IT, Computing, Telecommunications Degrees in the USA

...Applications of dynamic programming in a variety of fields will be covered in recitations. We will place increased emphasis on approximations... Learn about: Decision Making...

...Alexandre Megretski Homework assignments are usually posted on the Web on Wednesdays evenings. Homework papers are to be submitted during the next Wednesday... Learn about: Computer Aided Design...

...the simplex method, sensitivity analysis, robust optimization, large scale optimization network flows, solving problems with an exponential number of constraints... Learn about: Network Training...

...and semi-definite programming. Algorithmic methods used in the class include steepest descent, Newton's method, conditional gradient and subgradient optimization...

...Convex Optimization. Cambridge University Press, 2004. ISBN: 9780521833783. [Preview with Google Books] 6.079 Introduction to Convex Optimization follows this textbook...

...when preparing your homework solutions. However, at the end, you must write up solutions on your own. Duplicating a solution that someone else has written... Learn about: Communication Training...

...Find materials for this course in the pages linked along the left. MIT OpenCourseWare is a free & open publication of material from thousands of MIT courses... Learn about: Network Training...

...heavy-traffic theory and diffusion approximations. The course will cover state of the art results which lead to research opportunities. Bi-weekly problem...

...frequency-domain design, compensation techniques, application to a wide variety of physical systems, internal and external compensation of operational amplifiers...

...An infinity of adequate solutions exist to all realistic design problems; the more talented engineers select from the better of the possible solutions...

...This is an advanced interdisciplinary introduction to applied parallel computing on modern supercomputers. It has a hands-on emphasis on understanding...

...6.341 will assume that you have previously seen and have fluency with the following material in the 6.341 text: The first problem set provides a basis... Learn about: Signal processing...

...systems including pattern classification, search algorithms, stochastic modelling, and language modelling techniques. Part III compares and contrasts...

...Teams must have one to four people, but can be a mix of MIT and non-MIT students. Experience in programming definitely helps in the competition... Learn about: Artificial Intelligence, Team Training...

..."substantial effort". The 6.370 chairmen will make judgement calls on what constitutes "substantial", but basically your player must do something other... Learn about: Team Training...

...This fundamental subject is concerned with the nature, formulation, and analysis of probabilistic situations. No previous experience with probability is assumed...

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...enormous range of algorithms used in diverse applications. At the same time, everyone contemplating taking 6.432 should understand that it is an intense... Learn about: Signal processing...

...1.5 hours / session Recitations: 1 session / week, 1 hour / session Ljung, Lennart. System Identification: A Theory for the User. 2nd ed. Upper Saddle River...

...Learn more at Get Started with MIT OpenCourseWare...