What Algorithms and Complexity Theory Students Learn
Research topics, specializations, subject areas and concepts studied in Algorithms and Complexity Theory programs from universities in Canada..
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Studying Algorithms and Complexity Theory in Canada | |
Students learn the theoretical aspects of computing science and the application of this theory to modern industrial uses. In order to do this, they learn various problem-solving techniques and algorithms, analytical thought, and first order logic. They also learn to understand executional patterns and data structures and what effect they have on the program's finish time (eg. to avoid writing slow code). Many studies are very mathematically oriented. Students learn to understand fundamental algorithm design and use analysis techniques to estimate program efficiency. Specific types of algorithms studied include divide-and-conquer, greedy algorithms, and dynamic programming. Students also learn the limits of algorithm design, NP-completeness, and heuristic algorithms.
Students also learn about computational complexity theory, such as the classification of problems according to the computational resources required for their solution. Other topics include time and space complexity, tractable and intractable problems, computation using randomness, and parallel computation.
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Study and Work in Algorithms and Complexity Theory in Canada
Study Algorithms and Complexity Theory in Canada
What is Algorithms and Complexity Theory? Discover similiar and related programs and universities in Canada offering Algorithms and Complexity Theory degrees.
Algorithms and Complexity Theory Admission Requirements
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Research in Algorithms and Complexity Theory
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