Numerical methods are algorithms for solving practical problems in applied mathematics. They are used extensively in many areas of science, engineering and business. They are crucial to computational finance and portfolio management, video games and graphics, robotics and bioinformatics, data mining and machine learning, and many other areas. In fact, many contemporary problems would be impossible to solve without numerical methods. These problems include predicting climate change, designing modern aircraft, producing special effects in movies, finding hidden oil reserves, simulating car crashes, computing the trajectory of spacecraft, estimating the future value of stocks, optimizing the price of airline tickets, simulating the biological activity of living cells, and many more. Numerical methods are run on computers of all sizes, from laptops to workstations to supercomputers. In fact, the need to apply numerical methods to complex problems is the main reason supercomputers were developed.
Unlike some previous years, this year's course will place less emphasis on theory and proofs, and more emphasis on practical problems and programming. As a fringe benefit, you'll find out what all that math you learned is actually used for!
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Matlab:
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Octave:
Plagiarism and Cheating: