このコースについて
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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

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

約34時間で修了

推奨:6 weeks of study, 6–10 hours per week....

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

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

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

約34時間で修了

推奨:6 weeks of study, 6–10 hours per week....

英語

字幕:英語, 韓国語

シラバス - 本コースの学習内容

1
10分で修了

Introduction

1件のビデオ (合計9分), 2 readings
1件のビデオ
2件の学習用教材
Welcome to Algorithms, Part II1 分
Lecture Slides
2時間で修了

Undirected Graphs

6件のビデオ (合計98分), 2 readings, 1 quiz
6件のビデオ
Graph API14 分
Depth-First Search26 分
Breadth-First Search13 分
Connected Components18 分
Graph Challenges14 分
2件の学習用教材
Overview1 分
Lecture Slides
1の練習問題
Interview Questions: Undirected Graphs (ungraded)6 分
9時間で修了

Directed Graphs

5件のビデオ (合計68分), 1 reading, 2 quizzes
5件のビデオ
Digraph API4 分
Digraph Search20 分
Topological Sort 12 分
Strong Components20 分
1件の学習用教材
Lecture Slides
1の練習問題
Interview Questions: Directed Graphs (ungraded)6 分
2
2時間で修了

Minimum Spanning Trees

6件のビデオ (合計85分), 2 readings, 1 quiz
6件のビデオ
Greedy Algorithm12 分
Edge-Weighted Graph API11 分
Kruskal's Algorithm12 分
Prim's Algorithm33 分
MST Context10 分
2件の学習用教材
Overview1 分
Lecture Slides
1の練習問題
Interview Questions: Minimum Spanning Trees (ungraded)6 分
10時間で修了

Shortest Paths

5件のビデオ (合計85分), 1 reading, 2 quizzes
5件のビデオ
Shortest Path Properties14 分
Dijkstra's Algorithm18 分
Edge-Weighted DAGs19 分
Negative Weights21 分
1件の学習用教材
Lecture Slides
1の練習問題
Interview Questions: Shortest Paths (ungraded)6 分
3
7時間で修了

Maximum Flow and Minimum Cut

6件のビデオ (合計72分), 2 readings, 2 quizzes
6件のビデオ
Ford–Fulkerson Algorithm6 分
Maxflow–Mincut Theorem9 分
Running Time Analysis8 分
Java Implementation14 分
Maxflow Applications22 分
2件の学習用教材
Overview
Lecture Slides
1の練習問題
Interview Questions: Maximum Flow (ungraded)6 分
2時間で修了

Radix Sorts

6件のビデオ (合計85分), 1 reading, 1 quiz
6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
1件の学習用教材
Lecture Slides
1の練習問題
Interview Questions: Radix Sorts (ungraded)6 分
4
2時間で修了

Tries

3件のビデオ (合計75分), 2 readings, 1 quiz
3件のビデオ
Ternary Search Tries22 分
Character-Based Operations20 分
2件の学習用教材
Overview10 分
Lecture Slides
1の練習問題
Interview Questions: Tries (ungraded)6 分
10時間で修了

Substring Search

5件のビデオ (合計75分), 1 reading, 2 quizzes
5件のビデオ
Brute-Force Substring Search10 分
Knuth–Morris–Pratt33 分
Boyer–Moore8 分
Rabin–Karp16 分
1件の学習用教材
Lecture Slides10 分
1の練習問題
Interview Questions: Substring Search (ungraded)6 分
5.0
136件のレビューChevron Right

15%

コース終了後に新しいキャリアをスタートした

20%

コースが具体的なキャリアアップにつながった

13%

昇給や昇進につながった

Algorithms, Part II からの人気レビュー

by IOJan 21st 2018

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.

by AKApr 17th 2019

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.

講師

Avatar

Robert Sedgewick

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

Kevin Wayne

Phillip Y. Goldman '86 Senior Lecturer
Computer Science

プリンストン大学(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。

  • No. All features of this course are available for free.

  • No. As per Princeton University policy, no certificates, credentials, or reports are awarded in connection with 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.

  • 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。