Design and development of a search engine. Minimum grade of “C” required for enforced prerequisites. Prerequisite: Senior standing, EECS 281, and at least four credit hours of Upper Level Electives from list in either Computer Science or Computer Engineering. Instruction Mode: Online – Synchronous (3 credits) Semiconductor Lasers and LEDs Introduction to Artificial Intelligence Minimum grade of “C” required for enforced prerequisites. (4 credits) [Fewer than two previous elections of EECS 203 (incl. Probability and Random Processes Applications of convex geometry and convex optimization in control. (4 credits) Prerequisite: Graduate Standing or permission of instructor. Prerequisite: EECS 429. Analysis and design of BJT and MOS multi-transistor amplifiers. Introduction to: PN junctions, metal-semiconductor junctions, light detectors and emitters; bipolar junction transistors, junction and MOSFETs. (4 credits). Real-time operating systems. Scope, procedure instantiation, recursion, abstract data types and parameter passing methods. CourseProfile (ATLAS), EECS 540 (APPPHYS 540). These highly-successful textbooks are used all over the country. MWF 10:30-11:30AM EECS 1200 THE CORRECT TIME FOR THE FINAL EXAM IS DEC. 20, 4-6 PM! Computer and Network Security Lecture, seminar, or laboratory. Digital System Testing Prerequisite: permission of instructor. Instruction Mode: Online – Synchronous, Hybrid – Synchronous (1-4 credits) Instruction Mode: Online – Synchronous Principles and practice of distributed system design. Geometrical and physical theories of diffraction. (4 credits) Prerequisite: EECS 421. The Regents of the University of Michigan, Michigan Engineering | College Administration, 1221 Beal Avenue, Ann Arbor, MI 48109-2102, Safety Information | Privacy Policy | CourseProfile (ATLAS), EECS 470. Theoretical topics include subspaces, eigenvalue and singular value decomposition, projection theorem, constrained, regularized and unconstrained least squares techniques and iterative algorithms. CourseProfile (ATLAS), EECS 600 (IOE 600). Instruction Mode: In-Person – Synchronous Introduction to information visualization. Instruction Mode: Online – Synchronous Principles of modern medical imaging systems. User Interface Development Analysis and synthesis of linear arrays. CourseProfile (ATLAS), EECS 530 (APPPHYS 530). Instruction Mode: Online – Synchronous Principles of engineering design for electrical engineering systems. Basic concepts of probability theory. Doing an independent study? Digital communication signals and systems; fundamental limits on reliable communications, energy and bandwidth efficiency trade-offs; optimum receiver principles, modulation techniques including phase shift keying, quadrature modulation and OFDM; block and convolutional coding and decoding; applications to wireless communication systems; optional topics include synchronization, quantization and lossless compression of signals, fundamental limits of compression, role of entropy. Topics will be drawn from a variety of operating systems areas such as distributed systems and languages, networking, security and protection, real-time systems, modeling and analysis, etc. Instruction Mode: Online – Synchronous, Hybrid – Synchronous Web search, including Web crawling, link analysis, search engine development, social media, and crowdsourcing. Prerequisite: EECS 281 and EECS 370 or graduate standing in CSE. Prerequisite: EECS 330 and EECS 334. CourseProfile (ATLAS), EECS 524. CourseProfile (ATLAS), EECS 633. Introduction to electronic circuits. Transmission-line theory, microstrip and coplanar lines, S-parameters, signal-flow graphs, matching networks, directional couplers, low-pass and band-pass filters, diode detectors. Small distrubance (linear) analysis techniques are presented, along with methods for assessing large disturbance (nonlinear) behavior. Emphasizes construction of systems using graphics application programming interfaces (APIs) and analysis tools. Topics include location and context awareness, mobile data access, resource management, consistency protocols, mobile and ad hoc networking, networked sensors, security and privacy. Students program methods; lectures and labs emphasize computational thinking and reasoning. Laboratory techniques for plasma ionization and diagnosis relevant to plasma processing, propulsion, vacuum electronics, and fusion. Prerequisite: EECS 414. Pulse width modulation. (4 credits) Provides an opportunity for undergraduate students to work in on substantial research problems in EECS or areas of special interest such as design problems. CourseProfile (ATLAS), EECS 460. Biomedical Instrumentation and Design Instruction Mode: Online – Synchronous Prerequisite: EECS 281 or equivalent. Readings from recent research papers. Theory of Neural Computation Instruction Mode: In Person – Synchronous, Online – Synchronous, In Person – Asynchronous CourseProfile (ATLAS), EECS 495. Data Structures and Algorithms CourseProfile (ATLAS), EECS 300. (3 credits) Mobile App Development for Entrepreneurs CourseProfile (ATLAS), EECS 505. Stochastic adaptive control: Markov chains, self-tuning regulators, bandit problems. Prerequisite: EECS 281. Equilibrium statistics of electrons and holes. CourseProfile (ATLAS), EECS 536. Introduction to Machine Learning 100-level dept: 2 … It covers concepts such as information need, documents and queries, indexing and searching, retrieval evaluation, multimedia and hypertext search, Web search, as well as bibliographical databases. Acceleration algorithms: culling and level-of-detail. Design of algorithms for idealized models. CourseProfile (ATLAS), EECS 535. Prerequisite: EECS 330. (4 credits) Parallel Computer Architecture Special Topics CourseProfile (ATLAS), EECS 892. Students are expected to be familiar with basic concepts of programming, such as control flow (e.g. CourseProfile (ATLAS), EECS 312. Programming and Introductory Data Structures Plasmonics Prerequisite: (EECS 203 or Math 465 or Math 565 or EECS 270) and EECS 280. CourseProfile (ATLAS), EECS 200. Instruction Mode: Online – Synchronous Several programming assignments. Samuel’s strategies, realistic neural networks, connectionist systems, classifier systems and related models of cognition. Fundamental limits in coding and modulation. Instruction Mode: In Person – Asynchronous, Hybrid – Synchronous, Online – Synchronous Topics of current interest in electrical engineering and computer science. CourseProfile (ATLAS), EECS 403. A hands-on, project based introduction to the principles of robotics and robot design. Linear quadratic Gaussian based design methods. CourseProfile (ATLAS), EECS 580. (4 credits) Instruction Mode: Online – Synchronous CourseProfile (ATLAS), EECS 491. Horns, reflector and lens antennas. Introduction to algorithm analysis and O-notation; Fundamental data structures including lists, stacks, queues, priority queues, hash tables, binary trees, search trees, balanced trees and graphs; searching and sorting algorithms; recursive algorithms; basic graph algorithms; introduction to greedy algorithms and divide and conquer strategy. Below I will give you my suggestions based on the courses I have taken. Coping with intractability. Semiconductor processing techniques: oxidation, diffusion, deposition, etching, photolithography. CourseProfile (ATLAS), EECS 584. Program language syntax and static and runtime semantics. Four aspects of starting high-tech companies are discussed: opportunity and strategy, creating new ventures, functional development, and growth and financing. Special Topics. CourseProfile (ATLAS), EECS 473. MEMS-based transducer design and electrical, mechanical and thermal limits. CourseProfile (ATLAS), EECS 553. Instruction Mode: Online – Synchronous Instruction Mode: Online – Synchronous Instruction Mode: Online – Synchronous Theory and application of matrix methods to signal processing, data analysis and machine learning. Machine Learning (4 credits) Prerequisite: EECS 484 or permission of instructor. Error correcting codes; linear, cyclic and convolutional codes; encoding and decoding algorithms; performance evaluation of codes on a variety of channels. Prerequisite: EECS 330. Database design, integrity, normalization, access methods, query optimization, transaction management and concurrency control and recovery. Prerequisite: ((Phys 240 or 260) and EECS 215 and EECS 216) or graduate standing. Prerequisite: (EECS 215 and EECS 216 and preceded or accompanied by EECS 320) or graduate standing. Instruction Mode: Online – Synchronous Introduction to Java programming, including language features, design principles, and programming practices. Analysis of Electric Power Distribution Systems and Loads Geometry, kinematics, differential kinematics, dynamics, and control of robot manipulators. Instruction Mode: Online – Synchronous Electrical Engineering Systems Design I (4 credits) Computational Data Science and Machine Learning  Prerequisite: graduate standing or permission of instructor. Multiple team projects consisting of design and implementation of a robot. (4 credits) CourseProfile (ATLAS), EECS 370. This course introduces a body of quantitative techniques for modeling and analyzing natural language and for extracting useful information from texts. Instruction Mode: Online – Synchronous Discussion of major programming approaches used in the design and development of knowledge-based systems. Advanced Database Systems Natural Language Processing Autocode generation for rapid prototyping. Students who have previously enrolled in 453 or 505 cannot get credit for 551. Instruction Mode: Hybrid – Synchronous, Online – Synchronous Introduction to nonrelativistic quantum mechanics. Advised Prerequisite: EECS 380 or concurrent election of one of SI 503 or LING 541; and Graduate Standing. Best practices in the software engineering of mobile applications and best practices of software entrepreneurs in the design, production and marketing of mobile apps. Lecture and laboratory. CourseProfile (ATLAS), EECS 592. Exam/Transfer Introductory Computer Programming Credit  DC motors. Topics covered include recent approaches in leakage control, high speed on-chip communication, memory design, soft error failures, noise analysis and control, error tolerant design and new circuit families. (2-8 credits); (1-4 credits) (4 credits) (Credit cannot be obtained for both EECS 492 and EECS 592.) Instruction Mode: Online – Synchronous Detection: simple, composite, binary and multiple hypotheses. (3 credits) (4 credits) Students will be introduced to nanofabrication and characterization techniques. (4 credits) CourseProfile (ATLAS), EECS 590. AC-DC, DC-DC switch-mode power converter topologies. Introduction and fundamentals to the passive, active, reflective and emissive flat panel display technologies. Prerequisite: EECS 215 and PHYSICS 240 or 260. EECS Building Access and Student Advising, Information, Communication, and Data Science, Electrical Engineering and Computer Science Department, The Regents of the University of Michigan. Specific topics vary each time the course is offered. Prerequisite: EECS 413 or permission of instructor. CourseProfile (ATLAS), EECS 428. Power systems overview; Fundamentals: phasors, complex power, three phases; transformer modeling; Transmission line modeling; Power flow analysis; Power system control; Protection; Economic operation and electricity markets; Impact of renewable generation on grid operation and control. Neural Models and Psychological Processes Sufficient time to read and understand two 30-page research papers per week. Minimum grade of “C” required for enforced prerequisite. Prerequisite: EECS 470 or permission of instructor. To be elected by EE and EES students pursuing the master’s thesis option. To be elected by EECS students pursuing the Master of Engineering degree. Advanced MEMS Devices and Technologies Principles of estimation, linear filtering and detection. Physics of operation of three terminal device structures important for high frequency analog or high speed digital applications. Prerequisite: permission of instructor. CourseProfile (ATLAS), EECS 591. Instruction Mode: Online – Synchronous Microwave Remote Sensing I: Radiometry CourseProfile (ATLAS), EECS 444. (3 credits) These thought leaders are invited from academia, industry and government. CourseProfile (ATLAS), EECS 406 (ENGR 406). NOTE: how courses will be delivered is subject to change pending potential updates to University policy in the near future. Minimum grade of “C”. Minimum grade requirement of C- for enforced prerequisites. CourseProfile (ATLAS), EECS 555. Min grade of “C”. Compiler Construction EECS 441. The class focus is processor-specific compilation techniques, thus familiarity with both computer architecture and compilers is recommended. Prerequisite: Undergraduate Calculus, Linear Algebra, Probability and Programming. Theoretical foundations. Data link control: error correction, protocol analysis, framing. Prerequisite: EECS 482 or EECS 489 or graduate standing. Introduction to Signals and Systems Prerequisite: graduate standing (3 credits) (4 credits) (3 credits) Topics include: camera models, multi-view geometry, reconstruction, some low-level image processing, and high-level vision problems like object and scene recognition. (4 credits) Micromachining technologies such as laser machining and microdrilling, EDM, materials such as SiC and diamond. Prerequisite: EECS 281 or EECS 478 or graduate standing. Performance analysis. (4 credits) Design of Digital Control Systems (2 credits) (3 credits) This course will examine computational models of human cognitive processes. Power electronic drives, motion control. Power converter topologies. Plane, cylindrical, and spherical waves. (3 credits) Message delay: Markov processes, queuing, delays in statistical multiplexing, multiple users with reservations, limited service, priorities. ... All the contents of the course website is required reading. Additional topics include sound navigation and ranging (SONAR), tracking and guidance systems, and computer-controlled systems. Emphasis on both the potential breadth of application and intuitive reasonableness of various models. CourseProfile (ATLAS), EECS 538 (APPPHYS 550) (PHYSICS 650). Production Systems Engineering (PSE) investigates fundamental laws that govern production systems and utilizes them for analysis, design, and continuous improvement. CourseProfile (ATLAS), © 2021 (3 credits) Emphasizes rigorous mathematical study in terms of algorithmic complexity. Instruction Mode:  Discrete Mathematics Prerequisite: EECS 280. CourseProfile (ATLAS), EECS 501. Micro-devices covered include resonators, switches, filters, tunable passive devices and reconfigurable modules. Design of Power Electronics Lecture and laboratory. It also covers the optimization methods required to solve planning and operational problems including economic dispatch, optimal power flow, and unit commitment. Query languages such as SQL, forms, embedded SQL, and application development tools. Instruction Mode: Online – Synchronous Linear response, Kramers-Kronig relations, and pulse propagation. Prerequisite: EECS 311 and EECS 320 or graduate standing. CourseProfile (ATLAS), EECS 643 (PSYCH 643). CourseProfile (ATLAS), EECS 700. Diffraction, Fresnel and Fraunhofer. Techniques: scalar and vector quantization; transform and differential coding; variable-length, Lempel-Ziv and arithmetic lossless coding. Case studies. Techniques for routing and clock tree design. Programming techniques in Standard C++ for large-scale, complex, or high-performance software. We explore entrepreneurship, team management, product design, project management, code development, and testing within the context of mobile app development. CourseProfile (ATLAS), EECS 418. Relations between complexity classes, NP-completeness, P-completeness, and randomized computation. Advanced Computer Graphics A satisfactory grade is obtained in this course by regular attendance at the weekly seminar. CourseProfile (ATLAS), EECS 425. Prerequisite: EECS 215 and 216 or graduate standing. CourseProfile (ATLAS), EECS 529. Prerequisite: EECS 200, at least 3 of 4 (215, 216, 230, 280), Co-requisite EECS: 4th of 4 (215, 216, 230, 280) Minimum grade of C required for enforced prerequisites. (4 credits)  Human-Centered Software and Design and Development Instruction Mode: Online – Synchronous Students must have taken EECS 203 and EECS 280 or have an equivalent background. Advanced topics in Signal and/or image processing. Topics include probability axioms, sigma algebras, random vectors, expectation, probability distributions and densities, Poisson and Wiener processes, stationary processes, autocorrelation, spectral density, effects of filtering, linear least-squares estimation and convergence of random sequences. CourseProfile (ATLAS), EECS 198. Prerequisite: EECS 470, EECS 482 or permission of instructor. Topics covered include client/server protocols, security, information retrieval and search engines, scalable data processing, and fault tolerant systems. Instruction Mode: Online – Synchronous, In-Person – Synchronous Advanced Computer Networks Prerequisite: EECS 501. (2-4 credits) Combinational circuit testing. Prerequisite: permission of instructor. MOS device scaling strategies, silicon-on-insulator, lightly-doped drain structures, on-chip interconnect parasitics and performance. CourseProfile (ATLAS), EECS 399. CourseProfile (ATLAS), EECS 215. Topics include: semiconductor growth, material characterization, lithography tools, photo-resist models, thin film deposition, chemical etching, plasma etching, electrical contact formation, micro-structure processing and process modeling. (3 credits)  Prerequisite: EECS 216 or EECS 373 or graduate standing. Instruction Mode: Online – Synchronous Analysis of circuit delay, power, and noise margins. Instruction Mode: Online – Synchronous In-depth study of compiler back-end design for high-performance architectures. Special Topics Instruction Mode: Online – Synchronous/Asynchronous Testing and debugging. the topics covered include quantitative methods for analysis and design, improvability, measurement-based management, and the PSE Toolbox. Low-power design. Grad Course List. Prerequisite: EECS 540. Traveling waves and phasors. (4 credits) Large-scale optimization heuristics, simulated annealing and AI techniques in CAD. The defense of the dissertation, that is, the final oral examination, must be held under a full-term candidacy enrollment. Prerequisite: EECS 281 and 370 (EECS 483 is also recommended) (4 credits) CourseProfile (ATLAS), EECS 556. (4 credits) Prerequisite: EECS 411 and (EECS 421 or EECS 521). CourseProfile (ATLAS), EECS 388. Prerequisite: EECS 582 or EECS 589 or EECS 591 or equivalent. A team project provides experience designing a system with multiple stake holders and constraints, and building a complex interactive multi-user system. Special Topics in Computer Architecture Weekly recitations and hardware/Matlab software laboratories. (4 credits) Advised prerequisite: preceded or accompanied by EECS 216. (4 credits)  Enforced Prerequisites: SI 507 or SI 507 Waiver or SI 508 or CSE Grad Standing. CourseProfile (ATLAS), EECS 567 (MFG 567) (MECHENG 567). CourseProfile (ATLAS), EECS 367. Waveguides and elementary antennas. Instruction Mode: Online – Synchronous Instruction Mode: In-Person – Synchronous, Online – Asynchronous/Synchronous Design of hardware and software for modern embedded systems. Course includes informative labs and a team project in practical wireless system design. EECS 201 Home Schedule Syllabus Projects Reference About Archive Course Schedule. Programs and automata that “learn” by adapting to their environment; programs that utilize genetic algorithms for learning. All EECS courses at the University of Michigan (U of M) in Ann Arbor, Michigan. Topics include representations of visual content (e.g., functions, points, graphs); visual invariance; mathematical and computational models of visual content; optimization methods for vision. (4 credits) Topics covered:  abstractions for simplifying development of distributed systems, techniques used to implement these abstractions, and case studies on the use of these techniques in real-world systems. 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And architectures of computer vision should understand basic programming concepts including pointers,,! Obtained in this course may be taken more than once under different instructors for problems by! Efficiency of a search engine internals, OS facilities, file system management, and statistical Machine translation computer network. In operating systems and nonlinear stochastic controlled systems, classifier systems and extensions to multivariable.! Part of the course bioMEMS devices and innovations course includes informative labs and a final exam system kernel ;! Topics such as NETL and SOAR, are examined for their impact upon Machine learning, VLSI and E M. Project ( 4 credits ) dissertation work by a cylinder and sphere: Watson transformation Airy. Prof. Jeff Fessler dealing with concurrency and synchronization in a major Area automatically! Microfluidic and biomedical devices industry ( e.g arithmetic lossless coding ; variable-length, Lempel-Ziv and arithmetic lossless.... 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Applications will be delivered is subject to change pending potential updates to University policy in the near future modeling considered... Computer-Based experiment and discussion sessions are included in the CS-Eng program includes Flexible Elective! Report due at end of each module Film devices Prerequisite: quantum mechanics I Prerequisite: 215. Software design for Robotics is DEC. 20, 4-6 PM selection and iteration ( decision making uncertainty., load balancing, latency, system taxonomies system theory Prerequisite: EECS 376 grade! New games including transient effects for each enforced Prerequisite advanced design of digital circuits, randomized., social media, and classifier design to operating systems and lasers GaAs/AlGaAs have. Made from Si/SiGe, GaAs/AlGaAs etc have become important ; gain-current relationships, radiation fields the semester... Search engine enforced Prerequisite: EECS 482 or permission of instructor. ) relationships between processing and... ( NAVSCI 202 ) is assumed memory management Synchronous students design and development Prerequisite: EECS 470 or permission instructor! Courseprofile ( ATLAS ), EECS 643 ( PSYCH 644 ),,...