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(4 credits) Wire antennas: dipoles, loops and traveling-wave antennas. Topics covered include client/server protocols, security, information retrieval and search engines, scalable data processing, and fault tolerant systems. Prerequisite: EECS 281 and (MATH 214 or 217 or 296 or 417 or 419). Interconnection networks. Teams of 3-5 students complete projects based primarily on their individual interests. Traveling waves and phasors. Prerequisite: permission of instructor. Introduction to semiconductors in terms of atomic bonding and electron energy bands. Topics will be selected from various subareas such as physics based vision, geometry, motion and tracking, reconstruction, grouping and segmentation, recognition, activity and scene understanding, statistical methods and learning, systems and applications. • You may be required to take EECS 498 and TCHNCLCM 497 concurrently • Consult undergraduate advising office for more information (BBB 2808) • This course is almost exclusively project-based • An opportunity for high impact! Instruction Mode: Online – Synchronous The course discusses advanced topics and current research in computer vision. CourseProfile (ATLAS), EECS 435. Group projects. Prerequisite: Sophomore or Junior Standing, and Permission of Instructor. Instruction Mode: Online – Synchronous Prerequisite: graduate standing or permission of instructor. User Interface Development Substantial student-defined team design project. Advanced topics in data mining. (3 credits) Prerequisite: EECS 482. The course includes a range of topics such as the quantum vibrator, resonant tunneling, quantum circuits, a quantum flip flop, quantum information, quantum vacuum, and the role of quantum behavior in nano-devices and materials. Introduction to Algorithms CourseProfile (ATLAS), EECS 530 (APPPHYS 530). Electromagnetic Scattering out-of-order, multi-core, SMT) processor using an HDL. Our research activities, which range from the nano- to the systems level, are supported by more than $81M in funding annually — a clear indication of the strength of our programs and our award-winning faculty. Instruction Mode: Online – Asynchronous Students write several substantial programs implementing protocols at different layers of the network stack. Students present a research proposal to be approved by both the faculty member and the chief program advisor or designate. Instruction Mode: Online – Synchronous Prerequisite: EECS 334 or EECS 434 or graduate standing. Computer-aided design for MEMS layout, fabrication and analysis. CourseProfile (ATLAS), EECS 548 (SI 649). Principles of Microelectronics Process Technology CourseProfile (ATLAS), EECS 524. (4 credits)  CourseProfile (ATLAS), EECS 201. CourseProfile (ATLAS), EECS 467. Instruction Mode: Online – Synchronous CourseProfile (ATLAS), EECS 493. Instruction Mode: Online – Synchronous Integrated circuit fabrication overview, relationships between processing choices and device performance characteristics. Instruction Mode: Online – Asynchronous Team-based, user-centered design and development of complex software systems incorporating effective design strategies and project management methodologies. CourseProfile (ATLAS), EECS 525. CourseProfile (ATLAS), EECS 311. Dissertation/Pre-Candidate CourseProfile (ATLAS), EECS 402. CourseProfile (ATLAS), EECS 699. Prerequisite: EECS 215 and PHYSICS 240 or 260. Prerequisite: EECS 501. Project modules include measurement or respiratory volume and flow rates, biopotentials (electrocardiogram), and optical analysis of arterial blood oxygen saturation (pulse-oximetry). Prerequisite: EECS 203, MATH 425 (Stat 425). Scope, procedure instantiation, recursion, abstract data types and parameter passing methods. (4 credits) [Fewer than two previous elections of EECS 280 (incl. Instruction Mode: Online – Synchronous Design, development, and application of digital games. Instruction Mode: Online – Synchronous (4 credits) Architectures of single-chip DSP processors. Prerequisite: prior arrangement with instructor; mandatory satisfactory/unsatisfactory. Multiple team projects, culminating in a major design experience (MDE) project. CourseProfile (ATLAS), EECS 516 (BIOMEDE 516). Software Development for Accessibility CourseProfile (ATLAS), EECS 281. Design of efficient data structures and analysis of the running time and space requirements of algorithms in the worst and average cases. CourseProfile (ATLAS), EECS 483. Instruction Mode: Online – Synchronous Introduction to the core concepts of AI, organized around building computational agents. Advanced topics on stochastic systems such as stochastic calculus, nonlinear filtering, stochastic adaptive control, decentralized control and queuing networks. (3 credits) Minimum grade of C required for enforced prerequisites. (4 credits) Instruction Mode:   Instruction Mode: Online – Synchronous Topics include big data systems, frequent itemsets, similarity and cluster analysis, clasification, dimensionality reduction, mining of networks, time series and data streams, and applications (e.g., social network analysis, web search). Discussion of major programming approaches used in the design and development of knowledge-based systems. Prerequisite: EECS 423, EECS 512 and/or permission of instructor. (4 credits). Emphasizes research methods and practice, through explicit instruction, analysis of current literature, and a term project devoted to replicating published findings. Quadrature decoding. Delaunary triangulations and Voronoi diagrams. CourseProfile (ATLAS), EECS 565. The course will teach concepts and present case studies through lectures, homework, design problems, and a final project. Current Topics in Databases Matrix Methods for Signal Processing, Data Analysis and Machine Learning Practical Programming in Java General properties and design of linear and nonlinear solid state microwave circuits including: amplifier gain blocks, low-noise, broadband and power amplifiers, oscillators, mixer and multiplier circuits, packaging, system implementation for wireless communication. Web search, including Web crawling, link analysis, search engine development, social media, and crowdsourcing. Instruction Mode: Online – Synchronous Semiconductor processing techniques: oxidation, diffusion, deposition, etching, photolithography. (3 credits) Design of algorithms for nonnumeric problems involving sorting, searching, scheduling, graph theory and geometry. Students submit and present a thesis to be evaluated by the sponsoring faculty member and second reader. Topics of current interest selected by the faculty. Numerical techniques for antennas and scattering; integral representation: solutions of integral equations: method of moments, Galerkin’s technique, conjugate gradient FFT; finite element methods for 2-D and 3-D simulations; hybrid finite element/boundary integral methods; applications: wire, patch and planar arrays; scattering composite structures. Prerequisite: (Junior or senior standing) or graduate standing. Instruction Mode: Online – Synchronous Gaussian beams and ABCD law. Master of Engineering Team Project CourseProfile (ATLAS), EECS 627. Geometry, kinematics, differential kinematics, dynamics, and control of robot manipulators. Minimum grade of “C” required for enforced prerequisite. Verification and testing. Sampling leading to basic digital signal processing using the discrete-time Fourier and the discrete Fourier transform. (4 credits) Self-testing circuits and systems. Special Topics in Software Systems Prerequisite: EECS 320 or graduate standing. (4 credits) Medical Imaging Systems CourseProfile (ATLAS), EECS 513. (A project is assigned.) Instruction Mode: Online – Synchronous Prerequisite: Graduate Standing or permission of instructor. Design verification: simulation, formal techniques, and post-silicon validation. Advanced very large scale integrated (VLSI) circuit design. (3 credits) Prerequisite: EECS 501, EECS 554. CourseProfile (ATLAS), EECS 544. Prerequisite: EECS 460 or MECHENG 461. CourseProfile (ATLAS), EECS 381. Encapsulation, automatic memory management, exceptions, generic programming with templates and function objects, Standard Library algorithms and containers. CourseProfile (ATLAS), EECS 285. CourseProfile (ATLAS), EECS 528. (3 credits) Basic principles of optics: light sources and propagation of light; geometrical optics, lenses and imaging; ray tracing and lens aberrations; interference of light waves, coherent and incoherent light beams; Fresnel and Fraunhofer diffraction. Instruction Mode: Online – Synchronous Theory and application of matrix methods to signal processing, data analysis and machine learning. Master’s Thesis Scattering by half plane (Wiener-Hopf method) and wedge (Maliuzhinets method); edge diffraction. (4 credits) (Students who have previously enrolled in 551 or 453 cannot get credit for 505.) Prerequisite: EECS 501. These include the flash, folding, multi-step and pipeline Nyquist rate, architectures. Instruction Mode: Online – Synchronous Algorithms using selection and iteration (decision making, finding maxima/minima, searching, sorting, simulation, etc.) (3-4 credits) Plasma physics applied to electrical gas discharges used for material processing. Basic techniques for analysis and design of controllers applicable in any industry (e.g. (4 credits) Website for UMich EECS course. (4 credits) Here's my commentary on some of the classes I have taken at umich. Syllabus; Tentative Schedule; Projects. Prerequisite: EECS 311 and EECS 320 or graduate standing. Prerequisite: EECS 376 or graduate standing. CourseProfile (ATLAS), EECS 575. Enrollment Policy. CourseProfile (ATLAS), © 2021 Detailed study of static current-voltage characteristics and models for small and large signal behavior. Prerequisite: EECS 280 and (EECS 203 or Math 465 or Math 565). CourseProfile (ATLAS), EECS 557. D-Algorithm and PODEM. Lecture, seminar or laboratory. CourseProfile (ATLAS), EECS 489. Lecture and laboratory. Operating system kernel support; distributed system services including replication, caching, file system management, naming, clock synchronization and multicast communication. (4 credits) Additional topics such as sentiment analysis, text generation, and deep learning for NLP. Laboratory experience with power electronic circuits. Minimum grade of “C” required for enforced prerequisites. This course covers the fundamentals of patents for engineers. Prerequisite: EECS 216. EECS 441. Prerequisite: graduate standing. Compile-time vs. run-time tradeoffs. Oral presentation and/or written report due at end of term. Instruction Mode:  Digital Communication Theory Instruction Mode: Hybrid – Synchronous, Online – Asynchronous Major Design Experience Professionalism Shared-memory coherence and consistency. Prerequisite: EECS 482 or EECS 489 or graduate standing. Introduction to compiler construction. Prerequisite: EECS 460 or AEROSP 348 or MECHENG 461 and AEROSP 550 (EECS 560). AC-DC, DC-DC switch-mode power converter topologies. The course presents both the theoretical and practical design, analysis, construction, and measurement of circuits and components in different types of power converters. We explore entrepreneurship, team management, product design, project management, code development, and testing within the context of mobile app development. Key topics of current research interest in ultrafast phenomena, short wavelength lasers, atomic traps, integrated optics, nonlinear optics and spectroscopy. Fundamental concepts and methods in data mining, and practical skills for mining massive, real data on distributed frameworks (e.g., Hadoop). Linear response, Kramers-Kronig relations, and pulse propagation. Introduction to Machine Learning Advised Prerequisite: ENGR 100 or ENGR 101 or ENGR 151 or EECS 180 or EECS 280. Boolean algebra, digital design techniques, logic gates, logic and state minimization, standard combinational circuits, latches and flip-flops, sequential circuits, synthesis of synchronous sequential circuits, state machines, FPGAs, memories, arithmetic circuits, and computer-aided design. Instruction Mode:  Prerequisite: Particular attention to compression of images (JPEG), video (MPEG), speech (CELP) and audio (MP3). Pole placement/observer design. Micro-devices covered include resonators, switches, filters, tunable passive devices and reconfigurable modules. Student projects based on recent image processing literature. CourseProfile (ATLAS), EECS 526. Computer Architecture (3 credits) Minimum grade of “C” required for enforced prerequisites. CourseProfile (ATLAS), EECS 491. Equalization. Electrical biophysics of nerve and muscle; electrical conduction in excitable tissue; quantitative models for nerve and muscle, including the Hodgkin Huxley equations; biopotential mapping, cardiac electrophysiology, and functional electrical stimulation; group projects. This course uses a sequence of hands-on projects to bring into sharper focus the following concepts in the data-to-decision cycle: 1. how smart (or bad) data can positively (or negatively) affect decisions in the design and operation of an engineering system; 2. how to acquire such data, clean and store it via appropriate pre-processing and post-processing it for aiding reproducibility; 3. how to display, render, deploy and interpret it in the context of a real or simulated close-up loop type cloud based engineering system; and finally, 4. how to communicate the shortcomings and vulnerabilities of such systems, including plug-and-play systems using pre-trained off-the-shelf deep learning models, when integrated into a decision-making system; 5. conceptualization and execution of an open-ended, reproducible cloud-based design project. Channel Coding Theory Prerequisite: none. Information Theory Prerequisite: EECS 281. Topics of current interest selected by the faculty. Instruction Mode: Online – Synchronous CourseProfile (ATLAS), EECS 443. Instruction Mode: In-Person – Synchronous, Online – Asynchronous/Synchronous Design of hardware and software for modern embedded systems. Course may be elected more than once. The limiting case of electro- and magneto-statics. Specific topics vary each time the course is offered. Minimum grade of “C” required for enforced prerequisite. (1-4 credits) (to be arranged) DC motors. Prerequisite: permission of instructor. Metric spaces, normed linear spaces, Hilbert spaces, resolution spaces. Students are expected to work in project teams. Cannot receive credit if student has credit for EECS 183 or ENGR 101 or ENGR 151 (3-4 credits). CourseProfile (ATLAS), EECS 520. Advisory Prerequisite: EECS 463 or graduate standing. DC machines. EECS 497: Major Design Projects. In an effort to ensure all students have opportunity to enroll in courses during the registration period, the CSE division will limit enrollment in a specified set of courses. (1 credit) (4 credits) Non-photorealistic rendering. Advisory Prerequisite: EECS 463, or permission of instructor or graduate standing. Credit for college-level introductory programming coursework based on a satisfactory score on an approved exam (e.g., a score of 5 on the AP Computer Science A exam) or on transfer credit for an approved introductory programming course at another college. Digital Integrated Technology The theory of channel coding for reliable communication and computer memories. Introduction to nonlinear optics; harmonic generation, optical rectification, four-wave mixing, self-focusing and self-phase modulation. Minimum grade of “C” required for enforced prerequisites. Optical information processing, including spatial matched filtering. PCB design including power integrity and electromagnetic interference. For the past several terms, many CS courses have faced significant enrollment pressure resulting in long waitlists. System-theoretic concepts: causality, controllability, observability, realizations, canonical decomposition, stability. Applications examined include electric propulsion drives for electric/hybrid vehicles, generators for wind turbines, and high-speed motor/alternators for flywheel energy storage systems. Prerequisite: ENGR 101 or ENGR 151 or EECS 180 or EECS 183. Principles of designing application-specific computer systems that interact with the physical world. Other topics covered include litigation, ethics and licensing. CourseProfile (ATLAS), EECS 543. grades of W.I, VI, and AUD)] Data Science Seminar Programming paradigms including group communication, RPC, distributed shared memory, and distributed objects. CourseProfile (ATLAS), EECS 537 (APPPHYS 537). Parallel Computing CourseProfile (ATLAS), EECS 562 (AEROSP 551). Algorithims include gradient-based methods, proximal methods, and duality-based methods. CourseProfile (ATLAS), EECS 370. (3 credits). Introduces social computing research, and relevant web-based tools for creating systems that allow multiple users to interact. Digital System Testing Instruction Mode: Honestly we believe this should be a mandatory course over EECS 496 and TC 497 because 481 does a better job at preparing you what to really expect then those two classes. Instruction Mode: Online – Synchronous CourseProfile (ATLAS), EECS 510. (4 credits) Review of interface electronics for sense and drive and their influence on device performance, interface standards, MEMS and circuit noise sources, packaging and assembly techniques, testing and calibration approaches and communication in integrated microsystems. CourseProfile (ATLAS), EECS 662 (MECHENG 662). CourseProfile (ATLAS), EECS 574. CourseProfile (ATLAS), EECS 634 (APPPHYS 611) (Physics 611). EECS 270: Computer Organization. CourseProfile (ATLAS), EECS 461. Instruction Mode: Online – Synchronous Long-channel device I-V review, short-channel MOSFET I-V characteristics including velocity saturation, mobility degradation, hot carriers, gate depletion. Design techniques such as approximation, branch-and-bound, divide-and-conquer, dynamic programming, greed and randomization applied to polynomial and NP-hard problems. (4 credits) Topics include supervised learning (regression, classification, kernel methods, neural networks, and regularization) and unsupervised learning (clustering, density estimation, and dimensionality reduction). Linear Systems Theory CourseProfile (ATLAS), EECS 497. Instruction Mode: Online – Synchronous Prerequisite: EECS 562 or MECHENG 548. Topics will be drawn from a variety of areas such as mandatory and discretionary security policies, secure storage, security kernels, trust management, preventing software vulnerabilities, applied cryptography, network security. Theoretical topics include subspaces, eigenvalue and singular value decomposition, projection theorem, constrained, regularized and unconstrained least squares techniques and iterative algorithms. Instruction Mode: Online – Synchronous CourseProfile (ATLAS), EECS 554. Prerequisite: EECS 281 and EECS 370 or graduate standing in CSE. Prerequisite: EECS 530 and graduate standing. Analog Integrated Circuits Rapid prototyping of embedded systems. Prerequisite: EECS 537 or EECS 538 or EECS 530. (4 credits)  Design problems unique to multivariable systems. Applications such as image deblurring, ranking of webpages, image segmentation and compression, social networks, circuit analysis, recommender systems and handwritten digit recognition. Foundations of Computer Science (3 credits)  Biomedical applications include dermatology, cardiology and opthamology. Prerequisite: EECS 470 or permission of instructor. Sensitivity, robustness, and design tradeoffs. Instruction Mode: Hybrid – Synchronous, Online – Synchronous Introduction to nonrelativistic quantum mechanics. Optimization of finite-state machines. Lectures and laboratory. This course may be repeated for credit. CourseProfile (ATLAS), EECS 216. Laser mode-locking and ultrashort pulse generation. Stability analysis using Liapunov, input-output and asymptotic methods. MEMS-based transducer design and electrical, mechanical and thermal limits. Prerequisite: EECS 216 and EECS 301. Advised Prerequisite: (MATH 115 or 116 or 119 or 120 or 121 or 156 or 175 or 176 or 185 or 186 or 214 or 215 or 216 or 217 or 255 or 256 or 285 or 286 or 295 or 296 or 417 or 419). Theory of image formation and Fourier transformation by lenses. Principles of semiconducting lasers; gain-current relationships, radiation fields, optical confinement and transient effects. CourseProfile (ATLAS), EECS 564. Correct Operation for Processors and Embedded Systems Introduction and fundamentals of physical, optical and electrical properties of amorphous and microcrystalline semiconductor based devices: MIM structures, Schottky diodes, p-i-n junctions, heterojunctions, MIS structures, thin-film transistors, solar cells, threshold and memory switching devices and large area x-ray radiation detectors. Groups design an advanced (e.g. Special topics of current interest in solid-state devices, integrated circuits, microwave devices, quantum devices, noise, plasmas. Mask making, pattern transfer, oxidation, ion implantation and metallization. Real-time operating systems. Optimization Methods in Signal Processing and Machine Learning  Applications of convex geometry and convex optimization in control. 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Synchronous, Online – Synchronous advanced very large scale integrated ( VLSI ) circuit design as laser and! And MOSFETs design addressing the areas of solid-state Electronics Prerequisite: undergraduate calculus linear..., compressed sensing, power, and building a complex interactive multi-user..

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