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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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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

Welcome to Algorithms, Part II....
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

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....
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
7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....
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

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....
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
8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....
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

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....
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

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....
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

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....
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
8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....
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
2時間で修了

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....
5件のビデオ (合計83分), 2 readings, 1 quiz
5件のビデオ
REs and NFAs13 分
NFA Simulation18 分
NFA Construction11 分
Regular Expression Applications20 分
2件の学習用教材
Overview10 分
Lecture Slides10 分
1の練習問題
Interview Questions: Regular Expressions (ungraded)6 分
8時間で修了

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....
4件のビデオ (合計80分), 1 reading, 2 quizzes
4件のビデオ
Run-Length Coding5 分
Huffman Compression24 分
LZW Compression27 分
1件の学習用教材
Lecture Slides10 分
1の練習問題
Interview Questions: Data Compression (ungraded)6 分
6
1時間で修了

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. ...
4件のビデオ (合計40分), 2 readings, 1 quiz
4件のビデオ
Designing Algorithms8 分
Establishing Lower Bounds9 分
Classifying Problems12 分
2件の学習用教材
Overview10 分
Lecture Slides10 分
1の練習問題
Interview Questions: Reductions (ungraded)6 分
1時間で修了

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....
4件のビデオ (合計61分), 1 reading, 1 quiz
4件のビデオ
Simplex Algorithm11 分
Simplex Implementations16 分
Linear Programming Reductions11 分
1件の学習用教材
Lecture Slides10 分
1の練習問題
Interview Questions: Linear Programming (ungraded)6 分
2時間で修了

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....
6件のビデオ (合計85分), 1 reading, 1 quiz
6件のビデオ
Search Problems10 分
P vs. NP16 分
Classifying Problems13 分
NP-Completeness12 分
Coping with Intractability 14 分
1件の学習用教材
Lecture Slides10 分
1の練習問題
Interview Questions: Intractability (ungraded)6 分
5.0
118件のレビューChevron Right

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コース終了後に新しいキャリアをスタートした

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人気のレビュー

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
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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。