New 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 2013-06-14T03:06:44+05:00 MIT OpenCourseWare http://ocw.mit.edu en-US Content 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 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://www.pheedcontent.com/click.phdo?i=e182c093cb7da8200df937fecf4846fd http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-s096-introduction-to-c-and-c-january-iap-2013 Lieber, Tom Murray, Kyle Li, Frank 2013-03-18T16:19:10+05:00 6.S096 en-US C programming C++ programming memory management pointers preprocessor macros object oriented programming debugging MIT OpenCourseWare http://ocw.mit.edu Content 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 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://www.pheedcontent.com/click.phdo?i=6da7218af02543efc33bb762e23601ef http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-003-signals-and-systems-fall-2011 Freeman, Dennis 2013-03-14T10:54:29+05:00 6.003 en-US MIT OpenCourseWare http://ocw.mit.edu Content 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 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://www.pheedcontent.com/click.phdo?i=0e3b2345e1fe040960c92adf570ca76f http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-007-electromagnetic-energy-from-motors-to-lasers-spring-2011 Bulovic, Vladimir Ram, Rajeev Leeb, Steven Lang, Jeffrey H. Gu, Yu 2013-02-22T10:43:41+05:00 6.007 en-US electromagnetics quantum mechanics energy conversion power flow electric motors circuits quantum tunneling optoelectronic devices electromagnetic waves EM waves semiconductors lasers MIT OpenCourseWare http://ocw.mit.edu Content 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 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://www.pheedcontent.com/click.phdo?i=05d195577273beb6c40e83e287216c1c http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-006-introduction-to-algorithms-fall-2011 Demaine, Erik Devadas, Srinivas 2013-01-14T15:18:27+05:00 6.006 en-US algorithms data structures algorithm performance algorithm analysis sorting trees hashing numerics graphs shortest paths dynamic programming Python MIT OpenCourseWare http://ocw.mit.edu Content 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 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://www.pheedcontent.com/click.phdo?i=d89fcdd88923b9827767b7547f199626 http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-253-convex-analysis-and-optimization-spring-2012 Bertsekas, Dimitri 2012-12-14T12:48:55+05:00 6.253 en-US convex analysis convex optimization hyperplanes conjugacy polyhedral convexity geometric duality duality theory subgradients optimality conditions convex optimization algorithms MIT OpenCourseWare http://ocw.mit.edu Content 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 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://www.pheedcontent.com/click.phdo?i=0be6b6e3386847cc122612dade51b92d http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-231-dynamic-programming-and-stochastic-control-fall-2011 Bertsekas, Dimitri 2012-11-07T15:57:00+05:00 6.231 en-US dynamic programming stochastic control algorithms finite-state continuous-time imperfect state information suboptimal control finite horizon infinite horizon discounted problems stochastic shortest path approximate dynamic programming MIT OpenCourseWare http://ocw.mit.edu Content 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 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://www.pheedcontent.com/click.phdo?i=00b72f141b1a2b21e6bb0dfe7c30d54e http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-005-elements-of-software-construction-fall-2011 Miller, Robert 2012-06-22T16:09:10+05:00 6.005 en-US software development specifications invariants state machines test-driven development design patterns object-oriented programming concurrent programming functional programming MIT OpenCourseWare http://ocw.mit.edu Content 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 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://www.pheedcontent.com/click.phdo?i=441fdc9021defa51638810ff82093abf http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-831-user-interface-design-and-implementation-spring-2011 Miller, Robert 2012-06-11T10:38:23+05:00 6.831 6.813 en-US human-computer interaction user interfaces human capabilities design principles prototyping techniques evaluation techniques MIT OpenCourseWare http://ocw.mit.edu Content 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 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://www.pheedcontent.com/click.phdo?i=a6cbf965847e859cc0401332c99ad759 http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-00sc-introduction-to-computer-science-and-programming-spring-2011 Guttag, John 2012-03-02T14:47:24+05:00 6.00SC en-US Python programming algorithms dynamic programming object-oriented programming debugging problem solving recursion iteration search algorithms program efficiency order of growth memoization hashing object classes inheritance Monte Carlo simulation curve fitting optimization clustering queuing networks data sampling MIT OpenCourseWare http://ocw.mit.edu Content 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 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://www.pheedcontent.com/click.phdo?i=3608d0b5e90ec35e79f051a8c50ca82b http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-01sc-introduction-to-electrical-engineering-and-computer-science-i-spring-2011 Kaelbling, Leslie White, Jacob Abelson, Harold Freeman, Dennis Lozano-Pérez, Tomás Chuang, Isaac 2012-02-13T15:10:04+05:00 6.01SC en-US Python programming object-oriented programming state machines signals and systems linear time-invariant LTI poles circuits op-amps Thevenin Norton superposition probability state estimation search algorithms MIT OpenCourseWare http://ocw.mit.edu Content 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 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://www.pheedcontent.com/click.phdo?i=ee2472cf603d577ae2113623b59c60cf http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-241j-dynamic-systems-and-control-spring-2011 Frazzoli, Emilio Dahleh, Munther 2011-12-28T16:31:42+05:00 6.241J 16.338J en-US dynamic systems multiple inputs multiple outputs MIMO feedback control systems linear time-invariant optimal control robust control linear algebra least squares MIT OpenCourseWare http://ocw.mit.edu Content 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 Modern computing platforms provide unprecedented amounts of raw computational power. But significant complexity comes along with this power, to the point that making useful computations exploit even a fraction of the potential of the computing platform is a substantial challenge. Indeed, obtaining good performance requires a comprehensive understanding of all layers of the underlying platform, deep insight into the computation at hand, and the ingenuity and creativity required to obtain an effective mapping of the computation onto the machine. The reward for mastering these sophisticated and challenging topics is the ability to make computations that can process large amount of data orders of magnitude more quickly and efficiently and to obtain results that are unavailable with standard practice. This class is a hands-on, project-based introduction to building scalable and high-performance software systems. Topics include performance analysis, algorithmic techniques for high performance, instruction-level optimizations, cache and memory hierarchy optimization, parallel programming, and building scalable distributed systems. The course also includes design reviews with industry mentors, as described in this MIT News article. http://www.pheedcontent.com/click.phdo?i=2530f274b4f1f36a36631ddfa06be0f2 http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-172-performance-engineering-of-software-systems-fall-2010 Amarasinghe, Saman Leiserson, Charles 2011-12-22T16:54:49+05:00 6.172 en-US performance analysis algorithmic techniques high performance instruction level optimization cache optimization memory optimization parallel programming scalable distributed systems MIT OpenCourseWare http://ocw.mit.edu Content 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 Discrete stochastic processes are essentially probabilistic systems that evolve in time via random changes occurring at discrete fixed or random intervals. This course aims to help students acquire both the mathematical principles and the intuition necessary to create, analyze, and understand insightful models for a broad range of these processes. The range of areas for which discrete stochastic-process models are useful is constantly expanding, and includes many applications in engineering, physics, biology, operations research and finance. http://www.pheedcontent.com/click.phdo?i=bf10df2703d06a3b21b7d1f3ce993cc8 http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-262-discrete-stochastic-processes-spring-2011 Gallager, Robert 2011-11-03T15:28:27+05:00 6.262 en-US probability Poisson processes finite-state Markov chains renewal processes countable-state Markov chains Markov processes countable state spaces random walks large deviations martingales MIT OpenCourseWare http://ocw.mit.edu Content 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 This course provides a challenging introduction to some of the central ideas of theoretical computer science. Beginning in antiquity, the course will progress through finite automata, circuits and decision trees, Turing machines and computability, efficient algorithms and reducibility, the P versus NP problem, NP-completeness, the power of randomness, cryptography and one-way functions, computational learning theory, and quantum computing. It examines the classes of problems that can and cannot be solved by various kinds of machines. It tries to explain the key differences between computational models that affect their power. http://www.pheedcontent.com/click.phdo?i=afa451f2d8d44031fa282ee6d65fb62d http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-045j-automata-computability-and-complexity-spring-2011 Aaronson, Scott 2011-11-02T16:25:19+05:00 6.045J 18.400J en-US finite automata Turing machine halting problem computability computational complexity polynomial time P NP NP complete probabilistic algorithms private-key cryptography public-key cryptography randomness MIT OpenCourseWare http://ocw.mit.edu Content 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 This course is an introductory subject in the field of electric power systems and electrical to mechanical energy conversion. Electric power has become increasingly important as a way of transmitting and transforming energy in industrial, military and transportation uses. Electric power systems are also at the heart of alternative energy systems, including wind and solar electric, geothermal and small scale hydroelectric generation. http://www.pheedcontent.com/click.phdo?i=a37f1724392622adec6418bd55bf9482 http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-061-introduction-to-electric-power-systems-spring-2011 Kirtley, James 2011-09-30T12:20:12+05:00 6.061 6.690 en-US electric power systems energy conversion electrical energy mechanical energy electric transportation alternative energy electric circuits magnetic field devices lumped parameter electromechanics MIT OpenCourseWare http://ocw.mit.edu Content 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 This course introduces students to the basic knowledge representation, problem solving, and learning methods of artificial intelligence. Upon completion of 6.034, students should be able to develop intelligent systems by assembling solutions to concrete computational problems, understand the role of knowledge representation, problem solving, and learning in intelligent-system engineering, and appreciate the role of problem solving, vision, and language in understanding human intelligence from a computational perspective. http://www.pheedcontent.com/click.phdo?i=7cfbfdcb6f827c90930f84e8ca193920 http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-034-artificial-intelligence-fall-2010 Winston, Patrick Henry 2011-06-29T14:33:34+05:00 6.034 en-US artificial intelligence knowledge representation problem solving learning methods intelligent systems basic search optimal search neural nets genetic algorithms support vector machines boosting probabilistic inference MIT OpenCourseWare http://ocw.mit.edu Content 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 This course will provide a gentle, yet intense, introduction to programming using Python for highly motivated students with little or no prior experience in programming. The course will focus on planning and organizing programs, as well as the grammar of the Python programming language. The course is designed to help prepare students for 6.01 Introduction to EECS I. 6.01 assumes some knowledge of Python upon entering; the course material for 6.189 has been specially designed to make sure that concepts important to 6.01 are covered. 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://www.pheedcontent.com/click.phdo?i=6cba19bd5d916bdf42461f2bc022f520 http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-189-a-gentle-introduction-to-programming-using-python-january-iap-2011 Canelake, Sarina 2011-06-24T12:18:34+05:00 6.189 en-US Python conditionals loops defining functions strings lists list comprehensions recursion tuples dictionaries classes inheritance scoping MIT OpenCourseWare http://ocw.mit.edu Content 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 6.301 is a course in analog circuit analysis and design. We cover the tools and methods necessary for the creative design of useful circuits using active devices. The class stresses insight and intuition, applied to the design of transistor circuits and the estimation of their performance. We concentrate on circuits using the bipolar junction transistor, but the techniques that we study can be equally applied to circuits using JFETs, MOSFETs, MESFETs, future exotic devices, or even vacuum tubes. http://www.pheedcontent.com/click.phdo?i=71c5016331a4be8498890b8bf570e974 http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-301-solid-state-circuits-fall-2010 Roberge, James 2011-06-24T11:08:35+05:00 6.301 en-US analog circuits circuit analysis circuit design transistor circuits bipolar junction transistor op amps charge control open circuit time constants MIT OpenCourseWare http://ocw.mit.edu Content 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 This course relies on primary readings from the database community to introduce graduate students to the foundations of database systems, focusing on basics such as the relational algebra and data model, schema normalization, query optimization, and transactions. It is designed for students who have taken 6.033 (or equivalent); no prior database experience is assumed, though students who have taken an undergraduate course in databases are encouraged to attend. http://www.pheedcontent.com/click.phdo?i=b822b13d02c6d90ba8fd84ace21ee262 http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-830-database-systems-fall-2010 Madden, Samuel Morris, Robert Stonebraker, Michael Curino, Carlo 2011-06-24T09:29:18+05:00 6.830 6.814 en-US database systems relational algebra data model query optimization query processing transactions recovery concurrency control distributed transactions parallel databases scientific databases streaming databases MIT OpenCourseWare http://ocw.mit.edu Content 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 This course covers elementary discrete mathematics for computer science and engineering. It emphasizes mathematical definitions and proofs as well as applicable methods. Topics include formal logic notation, proof methods; induction, well-ordering; sets, relations; elementary graph theory; integer congruences; asymptotic notation and growth of functions; permutations and combinations, counting principles; discrete probability. Further selected topics may also be covered, such as recursive definition and structural induction; state machines and invariants; recurrences; generating functions. http://www.pheedcontent.com/click.phdo?i=c23484c70a2fdb19b65bc3bbbc660017 http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-042j-mathematics-for-computer-science-fall-2010 Leighton, Tom Dijk, Marten van 2011-06-23T12:46:03+05:00 6.042J 18.062J en-US formal logic notation proof methods induction sets relations graph theory integer congruences asymptotic notation growth of functions permutations combinations counting discrete probability MIT OpenCourseWare http://ocw.mit.edu Content 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