课程信息
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561 个评分
93 个审阅
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中级

中级

完成时间(小时)

完成时间大约为33 小时

建议:6 weeks of study, 6–10 hours per week....
可选语言

英语(English)

字幕:英语(English), 韩语

您将获得的技能

GraphsData StructureAlgorithmsData Compression
100% 在线

100% 在线

立即开始,按照自己的计划学习。
可灵活调整截止日期

可灵活调整截止日期

根据您的日程表重置截止日期。
中级

中级

完成时间(小时)

完成时间大约为33 小时

建议:6 weeks of study, 6–10 hours per week....
可选语言

英语(English)

字幕:英语(English), 韩语

教学大纲 - 您将从这门课程中学到什么

1
完成时间(小时)
完成时间为 10 分钟

Introduction

Welcome to Algorithms, Part II....
Reading
1 个视频 (总计 9 分钟), 2 个阅读材料
Video1 个视频
Reading2 个阅读材料
Welcome to Algorithms, Part II1分钟
Lecture Slides0
完成时间(小时)
完成时间为 2 小时

Undirected Graphs

We define an undirected graph API and consider the adjacency-matrix and adjacency-lists representations. We introduce two classic algorithms for searching a graph—depth-first search and breadth-first search. We also consider the problem of computing connected components and conclude with related problems and applications....
Reading
6 个视频 (总计 98 分钟), 2 个阅读材料, 1 个测验
Video6 个视频
Graph API14分钟
Depth-First Search26分钟
Breadth-First Search13分钟
Connected Components18分钟
Graph Challenges14分钟
Reading2 个阅读材料
Overview1分钟
Lecture Slides0
Quiz1 个练习
Interview Questions: Undirected Graphs (ungraded)6分钟
完成时间(小时)
完成时间为 4 小时

Directed Graphs

In this lecture we study directed graphs. We begin with depth-first search and breadth-first search in digraphs and describe applications ranging from garbage collection to web crawling. Next, we introduce a depth-first search based algorithm for computing the topological order of an acyclic digraph. Finally, we implement the Kosaraju−Sharir algorithm for computing the strong components of a digraph....
Reading
5 个视频 (总计 68 分钟), 1 个阅读材料, 2 个测验
Video5 个视频
Digraph API4分钟
Digraph Search20分钟
Topological Sort 12分钟
Strong Components20分钟
Reading1 个阅读材料
Lecture Slides0
Quiz1 个练习
Interview Questions: Directed Graphs (ungraded)6分钟
2
完成时间(小时)
完成时间为 2 小时

Minimum Spanning Trees

In this lecture we study the minimum spanning tree problem. We begin by considering a generic greedy algorithm for the problem. Next, we consider and implement two classic algorithm for the problem—Kruskal's algorithm and Prim's algorithm. We conclude with some applications and open problems....
Reading
6 个视频 (总计 85 分钟), 2 个阅读材料, 1 个测验
Video6 个视频
Greedy Algorithm12分钟
Edge-Weighted Graph API11分钟
Kruskal's Algorithm12分钟
Prim's Algorithm33分钟
MST Context10分钟
Reading2 个阅读材料
Overview1分钟
Lecture Slides0
Quiz1 个练习
Interview Questions: Minimum Spanning Trees (ungraded)6分钟
完成时间(小时)
完成时间为 5 小时

Shortest Paths

In this lecture we study shortest-paths problems. We begin by analyzing some basic properties of shortest paths and a generic algorithm for the problem. We introduce and analyze Dijkstra's algorithm for shortest-paths problems with nonnegative weights. Next, we consider an even faster algorithm for DAGs, which works even if the weights are negative. We conclude with the Bellman−Ford−Moore algorithm for edge-weighted digraphs with no negative cycles. We also consider applications ranging from content-aware fill to arbitrage....
Reading
5 个视频 (总计 85 分钟), 1 个阅读材料, 2 个测验
Video5 个视频
Shortest Path Properties14分钟
Dijkstra's Algorithm18分钟
Edge-Weighted DAGs19分钟
Negative Weights21分钟
Reading1 个阅读材料
Lecture Slides0
Quiz1 个练习
Interview Questions: Shortest Paths (ungraded)6分钟
3
完成时间(小时)
完成时间为 4 小时

Maximum Flow and Minimum Cut

In this lecture we introduce the maximum flow and minimum cut problems. We begin with the Ford−Fulkerson algorithm. To analyze its correctness, we establish the maxflow−mincut theorem. Next, we consider an efficient implementation of the Ford−Fulkerson algorithm, using the shortest augmenting path rule. Finally, we consider applications, including bipartite matching and baseball elimination....
Reading
6 个视频 (总计 72 分钟), 2 个阅读材料, 2 个测验
Video6 个视频
Ford–Fulkerson Algorithm6分钟
Maxflow–Mincut Theorem9分钟
Running Time Analysis8分钟
Java Implementation14分钟
Maxflow Applications22分钟
Reading2 个阅读材料
Overview0
Lecture Slides0
Quiz1 个练习
Interview Questions: Maximum Flow (ungraded)6分钟
完成时间(小时)
完成时间为 2 小时

Radix Sorts

In this lecture we consider specialized sorting algorithms for strings and related objects. We begin with a subroutine to sort integers in a small range. We then consider two classic radix sorting algorithms—LSD and MSD radix sorts. Next, we consider an especially efficient variant, which is a hybrid of MSD radix sort and quicksort known as 3-way radix quicksort. We conclude with suffix sorting and related applications....
Reading
6 个视频 (总计 85 分钟), 1 个阅读材料, 1 个测验
Video6 个视频
Key-Indexed Counting12分钟
LSD Radix Sort15分钟
MSD Radix Sort13分钟
3-way Radix Quicksort7分钟
Suffix Arrays19分钟
Reading1 个阅读材料
Lecture Slides0
Quiz1 个练习
Interview Questions: Radix Sorts (ungraded)6分钟
4
完成时间(小时)
完成时间为 2 小时

Tries

In this lecture we consider specialized algorithms for symbol tables with string keys. Our goal is a data structure that is as fast as hashing and even more flexible than binary search trees. We begin with multiway tries; next we consider ternary search tries. Finally, we consider character-based operations, including prefix match and longest prefix, and related applications....
Reading
3 个视频 (总计 75 分钟), 2 个阅读材料, 1 个测验
Video3 个视频
R-way Tries32分钟
Ternary Search Tries22分钟
Character-Based Operations20分钟
Reading2 个阅读材料
Overview10分钟
Lecture Slides0
Quiz1 个练习
Interview Questions: Tries (ungraded)6分钟
完成时间(小时)
完成时间为 5 小时

Substring Search

In this lecture we consider algorithms for searching for a substring in a piece of text. We begin with a brute-force algorithm, whose running time is quadratic in the worst case. Next, we consider the ingenious Knuth−Morris−Pratt algorithm whose running time is guaranteed to be linear in the worst case. Then, we introduce the Boyer−Moore algorithm, whose running time is sublinear on typical inputs. Finally, we consider the Rabin−Karp fingerprint algorithm, which uses hashing in a clever way to solve the substring search and related problems....
Reading
5 个视频 (总计 75 分钟), 1 个阅读材料, 2 个测验
Video5 个视频
Brute-Force Substring Search10分钟
Knuth–Morris–Pratt33分钟
Boyer–Moore8分钟
Rabin–Karp16分钟
Reading1 个阅读材料
Lecture Slides10分钟
Quiz1 个练习
Interview Questions: Substring Search (ungraded)6分钟

讲师

Avatar

Robert Sedgewick

William O. Baker *39 Professor of Computer Science
Computer Science
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Kevin Wayne

Senior Lecturer
Computer Science

关于 Princeton University

Princeton University is a private research university located in Princeton, New Jersey, United States. It is one of the eight universities of the Ivy League, and one of the nine Colonial Colleges founded before the American Revolution....

常见问题

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  • Our central thesis is that algorithms are best understood by implementing and testing them. Our use of Java is essentially expository, and we shy away from exotic language features, so we expect you would be able to adapt our code to your favorite language. However, we require that you submit the programming assignments in Java.

  • Part II focuses on graph and string-processing algorithms. Topics include depth-first search, breadth-first search, topological sort, Kosaraju−Sharir, Kruskal, Prim, Dijkistra, Bellman−Ford, Ford−Fulkerson, LSD radix sort, MSD radix sort, 3-way radix quicksort, multiway tries, ternary search tries, Knuth−Morris−Pratt, Boyer−Moore, Rabin−Karp, regular expression matching, run-length coding, Huffman coding, LZW compression, and the Burrows−Wheeler transform.

    Part I focuses on elementary data structures, sorting, and searching. Topics include union-find, binary search, stacks, queues, bags, insertion sort, selection sort, shellsort, quicksort, 3-way quicksort, mergesort, heapsort, binary heaps, binary search trees, red−black trees, separate-chaining and linear-probing hash tables, Graham scan, and kd-trees.

  • Weekly programming assignments and interview questions.

    The programming assignments involve either implementing algorithms and data structures (graph algorithms, tries, and the Burrows–Wheeler transform) or applying algorithms and data structures to an interesting domain (computer graphics, computational linguistics, and data compression). The assignments are evaluated using a sophisticated autograder that provides detailed feedback about style, correctness, and efficiency.

    The interview questions are similar to those that you might find at a technical job interview. They are optional and not graded.

  • This course is for anyone using a computer to address large problems (and therefore needing efficient algorithms). At Princeton, over 25% of all students take the course, including people majoring in engineering, biology, physics, chemistry, economics, and many other fields, not just computer science.

  • The two courses are complementary. This one is essentially a programming course that concentrates on developing code; that one is essentially a math course that concentrates on understanding proofs. This course is about learning algorithms in the context of implementing and testing them in practical applications; that one is about learning algorithms in the context of developing mathematical models that help explain why they are efficient. In typical computer science curriculums, a course like this one is taken by first- and second-year students and a course like that one is taken by juniors and seniors.

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