(Spring 2016), Representation and Modeling for Image Analysis Preference to juniors and seniors. Enrollment limited. Normal registration is for 12 units. Discusses the appropriate times and reasons to use particular models to deliver engineering success. Investigates digital systems with a focus on FPGAs. (Fall 2005), Compound Semiconductor Devices Prereq: 6.002 U (Fall, Spring)4-0-8 units. Students taking graduate version complete additional assignments. Acad Year 2022-2023: Not offered3-0-9 units, Same subject as 15.032[J], IDS.505[J] For international students who begin the MEng program in the same summer as the proposed experience, internship may not begin earlier than the first day of the Summer Session. Lecture and readings from original research papers. Subject meets with 2.180[J], 6.027[J]Prereq: Biology (GIR), 18.03, or permission of instructor G (Spring)3-0-9 units, Same subject as 2.795[J], 10.539[J], 20.430[J]Prereq: Permission of instructor G (Fall)3-0-9 units, Same subject as 20.305[J] Programming experience with C/C++ required. Students apply concepts introduced in lectures and online assignments to design labs that include discussion-based checkoffs. Offered under: 2.723A, 6.902A, 16.662APrereq: None U (Fall, Spring; first half of term)2-0-1 units. Connections and applications to computational complexity, computational learning theory, cryptography and combinatorics. (Spring 2003), Analysis and Design of Digital Integrated Circuits Use OCW to guide your own life-long learning, or to teach others. Students define their specialization by selecting three to four header subjects, two advanced undergraduate subjects, and one to two EECS elective subjects from an extensive set of possibilities. Basic electric machines introduced include DC, induction, and permanent magnet motors, with drive considerations. (Fall 2006), Principles of Digital Communication II Optical waveguide and photonic devices. Introduces interactive computer theorem proving with the Coq proof assistant, which is used for all assignments, providing immediate feedback on soundness of logical arguments. Engineering School-Wide Elective Subject. Provides a set of basic tools (Objective-C and Cocos2D) and exposure to real-world issues in game design. Covers means for decoupling goals from strategy, mechanisms for implementing additive data-directed invocation, work with partially-specified entities, and how to manage multiple viewpoints. Acad Year 2022-2023: Not offered3-0-9 units. Exposure to CMOS process integration concepts, and impacts of processing on device characteristics. Hours arranged with research supervisor. Provides background and insight to understand current network literature and to perform research on networks with the aid of network design projects. Subject meets with 6.800Prereq: (6.0001 and 6.036) or permission of instructor G (Fall)3-2-7 units. Topics include exponential families, order statistics, sufficient statistics, estimation theory, hypothesis testing, measures of performance, notions of optimality, analysis of variance (ANOVA), simple linear regression, and selected topics. Recipients of a Master of Engineering degree normally receive a Bachelor of Science degree simultaneously. Introduces the fundamental algorithmic approaches for creating robot systems that can autonomously manipulate physical objects in open-world environments such as homes and warehouses. Includes lectures and laboratory sessions on processing techniques: wet and dry etching, chemical and physical deposition, lithography, thermal processes, packaging, and device and materials characterization. Build autonomous poker players and aquire the knowledge of the game of poker. (Spring 2017), Computation Structures one algorithms-intensive subject at either the basic or advanced level. Finite-state Markov chains. Linear networks involving independent and dependent sources, resistors, capacitors and inductors. Not offered regularly; consult departmentUnits arrangedCan be repeated for credit. Prereq: None U (IAP) Enrollment may be limited. The department offers a Minor in Computer Science. (Spring 2005), Cryptography and Cryptanalysis Subject meets with 6.802[J], 20.390[J], 20.490Prereq: Biology (GIR) and (18.600 or 6.041) G (Spring)3-0-9 units, Same subject as 18.425[J]Prereq: 6.046[J] G (Fall)3-0-9 units. The Sciences of the Artificial distills the essence of Simon's thought accessibly and coherently. This reissue of the third edition makes a pioneering work available to a new audience. Kullback-Leibler distance and information geometry. Geometric optimization. Not offered regularly; consult department3-6-3 units. Exposes students to the models and methods of engineering leadership within the contexts of conceiving, designing, implementing and operating products, processes and systems. (Spring 2005), Algorithmic Lower Bounds: Fun with Hardness Proofs Considers what separates human intelligence from that of other animals. Digital signal processing theories used for digital image processing, including one-dimensional and two-dimensional convolution, Fourier transform, discrete Fourier transform, and discrete cosine transform. Before enrolling, students must have an employment offer from a company or organization and must find an EECS supervisor. Labs in a modern Hardware Design Language (HDL) illustrate various aspects of microprocessor design, culminating in a term project in which students present a multicore design running on an FPGA board. Prereq: Permission of instructor U (Fall, IAP, Spring) Same subject as 2.791[J], 9.21[J], 20.370[J] Noise shaping. Students with research projects will be encouraged to share their experiences and project-specific questions. Special focus on results of asymptotic or algorithmic significance. Lab component consists of software design, construction, and implementation of design. (Students who have been undergraduates in Electrical Engineering and Computer Science at MIT and who seek opportunities for further study must complete the Master of Engineering rather than the Master of Science degree program.) Topics covered include techniques for leading the creative process in teams, the ethics of engineering systems, methods for articulating designs with group collaboration, identifying and reconciling paradoxes of engineering designs, and communicating solution concepts with impact. (Spring 2015), Mathematics for Computer Science Learn-by-design introduction to modeling and control of discrete- and continuous-time systems, from classical analytical techniques to modern computational strategies. Applications include compilers, computer-algebra systems, deductive systems, and some artificial intelligence applications. N. Gershenfeld, J. DiFrancesco, J. Lavallee, G. Darcey, Subject meets with 6.905Prereq: 6.034 or permission of instructor G (Spring)3-0-9 units, Same subject as 8.351[J], 12.620[J]Prereq: Physics I (GIR), 18.03, and permission of instructor Acad Year 2021-2022: Not offered The Technology and Policy Program (TPP) curriculum provides a solid grounding in technology and policy by combining advanced subjects in the student's chosen technical field with courses in economics, politics, quantitative methods, and social science. Enrollment limited. Competition culminates in a live BattleCode tournament. Same subject as 4.140[J], MAS.863[J]Prereq: Permission of instructor G (Fall)3-9-6 units. Topics presented in three modules - bits, signals, and packets - spanning the multiple layers of a communication system. (Spring 2008), The Structure of Engineering Revolutions Belief propagation, decision-making, classification, estimation, and prediction. (January IAP 2006), Introduction to Copyright Law Acad Year 2022-2023: G (Fall)3-0-9 units, Same subject as 2.097[J], 16.920[J]Prereq: 18.03 or 18.06 G (Fall)3-0-9 units. A text book designed to give the engineer a reasonably complete coverage of the mathematical topics needed specifically or collaterally in the analysis or synthesis of electrical networks. Substantial readings and a term project, where students build a program that illustrates one or more of the themes of the course. (Fall 2005), The Lexicon and Its Features Subject meets with 6.830Prereq: (6.033 and (6.006 or 6.046[J])) or permission of instructor U (Spring)3-0-9 units. In teams, students create a plan for a project of their choice in one of several areas, including: aircraft modification, factory automation, flood prevention engineering, solar farm engineering, small-business digital transformation/modernization, and disaster response, among others. On-chip passive component design of inductors, capacitors, and antennas. Prereq: 6.431 and 18.06 G (Spring)3-0-9 units. Develops analytical skills to lead a successful technology implementation with an integrated approach that combines technical, economical and social perspectives. Introduces basic electrical engineering concepts, components, and laboratory techniques. Prereq: 6.241[J] or 16.31 G (Fall) Same subject as MAS.453[J]Prereq: 6.033 or permission of instructor U (Spring)3-0-9 units. Explores biomedical signals generated from electrocardiograms, glucose detectors or ultrasound images, and magnetic resonance images. (Spring 2003), Applied Superconductivity Lectures cover version control, HTML, CSS, and JavaScript. The joint bachelor’s program in 6-14 is designed to equip students with a foundational knowledge of economic analysis, computing, optimization, and data science, as well as hands-on experience with empirical analysis of economic data. Focuses on modeling with machine learning methods with an eye towards applications in engineering and sciences. This page lists OCW courses from just one of over 30 MIT departments. (Spring 2007), Introduction to Electronics, Signals, and Measurement Prereq: Permission of instructor U (Spring)Units arrangedCan be repeated for credit. With an additional year of study and research beyond the master's level, a student in the doctoral or predoctoral program can complete the requirements for the degree of Electrical Engineer or Engineer in Computer Science. Same subject as 5.00[J], 10.579[J], 22.813[J]Prereq: None G (Fall; first half of term) Prepares students for practical use and development of computational engineering in their own research and future work. Internal stability of interconnected systems, feedback compensators, state feedback, optimal regulation, observers, and observer-based compensators. J. H. Lang, T. Palacios, D. J. Perreault, J. Voldman, Prereq: 6.0001 and 18.03 U (Fall, Spring)6-0-6 units. Limited to 24. Laboratory subjects, independent projects, and research provide engagement with principles and techniques of analysis, design, and experimentation in a variety of fields. (Fall 2005), Modern Optics Project Laboratory While in residence at MIT, students follow a program similar to that of other students in their home department. Media and News. Offered under: 2.723B, 6.902B, 16.662BPrereq: 6.902A U (Fall, Spring; second half of term)2-0-1 units. Mathematical definitions of information measures, convexity, continuity, and variational properties. (Fall 2009), Advanced Algorithms Topics include geometric and semantic perception, trajectory and task-level planning, learning, kinematics, dynamics, and control. Class projects include patent drafting, patent searching, and patentability opinions, and courtroom presentation. (Spring 2006), Introductory Digital Systems Laboratory (Spring 2006), Computer System Engineering Value and policy iteration. Predecessor problem; van Emde Boas priority queues; y-fast trees; fusion trees. An integrated introduction to electrical engineering and computer science, taught using substantial laboratory experiments with mobile robots. Subject meets with 6.320Prereq: Physics II (GIR) and (2.087 or 18.03) U (Fall)4-4-4 units. All applicants for any of these advanced programs will be evaluated in terms of their potential for successful completion of the department's doctoral program. Probability spaces and measures. Computational case studies and projects drawn from applications in finance, sports, engineering, and machine learning life sciences. Prereq: 6.046[J] Acad Year 2021-2022: Not offered Open to advanced students from all areas of EECS. Same subject as IDS.012[J] Parametric signal modeling, linear prediction, and lattice filters. Offered under: 1.082, 2.900, 6.904, 10.01, 16.676, 22.014 Develops intuition of how transistors operate. Graduate study in the department moves students toward mastery of areas of individual interest, through coursework and significant research, often defined in interdisciplinary areas that take advantage of the tremendous range of faculty expertise in the department and, more broadly, across MIT. Recommended prerequisites: 6.006 and 18.06. Fundamentals of digital signal processing with emphasis on problems in biomedical research and clinical medicine. Provides academic credit for graduate students in the second half of their 6-A MEng industry internship. Advanced topics in computer vision with a focus on the use of machine learning techniques and applications in graphics and human-computer interface. A. I. Akinwande, J. Kong, T. Palacios, M. Shulaker, Prereq: Calculus II (GIR) and Physics II (GIR) U (Spring)3-5-4 units. Students engage in problem solving, using Mathematica and MATLAB software extensively to help visualize processing in the time frequency domains. Introduction to computer graphics algorithms, software and hardware. (Fall 2008), Biomedical Devices Design Laboratory (Spring 2009), Machine Learning for Healthcare We don't offer credit or certification for using OCW. Fast-paced introduction to the C and C++ programming languages. Introduces principles, algorithms, and applications of machine learning from the point of view of modeling and prediction; formulation of learning problems; representation, over-fitting, generalization; classification, regression, reinforcement learning; and methods such as linear classifiers, feed-forward, convolutional, and recurrent networks. Image restoration. Electronic scores send to: MIT Graduate Admissions. Research Directions in Computer Science celebrates the twenty-fifth anniversary of the founding of MIT's Project MAC. Develops algebraic and numerical approaches of general applicability, with a view towards methods that simultaneously incorporate both elements, stressing convexity-based ideas, complexity results, and efficient implementations. Individual laboratory assignments accumulate in the construction of a minimal operating system (for an x86-based personal computer) that implements the basic operating system abstractions and a shell. Hypothesis testing and parameter estimation, sufficient statistics; exponential families. Students develop their own models and simulators for self-proposed applications, with an emphasis on creativity, teamwork, and communication. (Fall 2020), Introduction to Computational Thinking with Julia, with Applications to Modeling the COVID-19 Pandemic Contact-aware robot design. Includes problem sets, laboratory exercises, and opened-ended term project. Students engage in extensive written communications exercises. The CSE SM program trains students in the formulation, analysis, implementation, and application of computational approaches via a common core, which serves all science and engineering disciplines, and an elective component which focuses on particular disciplinary applications. (Spring 2003), Advanced Electromagnetism Emphasis on the fundamental cryptographic primitives of public-key encryption, digital signatures, pseudo-random number generation, and basic protocols and their computational complexity requirements. Topics include polarization properties of light; reflection and refraction; coherence and interference; Fraunhofer and Fresnel diffraction; holography; Fourier optics; coherent and incoherent imaging and signal processing systems; optical properties of materials; lasers and LEDs; electro-optic and acousto-optic light modulators; photorefractive and liquid-crystal light modulation; display technologies; optical waveguides and fiber-optic communication systems; photodetectors.
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