开始时间: 05/18/2022 持续时间: Approximately 4 months to complete Suggested pace of 4 hours/week
Algorithms are the heart of computer science, and the subject has countless practical applications as well as intellectual depth. This specialization is an introduction to algorithms for learners with at least a little programming experience. The specialization is rigorous but emphasizes the big picture and conceptual understanding over low-level implementation and mathematical details. After completing this specialization, you will be well-positioned to ace your technical interviews and speak fluently about algorithms with other programmers and computer scientists. 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.算法专业化：算法是计算机科学的核心，该主题具有无数的实际应用以及知识深度。该专业是对至少具有一点编程经验的学习者的算法介绍。专业化很严格，但是强调了对低级实现和数学细节的总体了解和概念理解。完成此专业后，您将可以很好地接受技术面试，并能与其他程序员和计算机科学家流利地谈论算法。 关于讲师：Tim Roughgarden自2004年以来一直是斯坦福大学计算机科学系的教授。他在算法及其应用方面进行了广泛的教学和出版。
Title:Divide and Conquer, Sorting and Searching, and Randomized Algorithms
Description:The primary topics in this part of the specialization are: asymptotic ("Big-oh") notation, sorting and searching, divide and conquer (master method, integer and matrix multiplication, closest pair), and randomized algorithms (QuickSort, contraction algorithm for min cuts).
Title:Graph Search, Shortest Paths, and Data Structures
Description:The primary topics in this part of the specialization are: data structures (heaps, balanced search trees, hash tables, bloom filters), graph primitives (applications of breadth-first and depth-first search, connectivity, shortest paths), and their applications (ranging from deduplication to social network analysis).
Title:Greedy Algorithms, Minimum Spanning Trees, and Dynamic Programming
Description:The primary topics in this part of the specialization are: greedy algorithms (scheduling, minimum spanning trees, clustering, Huffman codes) and dynamic programming (knapsack, sequence alignment, optimal search trees).
Title:Shortest Paths Revisited, NP-Complete Problems and What To Do About Them
Description:The primary topics in this part of the specialization are: shortest paths (Bellman-Ford, Floyd-Warshall, Johnson), NP-completeness and what it means for the algorithm designer, and strategies for coping with computationally intractable problems (analysis of heuristics, local search).