Analysis and Programming Degrees

...1 hour / session Labs: 3 sessions / week for 3 weeks, 2 hours / session Welcome to 6.189! This course will provide a comprehensive, fast-paced introduction to Python...

...platform as they learn how to design and implement exciting applications for multicore architectures. At the end of the course, students will have an understanding...

...as well as perfectly or imperfectly observed systems. We will also discuss approximation methods for problems involving large state spaces. Applications... Learn about: Decision Making...

...H-infinity controller design; Mu-synthesis; model and compensator simplification; and nonlinear effects. The assignments for the course comprise of computer-aided (MATLAB®)... 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...

...Lectures: 2 sessions / week, 1.5 hours / session This course will focus on fundamental subjects in convexity, duality, and convex optimization algorithms...

...pricing and investment decisions in the Internet), and social models (including social and economic networks). The course emphasizes theoretical foundations... Learn about: Communication Training...

...optimality conditions for nonlinear optimization, interior point methods for convex optimization, Newton's method, heuristic methods, and dynamic programming... Learn about: Network Training...

...single and multi-server queues, multi-class queueing networks, fluid models, adversarial queueing networks, heavy-traffic theory and diffusion approximations...

...Everything needs feedback. You will never design an electronic or an electromechanical system that does not include a feedback loop, either explicitly or implicitly...

...1.5 hours / session Most of the professional subjects you have taken at MIT effectively coach you in methods for solving relatively well-defined problems...

...high-performance dynamic programming language for technical computing. Lectures: 2 sessions / week, 1.5 hours / session 18.06 Linear Algebra or 18.701 Algebra...

...OCW does not provide access to this environment. A list of topics covered in the course is available in the calendar. Lectures: 2 sessions /... Learn about: Signal processing...

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

...programming skills experientially. The competition culminates in a live Battlecode tournament. Optional Lectures: 1 session / day, 1 hour / session... Learn about: Artificial Intelligence, Team Training...

...Students meet in teams. 6 General Credits To receive 6 units of general elective credit, your must successfully submit a Robocraft player... Learn about: Team Training...

...2 sessions / week, 1 hour / session Recitations: 2 sessions / week, 1 hour / session Tutorials: 1 session / week, 1 hour / session Welcome to 6.041/6...

...and requires extensive use of MAGIC for circuit layout, and HSPICE and IRSIM for simulations. Rabaey, Jan, Anantha Chandrakasan, and Bora Nikolic...

...estimators and the Cramer-Rao bounds; representations for stochastic processes, shaping and whitening filters, and Karhunen-Loeve expansions... Learn about: Signal processing...