MIT OpenCourseWare: New Courses in Electrical Engineering and Computer ScienceNew courses in Electrical Engineering and Computer Science from MIT OpenCourseWare, provider of free and open MIT course materials.
http://ocw.mit.edu/courses/electrical-engineering-and-computer-science
2014-04-23T16:47:05+05:00MIT OpenCourseWare http://ocw.mit.eduen-USContent within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm6.837 Computer Graphics (MIT)This course provides introduction to computer graphics algorithms, software and hardware. Topics include: ray tracing, the graphics pipeline, transformations, texture mapping, shadows, sampling, global illumination, splines, animation and color. This course offers 6 Engineering Design Points in MIT's EECS program.
http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-837-computer-graphics-fall-2012
Matusik, WojciechDurand, Frédo2014-04-02T17:10:21+05:006.837en-USanimation and colormodelingtransformationsBezier curves and splinesrepresentation and interpolation of rotationscomputer animationparticle systemscollision detectionray tracing and castingrasterization and shading texture mappinggraphics pipelineglobal illuminationantialiasingsamplingMIT OpenCourseWare http://ocw.mit.eduContent within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm6.685 Electric Machines (MIT)This course teaches the principles and analysis of electromechanical systems. Students will develop analytical techniques for predicting device and system interaction characteristics as well as learn to design major classes of electric machines. Problems used in the course are intended to strengthen understanding of the phenomena and interactions in electromechanics, and include examples from current research.
http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-685-electric-machines-fall-2013
Kirtley Jr., James L.2014-03-07T17:07:03+05:006.685en-USelectricmachinetransformerselectromechanicaltransducersrotatinglinear electric machineslumped parameterdcinductionsynchronousenergy conversionelectromechanicsMechatronicsMIT OpenCourseWare http://ocw.mit.eduContent within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm6.868J The Society of Mind (MIT)This course is an introduction to the theory that tries to explain how minds are made from collections of simpler processes. It treats such aspects of thinking as vision, language, learning, reasoning, memory, consciousness, ideals, emotions, and personality. It incorporates ideas from psychology, artificial intelligence, and computer science to resolve theoretical issues such as wholes vs. parts, structural vs. functional descriptions, declarative vs. procedural representations, symbolic vs. connectionist models, and logical vs. common-sense theories of learning.
http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-868j-the-society-of-mind-fall-2011
Minsky, Marvin2014-03-04T14:05:54+05:006.868Jen-USmarvin minskyartificial intelligencesociety of the mindemotion machinecognitive psychologycognitive theoryphilosophy of the mindMIT OpenCourseWare http://ocw.mit.eduContent within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm6.041SC Probabilistic Systems Analysis and Applied Probability (MIT)This course introduces students to the modeling, quantification, and analysis of uncertainty. The tools of probability theory, and of the related field of statistical inference, are the keys for being able to analyze and make sense of data. These tools underlie important advances in many fields, from the basic sciences to engineering and management.
http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-041sc-probabilistic-systems-analysis-and-applied-probability-fall-2013
Tsitsiklis, John2014-02-26T16:05:07+05:006.041SCen-USprobabilityprobability modelsbayes rulediscrete random variablescontinuous random variablesbernoulli processpoisson processmarkov chainscentral limit theoremstatistical inferenceMIT OpenCourseWare http://ocw.mit.eduContent within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm6.851 Advanced Data Structures (MIT)Data structures play a central role in modern computer science. You interact with data structures even more often than with algorithms (think Google, your mail server, and even your network routers). In addition, data structures are essential building blocks in obtaining efficient algorithms. This course covers major results and current directions of research in data structure. Acknowledgments Thanks to videographers Martin Demaine and Justin Zhang.
http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-851-advanced-data-structures-spring-2012
Demaine, Erik2013-12-18T04:40:36+05:006.851en-USdatastructuresdata structurescomputerscomputer sciencestringsdynamic graphsintegershashhashinghashishhashtaghash taghash taggermemorymemory heirarchybinary treebinary searchbinary search treetime travelback to the futureforward to the pastdatadatabasetabledatabase tablecachecachingmad cache moneylogarithmic timeeurythmic timeoperationssearchheapsMIT OpenCourseWare http://ocw.mit.eduContent within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm6.170 Software Studio (MIT)This course on software engineering covers design and implementation of medium-scale software systems, using web applications as a platform. In the course, students learn the fundamentals of structuring a web application and writing modular code, with an emphasis on conceptual design to achieve clarity, simplicity, and modularity. Topics also include functional programming, relational databases, and security.
http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-170-software-studio-spring-2013
Jackson, Daniel2013-11-22T17:06:57+05:006.170en-USsoftwarewebweb applicationprogrammingcodeRuby on RailsRESTrelational dataAjaxJavaScriptHTMLCSSobjectobject modelingsecuritydevelopment processdependencyMIT OpenCourseWare http://ocw.mit.eduContent within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm6.S079 Nanomaker (MIT)This course links clean energy sources and storage technology to energy consumption case studies to give students a concept of the full circle of production and consumption. Specifically, photovoltaic, organic photovoltaic, piezoelectricity and thermoelectricity sources are applied to electrophoresis, lab on a chip, and paper microfluidic applications–relevant analytical techniques in biology and chemistry. Hands-on experimentation with everyday materials and equipment help connect the theory with the implementation. Complementary laboratories fabricating LEDs, organic LEDs and spectrometers introduce the diagnostic tools used to characterize energy efficiency.This course is one of many OCW Energy Courses, and it is an elective subject in MIT’s undergraduate Energy Studies Minor. This Institute-wide program complements the deep expertise obtained in any major with a broad understanding of the interlinked realms of science, technology, and social sciences as they relate to energy and associated environmental challenges.
http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-s079-nanomaker-spring-2013
Lo, KateySummers, JosephBulovic, VladimirRam, Rajeev2013-11-15T13:38:45+05:006.S079en-USclean energyenergy sourcesenergy storageenergy consumptionphotovoltaicpiezoelectricthermoelectricLEDlight emitting diodeorganic LEDanalytical biologyanalytical chemistrymicrofluidicsspectrometerenergy efficiencyMIT OpenCourseWare http://ocw.mit.eduContent within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm6.046J Design and Analysis of Algorithms (MIT)Techniques for the design and analysis of efficient algorithms, emphasizing methods useful in practice. Topics include sorting; search trees, heaps, and hashing; divide-and-conquer; dynamic programming; greedy algorithms; amortized analysis; graph algorithms; and shortest paths. Advanced topics may include network flow, computational geometry, number-theoretic algorithms, polynomial and matrix calculations, caching, and parallel computing.
http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-046j-design-and-analysis-of-algorithms-spring-2012
Moshkovitz, DanaTidor, Bruce2013-08-20T14:33:44+05:006.046J18.410Jen-USsortingsearch treesheapshashingdivide and conquerdynamic programminggreedy algorithmsamortized analysisgraph algorithmsshortest pathsMIT OpenCourseWare http://ocw.mit.eduContent within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm6.02 Introduction to EECS II: Digital Communication Systems (MIT)An introduction to several fundamental ideas in electrical engineering and computer science, using digital communication systems as the vehicle. The three parts of the course—bits, signals, and packets—cover three corresponding layers of abstraction that form the basis of communication systems like the Internet. The course teaches ideas that are useful in other parts of EECS: abstraction, probabilistic analysis, superposition, time and frequency-domain representations, system design principles and trade-offs, and centralized and distributed algorithms. The course emphasizes connections between theoretical concepts and practice using programming tasks and some experiments with real-world communication channels.
http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-02-introduction-to-eecs-ii-digital-communication-systems-fall-2012
Balakrishnan, HariVerghese, George2013-07-10T14:34:41+05:006.02en-USdigital communicationcommunication systemsinformationentropycompressionerror correctionFourier analysisfilteringsignalsmedia access protocolsnetworkspacketsdata transportinternetMIT OpenCourseWare http://ocw.mit.eduContent within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm6.S096 Introduction to C and C++ (MIT)This course provides a fast-paced introduction to the C and C++ programming languages. You will learn the required background knowledge, including memory management, pointers, preprocessor macros, object-oriented programming, and how to find bugs when you inevitably use any of those incorrectly. There will be daily assignments and a small-scale individual project. This course is offered during the Independent Activities Period (IAP), which is a special 4-week term at MIT that runs from the first week of January until the end of the month.
http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-s096-introduction-to-c-and-c-january-iap-2013
Lieber, TomMurray, KyleLi, Frank2013-03-18T16:19:10+05:006.S096en-USC programmingC++ programmingmemory managementpointerspreprocessor macrosobject oriented programmingdebuggingMIT OpenCourseWare http://ocw.mit.eduContent within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm6.003 Signals and Systems (MIT)6.003 covers the fundamentals of signal and system analysis, focusing on representations of discrete-time and continuous-time signals (singularity functions, complex exponentials and geometrics, Fourier representations, Laplace and Z transforms, sampling) and representations of linear, time-invariant systems (difference and differential equations, block diagrams, system functions, poles and zeros, convolution, impulse and step responses, frequency responses). Applications are drawn broadly from engineering and physics, including feedback and control, communications, and signal processing.
http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-003-signals-and-systems-fall-2011
Freeman, Dennis2013-03-14T10:54:29+05:006.003en-USMIT OpenCourseWare http://ocw.mit.eduContent within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm6.007 Electromagnetic Energy: From Motors to Lasers (MIT)This course discusses applications of electromagnetic and equivalent quantum mechanical principles to classical and modern devices. It covers energy conversion and power flow in both macroscopic and quantum-scale electrical and electromechanical systems, including electric motors and generators, electric circuit elements, quantum tunneling structures and instruments. It studies photons as waves and particles and their interaction with matter in optoelectronic devices, including solar cells, displays, and lasers. The instructors would like to thank Scott Bradley, David Friend, Ta-Ming Shih, and Yasuhiro Shirasaki for helping to develop the course, and Kyle Hounsell, Ethan Koether, and Dmitri Megretski for their work preparing the lecture notes for OCW publication.
http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-007-electromagnetic-energy-from-motors-to-lasers-spring-2011
Bulovic, VladimirRam, RajeevLeeb, StevenLang, Jeffrey H.Gu, Yu2013-02-22T10:43:41+05:006.007en-USelectromagneticsquantum mechanicsenergy conversionpower flowelectric motorscircuitsquantum tunnelingoptoelectronic deviceselectromagnetic wavesEM wavessemiconductorslasersMIT OpenCourseWare http://ocw.mit.eduContent within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm6.006 Introduction to Algorithms (MIT)This course provides an introduction to mathematical modeling of computational problems. It covers the common algorithms, algorithmic paradigms, and data structures used to solve these problems. The course emphasizes the relationship between algorithms and programming, and introduces basic performance measures and analysis techniques for these problems.
http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-006-introduction-to-algorithms-fall-2011
Demaine, ErikDevadas, Srinivas2013-01-14T15:18:27+05:006.006en-USalgorithmsdata structuresalgorithm performancealgorithm analysissortingtreeshashingnumericsgraphsshortest pathsdynamic programmingPythonMIT OpenCourseWare http://ocw.mit.eduContent within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm6.253 Convex Analysis and Optimization (MIT)This course will focus on fundamental subjects in convexity, duality, and convex optimization algorithms. The aim is to develop the core analytical and algorithmic issues of continuous optimization, duality, and saddle point theory using a handful of unifying principles that can be easily visualized and readily understood.
http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-253-convex-analysis-and-optimization-spring-2012
Bertsekas, Dimitri2012-12-14T12:48:55+05:006.253en-USconvex analysisconvex optimizationhyperplanesconjugacypolyhedral convexitygeometric dualityduality theorysubgradientsoptimality conditionsconvex optimization algorithmsMIT OpenCourseWare http://ocw.mit.eduContent within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm6.231 Dynamic Programming and Stochastic Control (MIT)The course covers the basic models and solution techniques for problems of sequential decision making under uncertainty (stochastic control). We will consider optimal control of a dynamical system over both a finite and an infinite number of stages. This includes systems with finite or infinite state spaces, as well as perfectly or imperfectly observed systems. We will also discuss approximation methods for problems involving large state spaces. Applications of dynamic programming in a variety of fields will be covered in recitations.
http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-231-dynamic-programming-and-stochastic-control-fall-2011
Bertsekas, Dimitri2012-11-07T15:57:00+05:006.231en-USdynamic programmingstochastic controlalgorithmsfinite-statecontinuous-timeimperfect state informationsuboptimal controlfinite horizoninfinite horizondiscounted problemsstochastic shortest pathapproximate dynamic programmingMIT OpenCourseWare http://ocw.mit.eduContent within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm6.005 Elements of Software Construction (MIT)This course introduces fundamental principles and techniques of software development. Students learn how to write software that is safe from bugs, easy to understand, and ready for change. Topics include specifications and invariants; testing, test-case generation, and coverage; state machines; abstract data types and representation independence; design patterns for object-oriented programming; concurrent programming, including message passing and shared concurrency, and defending against races and deadlock; and functional programming with immutable data and higher-order functions. The course includes weekly programming exercises and two substantial group projects.
http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-005-elements-of-software-construction-fall-2011
Miller, Robert2012-06-22T16:09:10+05:006.005en-USsoftware developmentspecificationsinvariantsstate machinestest-driven developmentdesign patternsobject-oriented programmingconcurrent programmingfunctional programmingMIT OpenCourseWare http://ocw.mit.eduContent within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm6.831 User Interface Design and Implementation (MIT)6.831/6.813 examines human-computer interaction in the context of graphical user interfaces. The course covers human capabilities, design principles, prototyping techniques, evaluation techniques, and the implementation of graphical user interfaces. Deliverables include short programming assignments and a semester-long group project. Students taking the graduate version also have readings from current literature and additional assignments.
http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-831-user-interface-design-and-implementation-spring-2011
Miller, Robert2012-06-11T10:38:23+05:006.8316.813en-UShuman-computer interactionuser interfaceshuman capabilitiesdesign principlesprototyping techniquesevaluation techniquesMIT OpenCourseWare http://ocw.mit.eduContent within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm6.00SC Introduction to Computer Science and Programming (MIT)This subject is aimed at students with little or no programming experience. It aims to provide students with an understanding of the role computation can play in solving problems. It also aims to help students, regardless of their major, to feel justifiably confident of their ability to write small programs that allow them to accomplish useful goals. The class will use the Python programming language.
http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-00sc-introduction-to-computer-science-and-programming-spring-2011
Guttag, John2012-03-02T14:47:24+05:006.00SCen-USPython programmingalgorithmsdynamic programmingobject-oriented programmingdebuggingproblem solvingrecursioniterationsearch algorithmsprogram efficiencyorder of growthmemoizationhashingobject classesinheritanceMonte Carlo simulationcurve fittingoptimizationclusteringqueuing networksdata samplingMIT OpenCourseWare http://ocw.mit.eduContent within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm6.01SC Introduction to Electrical Engineering and Computer Science I (MIT)This course provides an integrated introduction to electrical engineering and computer science, taught using substantial laboratory experiments with mobile robots. Our primary goal is for you to learn to appreciate and use the fundamental design principles of modularity and abstraction in a variety of contexts from electrical engineering and computer science. Our second goal is to show you that making mathematical models of real systems can help in the design and analysis of those systems. Finally, we have the more typical goals of teaching exciting and important basic material from electrical engineering and computer science, including modern software engineering, linear systems analysis, electronic circuits, and decision-making.
http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-01sc-introduction-to-electrical-engineering-and-computer-science-i-spring-2011
Kaelbling, LeslieWhite, JacobAbelson, HaroldFreeman, DennisLozano-Pérez, TomásChuang, Isaac2012-02-13T15:10:04+05:006.01SCen-USPython programmingobject-oriented programmingstate machinessignals and systemslinear time-invariantLTIpolescircuitsop-ampsTheveninNortonsuperpositionprobabilitystate estimationsearch algorithmsMIT OpenCourseWare http://ocw.mit.eduContent within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm6.241J Dynamic Systems and Control (MIT)The course addresses dynamic systems, i.e., systems that evolve with time. Typically these systems have inputs and outputs; it is of interest to understand how the input affects the output (or, vice-versa, what inputs should be given to generate a desired output). In particular, we will concentrate on systems that can be modeled by Ordinary Differential Equations (ODEs), and that satisfy certain linearity and time-invariance conditions. We will analyze the response of these systems to inputs and initial conditions. It is of particular interest to analyze systems obtained as interconnections (e.g., feedback) of two or more other systems. We will learn how to design (control) systems that ensure desirable properties (e.g., stability, performance) of the interconnection with a given dynamic system.
http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-241j-dynamic-systems-and-control-spring-2011
Frazzoli, EmilioDahleh, Munther2011-12-28T16:31:42+05:006.241J16.338Jen-USdynamic systemsmultiple inputsmultiple outputsMIMOfeedbackcontrol systemslinear time-invariantoptimal controlrobust controllinear algebraleast squaresMIT OpenCourseWare http://ocw.mit.eduContent within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm