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中級

完成時間(小時)

完成時間大約為33 小時

建議:6 weeks of study, 6–10 hours per week....
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英語(English)

字幕:英語(English), 韓語

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GraphsData StructureAlgorithmsData Compression
100% 在線

100% 在線

立即開始,按照自己的計劃學習。
可靈活調整截止日期

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根據您的日程表重置截止日期。
中級

中級

完成時間(小時)

完成時間大約為33 小時

建議:6 weeks of study, 6–10 hours per week....
可選語言

英語(English)

字幕:英語(English), 韓語

教學大綱 - 您將從這門課程中學到什麼

1
完成時間(小時)
完成時間為 10 分鐘

Introduction

Welcome to Algorithms, Part II....
Reading
1 個視頻 (總計 9 分鐘), 2 個閱讀材料
Video1 個視頻
Reading2 個閱讀材料
Welcome to Algorithms, Part II1分鐘
Lecture Slides
完成時間(小時)
完成時間為 2 小時

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 個視頻 (總計 98 分鐘), 2 個閱讀材料, 1 個測驗
Video6 個視頻
Graph API14分鐘
Depth-First Search26分鐘
Breadth-First Search13分鐘
Connected Components18分鐘
Graph Challenges14分鐘
Reading2 個閱讀材料
Overview1分鐘
Lecture Slides
Quiz1 個練習
Interview Questions: Undirected Graphs (ungraded)6分鐘
完成時間(小時)
完成時間為 4 小時

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 個視頻 (總計 68 分鐘), 1 個閱讀材料, 2 個測驗
Video5 個視頻
Digraph API4分鐘
Digraph Search20分鐘
Topological Sort 12分鐘
Strong Components20分鐘
Reading1 個閱讀材料
Lecture Slides
Quiz1 個練習
Interview Questions: Directed Graphs (ungraded)6分鐘
2
完成時間(小時)
完成時間為 2 小時

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 個視頻 (總計 85 分鐘), 2 個閱讀材料, 1 個測驗
Video6 個視頻
Greedy Algorithm12分鐘
Edge-Weighted Graph API11分鐘
Kruskal's Algorithm12分鐘
Prim's Algorithm33分鐘
MST Context10分鐘
Reading2 個閱讀材料
Overview1分鐘
Lecture Slides
Quiz1 個練習
Interview Questions: Minimum Spanning Trees (ungraded)6分鐘
完成時間(小時)
完成時間為 5 小時

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 個視頻 (總計 85 分鐘), 1 個閱讀材料, 2 個測驗
Video5 個視頻
Shortest Path Properties14分鐘
Dijkstra's Algorithm18分鐘
Edge-Weighted DAGs19分鐘
Negative Weights21分鐘
Reading1 個閱讀材料
Lecture Slides
Quiz1 個練習
Interview Questions: Shortest Paths (ungraded)6分鐘
3
完成時間(小時)
完成時間為 4 小時

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 個視頻 (總計 72 分鐘), 2 個閱讀材料, 2 個測驗
Video6 個視頻
Ford–Fulkerson Algorithm6分鐘
Maxflow–Mincut Theorem9分鐘
Running Time Analysis8分鐘
Java Implementation14分鐘
Maxflow Applications22分鐘
Reading2 個閱讀材料
Overview
Lecture Slides
Quiz1 個練習
Interview Questions: Maximum Flow (ungraded)6分鐘
完成時間(小時)
完成時間為 2 小時

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 個視頻 (總計 85 分鐘), 1 個閱讀材料, 1 個測驗
Video6 個視頻
Key-Indexed Counting12分鐘
LSD Radix Sort15分鐘
MSD Radix Sort13分鐘
3-way Radix Quicksort7分鐘
Suffix Arrays19分鐘
Reading1 個閱讀材料
Lecture Slides
Quiz1 個練習
Interview Questions: Radix Sorts (ungraded)6分鐘
4
完成時間(小時)
完成時間為 2 小時

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 個視頻 (總計 75 分鐘), 2 個閱讀材料, 1 個測驗
Video3 個視頻
R-way Tries32分鐘
Ternary Search Tries22分鐘
Character-Based Operations20分鐘
Reading2 個閱讀材料
Overview10分鐘
Lecture Slides
Quiz1 個練習
Interview Questions: Tries (ungraded)6分鐘
完成時間(小時)
完成時間為 5 小時

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 個視頻 (總計 75 分鐘), 1 個閱讀材料, 2 個測驗
Video5 個視頻
Brute-Force Substring Search10分鐘
Knuth–Morris–Pratt33分鐘
Boyer–Moore8分鐘
Rabin–Karp16分鐘
Reading1 個閱讀材料
Lecture Slides10分鐘
Quiz1 個練習
Interview Questions: Substring Search (ungraded)6分鐘

講師

Avatar

Robert Sedgewick

William O. Baker *39 Professor of Computer Science
Computer Science
Avatar

Kevin Wayne

Senior Lecturer
Computer Science

關於 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....

常見問題

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  • 您购买证书后,将有权访问所有课程材料,包括评分作业。完成课程后,您的电子课程证书将添加到您的成就页中,您可以通过该页打印您的课程证书或将其添加到您的领英档案中。如果您只想阅读和查看课程内容,可以免费旁听课程。

  • 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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