanced Digital Integrated Circuits: Read More [+] Rules & Requirements Prerequisites: EL ENG 141 Credit Restrictions: Students will receive no credit for EL ENG 241B after completing EL ENG 241, or EL ENG W241B. A deficient grade in EL ENG 241B may be removed by taking EL ENG W241B. Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture per week Additional Details Subject/Course Level: Electrical Engineering/Graduate Grading: Letter grade. Instructors: Nikolic, Rabaey Formerly known as: Electrical Engineering 241 Advanced Digital Integrated Circuits: Read Less [-] 36 Computer Science EL ENG W241A Introduction to Digital Integrated Circuits 4 Units Terms offered: Fall 2015, Fall 2014, Spring 2014 CMOS devices and deep sub-micron manufacturing technology. CMOS inverters and complex gates. Modeling of interconnect wires. Optimization of designs with respect to a number of metrics: cost, reliability, performance, and power dissipation. Sequential circuits, timing considerations, and clocking approaches. Design of large system blocks, including arithmetic, interconnect, memories, and programmable logic arrays. Introduction to design methodologies, including laboratory experience. Introduction to Digital Integrated Circuits: Read More [+] Rules & Requirements Prerequisites: MAS-IC students only Credit Restrictions: Students will receive no credit for W241A after taking EE 141 or EE 241A. Hours & Format Fall and/or spring: 15 weeks - 3 hours of web-based lecture and 4 hours of web-based discussion per week Summer: 10 weeks - 4.5 hours of web-based lecture and 6 hours of web- based discussion per week Online: This is an online course. Additional Details Subject/Course Level: Electrical Engineering/Graduate Grading: Letter grade. Instructors: Alon, Rabaey, Nikolic Introduction to Digital Integrated Circuits: Read Less [-] EL ENG W241B Advanced Digital Integrated Circuits 3 Units Terms offered: Spring 2017, Spring 2016, Spring 2015 Analysis and design of MOS and bipolar large-scale integrated circuits at the circuit level. Fabrication processes, device characteristics, parasitic effects static and dynamic digital circuits for logic and memory functions. Calculation of speed and power consumption from layout and fabrication parameters. ROM, RAM, EEPROM circuit design. Use of SPICE and other computer aids. Advanced Digital Integrated Circuits: Read More [+] Rules & Requirements Prerequisites: EL ENG W241A; MAS-IC students only Credit Restrictions: Students will receive no credit for EE W241B after taking EE 241B. Hours & Format Fall and/or spring: 15 weeks - 3 hours of web-based lecture per week Summer: 10 weeks - 4.5 hours of web-based lecture per week Online: This is an online course. Additional Details Subject/Course Level: Electrical Engineering/Graduate Grading: Letter grade. Instructors: Nikolic, Rabaey Formerly known as: Electrical Engineering W241 Advanced Digital Integrated Circuits: Read Less [-] Computer Science 37 EL ENG 242A Integrated Circuits for Communications 4 Units Terms offered: Spring 2023, Spring 2022, Spring 2021 Analysis and design of electronic circuits for communication systems, with an emphasis on integrated circuits for wireless communication systems. Analysis of noise and distortion in amplifiers with application to radio receiver design. Power amplifier design with application to wireless radio transmitters. Radio-frequency mixers, oscillators, phase-locked loops, modulators, and demodulators. Integrated Circuits for Communications: Read More [+] Rules & Requirements Prerequisites: 20N and 140 or equivalent Credit Restrictions: Students will receive no credit for Electrical Engineering 242A after taking Electrical Engineering 142. Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture, 1 hour of discussion, and 3 hours of laboratory per week Additional Details Subject/Course Level: Electrical Engineering/Graduate Grading: Letter grade. Formerly known as: Electrical Engineering 242M Integrated Circuits for Communications: Read Less [-] EL ENG 242B Advanced Integrated Circuits for Communications 3 Units Terms offered: Fall 2020, Fall 2014 Analysis, evaluation and design of present-day integrated circuits for communications application, particularly those for which nonlinear response must be included. MOS, bipolar and BICMOS circuits, audio and video power amplifiers, optimum performance of near-sinusoidal oscillators and frequency-translation circuits. Phase-locked loop ICs, analog multipliers and voltage-controlled oscillators; advanced components for telecommunication circuits. Use of new CAD tools and systems. Advanced Integrated Circuits for Communications: Read More [+] Rules & Requirements Prerequisites: EL ENG 142 and EL ENG 240 Credit Restrictions: Students will receive no credit for EL ENG 242B after completing EL ENG 242, or EL ENG W242B. A deficient grade in EL ENG 242B may be removed by taking EL ENG W242B. Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture per week Additional Details Subject/Course Level: Electrical Engineering/Graduate Grading: Letter grade. Instructor: Niknejad Formerly known as: Electrical Engineering 242 Advanced Integrated Circuits for Communications: Read Less [-] 40 Computer Science EL ENG C246 Parametric and Optimal Design of MEMS 3 Units Terms offered: Spring 2013, Spring 2012, Spring 2011 Parametric design and optimal design of MEMS. Emphasis on design, not fabrication. Analytic solution of MEMS design problems to determine the dimensions of MEMS structures for specified function. Trade- off of various performance requirements despite conflicting design requirements. Structures include flexure systems, accelerometers, and rate sensors. Parametric and Optimal Design of MEMS: Read More [+] Rules & Requirements Prerequisites: Graduate standing or consent of instructor Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture per week Additional Details Subject/Course Level: Electrical Engineering/Graduate Grading: Letter grade. Instructors: Lin, Pisano Formerly known as: 219 Also listed as: MEC ENG C219 Parametric and Optimal Design of MEMS: Read Less [-] EL ENG 247A Introduction to Microelectromechanical Systems (MEMS) 3 Units Terms offered: Fall 2022, Fall 2021, Fall 2020 This course will teach fundamentals of micromachining and microfabrication techniques, including planar thin-film process technologies, photolithographic techniques, deposition and etching techniques, and the other technologies that are central to MEMS fabrication. It will pay special attention to teaching of fundamentals necessary for the design and analysis of devices and systems in mechanical, electrical, fluidic, and thermal energy/signal domains, and will teach basic techniques for multi-domain analysis. Fundamentals of sensing and transduction mechanisms including capacitive and piezoresistive techniques, and design and analysis of micmicromachined miniature sensors and actuators using these techniques will be covered. Introduction to Microelectromechanical Systems (MEMS): Read More [+] Rules & Requirements Prerequisites: EECS 16A and EECS 16B; or consent of instructor required Credit Restrictions: Students will receive no credit for EE 247A after taking EE 147. Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture and 1 hour of discussion per week Additional Details Subject/Course Level: Electrical Engineering/Graduate Grading: Letter grade. Instructors: Maharbiz, Nguyen, Pister Introduction to Microelectromechanical Systems (MEMS): Read Less [-] Computer Science 41 EL ENG C247B Introduction to MEMS Design 4 Units Terms offered: Spring 2023, Spring 2022, Spring 2021, Spring 2020 Physics, fabrication, and design of micro-electromechanical systems (MEMS). Micro and nanofabrication processes, including silicon surface and bulk micromachining and non-silicon micromachining. Integration strategies and assembly processes. Microsensor and microactuator devices: electrostatic, piezoresistive, piezoelectric, thermal, magnetic transduction. Electronic position-sensing circuits and electrical and mechanical noise. CAD for MEMS. Design project is required. Introduction to MEMS Design: Read More [+] Rules & Requirements Prerequisites: Graduate standing in engineering or science; undergraduates with consent of instructor Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture and 1 hour of discussion per week Additional Details Subject/Course Level: Electrical Engineering/Graduate Grading: Letter grade. Instructors: Nguyen, Pister Formerly known as: Electrical Engineering C245, Mechanical Engineering C218 Also listed as: MEC ENG C218 Introduction to MEMS Design: Read Less [-] EL ENG W247B Introduction to MEMS Design 4 Units Terms offered: Prior to 2007 Physics, fabrication and design of micro electromechanical systems (MEMS). Micro and nano-fabrication processes, including silicon surface and bulk micromachining and non-silicon micromachining. Integration strategies and assembly processes. Microsensor and microactuator devices: electrostatic, piezoresistive, piezoelectric, thermal, and magnetic transduction. Electronic position-sensing circuits and electrical and mechanical noise. CAD for MEMS. Design project is required. Introduction to MEMS Design: Read More [+] Rules & Requirements Prerequisites: MAS-IC students only Credit Restrictions: Students will receive no credit for EE W247B after taking EE C247B or Mechanical Engineering C218. Hours & Format Fall and/or spring: 15 weeks - 3 hours of web-based lecture and 1 hour of web-based discussion per week Summer: 10 weeks - 4.5 hours of web-based lecture and 1.5 hours of web-based discussion per week Online: This is an online course. Additional Details Subject/Course Level: Electrical Engineering/Graduate Grading: Letter grade. Instructors: Nguyen, Pister Formerly known as: Electrical Engineering W245 Introduction to MEMS Design: Read Less [-] 42 Computer Science EL ENG 248C Numerical Modeling and Analysis: Nonlinear Systems and Noise 4 Units Terms offered: Prior to 2007 Numerical modelling and analysis techniques are widely used in scientific and engineering practice; they are also an excellent vehicle for understanding and concretizing theory. This course covers topics important for a proper understanding of nonlinearity and noise: periodic steady state and envelope ("RF") analyses; oscillatory systems; nonstationary and phase noise; and homotopy/continuation techniques for solving "difficult" equation systems. An underlying theme of the course is relevance to different physical domains, from electronics (e.g., analog/RF/mixed-signal circuits, high-speed digital circuits, interconnect, etc.) to optics, nanotechnology, chemistry, biology and mechanics. Hands-on coding using the MATLAB-based Berkeley Model Numerical Modeling and Analysis: Nonlinear Systems and Noise: Read More [+] Objectives & Outcomes Course Objectives: Homotopy techniques for robust nonlinear equation solution Modelling and analysis of oscillatory systems - harmonic, ring and relaxation oscillators - oscillator steady state analysis - perturbation analysis of amplitude-stable oscillators RF (nonlinear periodic steady state) analysis - harmonic balance and shooting - Multi-time PDE and envelope methods - perturbation analysis of periodic systems (Floquet theory) RF (nonlinear, nonstationary) noise concepts and their application - cyclostationary noise analysis - concepts of phase noise in oscillators Using MAPP for fast/convenient modelling and analysis Student Learning Outcomes: Students will develop a facility in the above topics and be able to apply them widely across science and engineering. Rules & Requirements Prerequisites: Consent of Instructor Hours & Format Fall and/or spring: 15 weeks - 4 hours of lecture per week Additional Details Subject/Course Level: Electrical Engineering/Graduate Grading: Letter grade. Instructor: Roychowdhury Numerical Modeling and Analysis: Nonlinear Systems and Noise: Read Less [-] EL ENG C249A Introduction to Embedded Systems 4 Units Terms offered: Fall 2022, Fall 2021, Fall 2020 This course introduces students to the basics of models, analysis tools, and control for embedded systems operating in real time. Students learn how to combine physical processes with computation. Topics include models of computation, control, analysis and verification, interfacing with the physical world, mapping to platforms, and distributed embedded systems. The course has a strong laboratory component, with emphasis on a semester-long sequence of projects. Introduction to Embedded Systems: Read More [+] Rules & Requirements Credit Restrictions: Students will receive no credit for Electrical Engineering/Computer Science C249A after completing Electrical Engineering/Computer Science C149. Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture and 3 hours of laboratory per week Additional Details Subject/Course Level: Electrical Engineering/Graduate Grading: Letter grade. Instructors: Lee, Seshia Formerly known as: Electrical Engineering C249M/Computer Science C249M Also listed as: COMPSCI C249A Introduction to Embedded Systems: Read Less [-] Computer Science 45 EL ENG 290D Advanced Topics in Electrical Engineering: Advanced Topics in Semiconductor Technology 1 - 3 Units Terms offered: Spring 2021, Fall 2014, Fall 2013 The 290 courses cover current topics of research interest in electrical engineering. The course content may vary from semester to semester. Advanced Topics in Electrical Engineering: Advanced Topics in Semiconductor Technology: Read More [+] Rules & Requirements Prerequisites: Consent of instructor Repeat rules: Course may be repeated for credit without restriction. Hours & Format Fall and/or spring: 15 weeks - 1-3 hours of lecture per week Additional Details Subject/Course Level: Electrical Engineering/Graduate Grading: Letter grade. Advanced Topics in Electrical Engineering: Advanced Topics in Semiconductor Technology: Read Less [-] EL ENG 290F Advanced Topics in Electrical Engineering: Advanced Topics in Photonics 1 - 3 Units Terms offered: Spring 2014, Fall 2013, Fall 2012 The 290 courses cover current topics of research interest in electrical engineering. The course content may vary from semester to semester. Advanced Topics in Electrical Engineering: Advanced Topics in Photonics: Read More [+] Rules & Requirements Prerequisites: Consent of instructor Repeat rules: Course may be repeated for credit without restriction. Hours & Format Fall and/or spring: 15 weeks - 1-3 hours of lecture per week Additional Details Subject/Course Level: Electrical Engineering/Graduate Grading: Letter grade. Advanced Topics in Electrical Engineering: Advanced Topics in Photonics: Read Less [-] EL ENG 290G Advanced Topics in Electrical Engineering: Advanced Topics in Mems, Microsensors, and Microactuators 1 - 3 Units Terms offered: Fall 2017, Fall 2016, Spring 2002 The 290 courses cover current topics of research interest in electrical engineering. The course content may vary from semester to semester. Advanced Topics in Electrical Engineering: Advanced Topics in Mems, Microsensors, and Microactuators: Read More [+] Rules & Requirements Prerequisites: Consent of instructor Repeat rules: Course may be repeated for credit without restriction. Hours & Format Fall and/or spring: 15 weeks - 1-3 hours of lecture per week Additional Details Subject/Course Level: Electrical Engineering/Graduate Grading: Letter grade. Formerly known as: Engineering 210 Advanced Topics in Electrical Engineering: Advanced Topics in Mems, Microsensors, and Microactuators: Read Less [-] EL ENG 290N Advanced Topics in Electrical Engineering: Advanced Topics in System Theory 1 - 3 Units Terms offered: Fall 2018, Fall 2017, Fall 2015 The 290 courses cover current topics of research interest in electrical engineering. The course content may vary from semester to semester. Advanced Topics in Electrical Engineering: Advanced Topics in System Theory: Read More [+] Rules & Requirements Prerequisites: Consent of instructor Repeat rules: Course may be repeated for credit without restriction. Hours & Format Fall and/or spring: 15 weeks - 1-3 hours of lecture per week Additional Details Subject/Course Level: Electrical Engineering/Graduate Grading: Letter grade. Advanced Topics in Electrical Engineering: Advanced Topics in System Theory: Read Less [-] 46 Computer Science EL ENG 290O Advanced Topics in Electrical Engineering: Advanced Topics in Control 1 - 3 Units Terms offered: Spring 2019, Fall 2018, Fall 2017 The 290 courses cover current topics of research interest in electrical engineering. The course content may vary from semester to semester. Advanced Topics in Electrical Engineering: Advanced Topics in Control: Read More [+] Rules & Requirements Prerequisites: Consent of instructor Repeat rules: Course may be repeated for credit without restriction. Hours & Format Fall and/or spring: 15 weeks - 1-3 hours of lecture per week Additional Details Subject/Course Level: Electrical Engineering/Graduate Grading: Letter grade. Advanced Topics in Electrical Engineering: Advanced Topics in Control: Read Less [-] EL ENG 290P Advanced Topics in Electrical Engineering: Advanced Topics in Bioelectronics 1 - 3 Units Terms offered: Spring 2019, Spring 2018, Fall 2017 The 290 courses cover current topics of research interest in electrical engineering. The course content may vary from semester to semester. Advanced Topics in Electrical Engineering: Advanced Topics in Bioelectronics: Read More [+] Rules & Requirements Prerequisites: Consent of instructor Repeat rules: Course may be repeated for credit without restriction. Hours & Format Fall and/or spring: 15 weeks - 1-3 hours of lecture per week Additional Details Subject/Course Level: Electrical Engineering/Graduate Grading: Letter grade. Advanced Topics in Electrical Engineering: Advanced Topics in Bioelectronics: Read Less [-] EL ENG 290Q Advanced Topics in Electrical Engineering: Advanced Topics in Communication Networks 1 - 3 Units Terms offered: Spring 2017, Spring 2016, Fall 2014 The 290 courses cover current topics of research interest in electrical engineering. The course content may vary from semester to semester. Advanced Topics in Electrical Engineering: Advanced Topics in Communication Networks: Read More [+] Rules & Requirements Prerequisites: Consent of instructor Repeat rules: Course may be repeated for credit without restriction. Hours & Format Fall and/or spring: 15 weeks - 1-3 hours of lecture per week Additional Details Subject/Course Level: Electrical Engineering/Graduate Grading: Letter grade. Advanced Topics in Electrical Engineering: Advanced Topics in Communication Networks: Read Less [-] EL ENG 290S Advanced Topics in Electrical Engineering: Advanced Topics in Communications and Information Theory 1 - 3 Units Terms offered: Fall 2018, Fall 2016, Fall 2009 The 290 courses cover current topics of research interest in electrical engineering. The course content may vary from semester to semester. Advanced Topics in Electrical Engineering: Advanced Topics in Communications and Information Theory: Read More [+] Rules & Requirements Prerequisites: Consent of instructor Repeat rules: Course may be repeated for credit without restriction. Hours & Format Fall and/or spring: 15 weeks - 1-3 hours of lecture per week Additional Details Subject/Course Level: Electrical Engineering/Graduate Grading: Letter grade. Advanced Topics in Electrical Engineering: Advanced Topics in Communications and Information Theory: Read Less [-] Computer Science 47 EL ENG 290T Advanced Topics in Electrical Engineering: Advanced Topics in Signal Processing 1 - 3 Units Terms offered: Fall 2018, Fall 2017, Fall 2016 The 290 courses cover current topics of research interest in electrical engineering. The course content may vary from semester to semester. Advanced Topics in Electrical Engineering: Advanced Topics in Signal Processing: Read More [+] Rules & Requirements Prerequisites: Consent of instructor Repeat rules: Course may be repeated for credit without restriction. Hours & Format Fall and/or spring: 15 weeks - 1-3 hours of lecture per week Additional Details Subject/Course Level: Electrical Engineering/Graduate Grading: Letter grade. Advanced Topics in Electrical Engineering: Advanced Topics in Signal Processing: Read Less [-] EL ENG 290Y Advanced Topics in Electrical Engineering: Organic Materials in Electronics 3 Units Terms offered: Spring 2014, Spring 2013, Fall 2009 Organic materials are seeing increasing application in electronics applications. This course will provide an overview of the properties of the major classes of organic materials with relevance to electronics. Students will study the technology, physics, and chemistry of their use in the three most rapidly growing major applications--energy conversion/generation devices (fuel cells and photovoltaics), organic light-emitting diodes, and organic transistors. Advanced Topics in Electrical Engineering: Organic Materials in Electronics: Read More [+] Rules & Requirements Prerequisites: EL ENG 130; and undergraduate general chemistry Repeat rules: Course may be repeated for credit without restriction. Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture per week Additional Details Subject/Course Level: Electrical Engineering/Graduate Grading: Letter grade. Instructor: Subramanian Advanced Topics in Electrical Engineering: Organic Materials in Electronics: Read Less [-] EL ENG W290C Advanced Topics in Circuit Design 3 Units Terms offered: Prior to 2007 Seminar-style course presenting an in-depth perspective on one specific domain of integrated circuit design. Most often, this will address an application space that has become particularly relevant in recent times. Examples are serial links, ultra low-power design, wireless transceiver design, etc. Advanced Topics in Circuit Design: Read More [+] Rules & Requirements Prerequisites: MAS-IC students only Credit Restrictions: Students will receive no credit for W290C after taking 290C. Repeat rules: Course may be repeated for credit without restriction. Hours & Format Fall and/or spring: 15 weeks - 3 hours of web-based lecture per week Summer: 10 weeks - 4.5 hours of web-based lecture per week Online: This is an online course. Additional Details Subject/Course Level: Electrical Engineering/Graduate Grading: Letter grade. Advanced Topics in Circuit Design: Read Less [-] EL ENG C291 Control and Optimization of Distributed Parameters Systems 3 Units Terms offered: Fall 2017, Spring 2016, Spring 2015, Spring 2014 Distributed systems and PDE models of physical phenomena (propagation of waves, network traffic, water distribution, fluid mechanics, electromagnetism, blood vessels, beams, road pavement, structures, etc.). Fundamental solution methods for PDEs: separation of variables, self-similar solutions, characteristics, numerical methods, spectral methods. Stability analysis. Adjoint-based optimization. Lyapunov stabilization. Differential flatness. Viability control. Hamilton-Jacobi-based control. Control and Optimization of Distributed Parameters Systems: Read More [+] Rules & Requirements Prerequisites: ENGIN 7 and MATH 54; or consent of instructor Hours & Format Fall and/or spring: 15 weeks - 3 hours of lecture per week Additional Details Subject/Course Level: Electrical Engineering/Graduate Grading: Letter grade. Also listed as: CIV ENG C291F/MEC ENG C236 Control and Optimization of Distributed Parameters Systems: Read Less [-]