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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 learners with at least a little programming experience. The course is rigorous but emphasizes the big picture and conceptual understanding over low-level implementation and mathematical details. After completing this course, you will be well-positioned to ace your technical interviews and speak fluently about algorithms with other programmers and computer scientists.
Specific topics include: "Big-oh" notation, sorting and searching, divide and conquer (master method, integer and matrix multiplication, closest pair), randomized algorithms (QuickSort, contraction algorithm for min cuts), data structures (heaps, balanced search trees, hash tables, bloom filters), graph primitives (applications of BFS and DFS, connectivity, shortest paths).
About the instructor: Tim Roughgarden has been a professor in the Computer Science Department at Stanford University since 2004. He has taught and published extensively on the subject of algorithms and their applications.
Note: this course is closing on October 10th, 2016, and relaunching as part of a specialization: https://www.coursera.org/specializations/algorithms
Introduction; "big-oh" notation and asymptotic analysis; divide-and-conquer basics.
The master method for analyzing divide and conquer algorithms; the QuickSort algorithm and its analysis; probability review.
Linear-time selection; graphs, cuts, and the contraction algorithm.
Breadth-first and depth-first search; computing strong components; applications.
Dijkstra's shortest-path algorithms; heaps; balanced binary search trees.
Hashing; bloom filters.
Final exam (1 attempt per 24 hours)