このコースについて
5.0
560件の評価
93件のレビュー
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自分のスケジュールですぐに学習を始めてください。
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柔軟性のある期限

スケジュールに従って期限をリセットします。
中級レベル

中級レベル

修了時間

約33時間で修了

推奨:6 weeks of study, 6–10 hours per week....
利用可能な言語

英語

字幕:英語, 韓国語

習得するスキル

GraphsData StructureAlgorithmsData Compression
100%オンライン

100%オンライン

自分のスケジュールですぐに学習を始めてください。
柔軟性のある期限

柔軟性のある期限

スケジュールに従って期限をリセットします。
中級レベル

中級レベル

修了時間

約33時間で修了

推奨:6 weeks of study, 6–10 hours per week....
利用可能な言語

英語

字幕:英語, 韓国語

シラバス - 本コースの学習内容

1
修了時間
10分で修了

Introduction

Welcome to Algorithms, Part II....
Reading
1 video (Total 9 min), 2 readings
Video1件のビデオ
Reading2件の学習用教材
Welcome to Algorithms, Part II1 分
Lecture Slides0
修了時間
2時間で修了

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 videos (Total 98 min), 2 readings, 1 quiz
Video6件のビデオ
Graph API14 分
Depth-First Search26 分
Breadth-First Search13 分
Connected Components18 分
Graph Challenges14 分
Reading2件の学習用教材
Overview1 分
Lecture Slides0
Quiz1の練習問題
Interview Questions: Undirected Graphs (ungraded)6 分
修了時間
4時間で修了

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 videos (Total 68 min), 1 reading, 2 quizzes
Video5件のビデオ
Digraph API4 分
Digraph Search20 分
Topological Sort 12 分
Strong Components20 分
Reading1件の学習用教材
Lecture Slides0
Quiz1の練習問題
Interview Questions: Directed Graphs (ungraded)6 分
2
修了時間
2時間で修了

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 videos (Total 85 min), 2 readings, 1 quiz
Video6件のビデオ
Greedy Algorithm12 分
Edge-Weighted Graph API11 分
Kruskal's Algorithm12 分
Prim's Algorithm33 分
MST Context10 分
Reading2件の学習用教材
Overview1 分
Lecture Slides0
Quiz1の練習問題
Interview Questions: Minimum Spanning Trees (ungraded)6 分
修了時間
5時間で修了

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 videos (Total 85 min), 1 reading, 2 quizzes
Video5件のビデオ
Shortest Path Properties14 分
Dijkstra's Algorithm18 分
Edge-Weighted DAGs19 分
Negative Weights21 分
Reading1件の学習用教材
Lecture Slides0
Quiz1の練習問題
Interview Questions: Shortest Paths (ungraded)6 分
3
修了時間
4時間で修了

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 videos (Total 72 min), 2 readings, 2 quizzes
Video6件のビデオ
Ford–Fulkerson Algorithm6 分
Maxflow–Mincut Theorem9 分
Running Time Analysis8 分
Java Implementation14 分
Maxflow Applications22 分
Reading2件の学習用教材
Overview0
Lecture Slides0
Quiz1の練習問題
Interview Questions: Maximum Flow (ungraded)6 分
修了時間
2時間で修了

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 videos (Total 85 min), 1 reading, 1 quiz
Video6件のビデオ
Key-Indexed Counting12 分
LSD Radix Sort15 分
MSD Radix Sort13 分
3-way Radix Quicksort7 分
Suffix Arrays19 分
Reading1件の学習用教材
Lecture Slides0
Quiz1の練習問題
Interview Questions: Radix Sorts (ungraded)6 分
4
修了時間
2時間で修了

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 videos (Total 75 min), 2 readings, 1 quiz
Video3件のビデオ
Ternary Search Tries22 分
Character-Based Operations20 分
Reading2件の学習用教材
Overview10 分
Lecture Slides0
Quiz1の練習問題
Interview Questions: Tries (ungraded)6 分
修了時間
5時間で修了

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 videos (Total 75 min), 1 reading, 2 quizzes
Video5件のビデオ
Brute-Force Substring Search10 分
Knuth–Morris–Pratt33 分
Boyer–Moore8 分
Rabin–Karp16 分
Reading1件の学習用教材
Lecture Slides10 分
Quiz1の練習問題
Interview Questions: Substring Search (ungraded)6 分

講師

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Robert Sedgewick

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

Senior Lecturer
Computer Science

Princeton Universityについて

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....

よくある質問

  • 修了証に登録すると、すべてのビデオ、テスト、およびプログラミング課題(該当する場合)にアクセスできます。ピアレビュー課題は、セッションが開始してからのみ、提出およびレビューできます。購入せずにコースを検討することを選択する場合、特定の課題にアクセスすることはできません。

  • 修了証を購入する際、コースのすべての教材(採点課題を含む)にアクセスできます。コースを完了すると、電子修了証が成果のページに追加されます。そこから修了証を印刷したり、LinkedInのプロフィールに追加したりできます。コースの内容の閲覧のみを希望する場合は、無料でコースを聴講できます。

  • 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.

さらに質問がある場合は、受講者向けヘルプセンターにアクセスしてください。