算法，第二部分

課程信息

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This course covers the essential information that every serious programmer needs to know about algorithms and data structures, with emphasis on applications and scientific performance analysis of Java implementations. Part I covers elementary data structures, sorting, and searching algorithms. Part II focuses on graph- and string-processing algorithms.
All the features of this course are available for free.  It does not offer a certificate upon completion.

學生職業成果

10%

完成這些課程後已開始新的職業生涯

17%

通過此課程獲得實實在在的工作福利

15%

加薪或升職

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100% 在線

立即開始，按照自己的計劃學習。

中級

完成時間大約為63 小時

英語（English）

字幕：阿拉伯語（Arabic）, 法語（French）, （歐洲人講的）葡萄牙語, 意大利語, 越南語, 韓語, 德語（German）, 俄語（Russian）, 英語（English）, 西班牙語（Spanish）

您將獲得的技能

GraphsData StructureAlgorithmsData Compression

學生職業成果

10%

完成這些課程後已開始新的職業生涯

17%

通過此課程獲得實實在在的工作福利

15%

加薪或升職

可靈活調整截止日期

根據您的日程表重置截止日期。

100% 在線

立即開始，按照自己的計劃學習。

中級

完成時間大約為63 小時

英語（English）

字幕：阿拉伯語（Arabic）, 法語（French）, （歐洲人講的）葡萄牙語, 意大利語, 越南語, 韓語, 德語（German）, 俄語（Russian）, 英語（English）, 西班牙語（Spanish）

講師

授課教師評分

4.82/5 （174 個評分）

Robert Sedgewick

William O. Baker *39 Professor of Computer Science

Computer Science

1,016,462 個學生

7 門課程

Kevin Wayne

Phillip Y. Goldman '86 Senior Lecturer

Computer Science

991,954 個學生

5 門課程

教學大綱 - 您將從這門課程中學到什麼

內容評分96%（5,174 個評分）

週

1

週 1

完成時間為 10 分鐘

Introduction

Welcome to Algorithms, Part II.

完成時間為 10 分鐘

1 個視頻（總計 9 分鐘）, 2 個閱讀材料

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.

完成時間為 2 小時

6 個視頻（總計 98 分鐘）, 2 個閱讀材料, 1 個測驗

完成時間為 10 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.

完成時間為 10 小時

5 個視頻（總計 68 分鐘）, 1 個閱讀材料, 2 個測驗

週

2

週 2

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.

完成時間為 2 小時

6 個視頻（總計 85 分鐘）, 2 個閱讀材料, 1 個測驗

完成時間為 10 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.

完成時間為 10 小時

5 個視頻（總計 85 分鐘）, 1 個閱讀材料, 2 個測驗

週

3

週 3

完成時間為 8 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.

完成時間為 8 小時

6 個視頻（總計 72 分鐘）, 2 個閱讀材料, 2 個測驗

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.

完成時間為 2 小時

6 個視頻（總計 85 分鐘）, 1 個閱讀材料, 1 個測驗

週

4

週 4

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.

完成時間為 2 小時

3 個視頻（總計 75 分鐘）, 2 個閱讀材料, 1 個測驗

完成時間為 10 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.

完成時間為 10 小時

5 個視頻（總計 75 分鐘）, 1 個閱讀材料, 2 個測驗

週

5

週 5

完成時間為 2 小時

Regular Expressions

A regular expression is a method for specifying a set of strings. Our topic for this lecture is the famous grep algorithm that determines whether a given text contains any substring from the set. We examine an efficient implementation that makes use of our digraph reachability implementation from Week 1.

完成時間為 2 小時

5 個視頻（總計 83 分鐘）, 2 個閱讀材料, 1 個測驗

完成時間為 10 小時

Data Compression

We study and implement several classic data compression schemes, including run-length coding, Huffman compression, and LZW compression. We develop efficient implementations from first principles using a Java library for manipulating binary data that we developed for this purpose, based on priority queue and symbol table implementations from earlier lectures.

完成時間為 10 小時

4 個視頻（總計 80 分鐘）, 1 個閱讀材料, 2 個測驗

週

6

週 6

完成時間為 1 小時

Reductions

Our lectures this week are centered on the idea of problem-solving models like maxflow and shortest path, where a new problem can be formulated as an instance of one of those problems, and then solved with a classic and efficient algorithm. To complete the course, we describe the classic unsolved problem from theoretical computer science that is centered on the concept of algorithm efficiency and guides us in the search for efficient solutions to difficult problems.

完成時間為 1 小時

4 個視頻（總計 40 分鐘）, 2 個閱讀材料, 1 個測驗

完成時間為 2 小時

Linear Programming (optional)

The quintessential problem-solving model is known as linear programming, and the simplex method for solving it is one of the most widely used algorithms. In this lecture, we given an overview of this central topic in operations research and describe its relationship to algorithms that we have considered.

完成時間為 2 小時

4 個視頻（總計 61 分鐘）, 1 個閱讀材料, 1 個測驗

完成時間為 2 小時

Intractability

Is there a universal problem-solving model to which all problems that we would like to solve reduce and for which we know an efficient algorithm? You may be surprised to learn that we do no know the answer to this question. In this lecture we introduce the complexity classes P, NP, and NP-complete, pose the famous P = NP question, and consider implications in the context of algorithms that we have treated in this course.

完成時間為 2 小時

6 個視頻（總計 85 分鐘）, 1 個閱讀材料, 1 個測驗

審閱

4.9

279 條評論

5 stars
94.25%
4 stars
4.62%
3 stars
0.49%
2 stars
0.30%
1 star
0.30%

來自算法，第二部分的熱門評論

由 IO 提供2018年1月20日

Pretty challenging course, but very good. Having a book is a must (at least it was for me), video lectures complement book nicely, and some topics are explained better in the Algorithms, 4th ed. book.

由 MS 提供2021年2月27日

Essential information that every serious programmer needs to know about algorithms and data structures, with emphasis on applications and scientific performance analysis of Java implementations.

由 AK 提供2019年4月16日

Amazing course! Loved the theory and exercises! Just a note for others: Its part 1 had almost no dependency on book, but this part 2 has some dependency (e.g. chapter on Graph) on book as well.

由 HT 提供2020年2月7日

The algorithms are more difficult than part I, nevertheless Sedgewick's vids are still easy to understand. The only drawback maybe chapter 3, max flow min cut part, which is not very clarified.

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常見問題

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我什么时候能够访问课程视频和作业？
Once you enroll, you’ll have access to all videos and programming assignments.
Do I need to pay for this course?
No. All features of this course are available for free.
Can I earn a certificate in this course?
No. As per Princeton University policy, no certificates, credentials, or reports are awarded in connection with this course.
I have no familiarity with Java programming. Can I still take this course?
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.
Which algorithms and data structures are covered in this course?
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.
What kinds of assessments are available in this course?
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.
I am/was not a Computer Science major. Is this course for me?
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.
How does this course differ from Design and Analysis of Algorithms?
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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算法，第二部分