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Welcome to the self-paced course, Algorithms: Design and Analysis, Part 2! Algorithms are the heart of computer science, and the subject has countless practical applications as well as intellectual depth. This course is an introduction to algorithms for students with at least some programming experience.
greedy algorithms (programming, minimum spanning trees, clustering, Huffman codes) dynamic programming (backpacking, sequence alignment of optimal search trees, shortest paths) NP completeness and what it means for algorithm designer analysis of heuristics local search Minimize what you will learn
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Stanford University
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