Об этом курсе
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Часов на завершение

Прибл. 33 часа на выполнение

Предполагаемая нагрузка: 6 weeks of study, 6–10 hours per week....
Доступные языки

Английский

Субтитры: Английский, Корейский

Приобретаемые навыки

GraphsData StructureAlgorithmsData Compression
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Гибкие сроки

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Назначьте сроки сдачи в соответствии со своим графиком.
Промежуточный уровень

Промежуточный уровень

Часов на завершение

Прибл. 33 часа на выполнение

Предполагаемая нагрузка: 6 weeks of study, 6–10 hours per week....
Доступные языки

Английский

Субтитры: Английский, Корейский

Программа курса: что вы изучите

Неделя
1
Часов на завершение
10 минуты на завершение

Introduction

Welcome to Algorithms, Part II....
Reading
1 video (Total 9 min), 2 материалов для самостоятельного изучения
Video1 видео
Reading2 материала для самостоятельного изучения
Welcome to Algorithms, Part II1мин
Lecture Slides0
Часов на завершение
2 ч. на завершение

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 материалов для самостоятельного изучения, 1 тест
Video6 видео
Graph API14мин
Depth-First Search26мин
Breadth-First Search13мин
Connected Components18мин
Graph Challenges14мин
Reading2 материала для самостоятельного изучения
Overview1мин
Lecture Slides0
Quiz1 практическое упражнение
Interview Questions: Undirected Graphs (ungraded)6мин
Часов на завершение
4 ч. на завершение

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 материал для самостоятельного изучения, 2 тестов
Video5 видео
Digraph API4мин
Digraph Search20мин
Topological Sort 12мин
Strong Components20мин
Reading1 материал для самостоятельного изучения
Lecture Slides0
Quiz1 практическое упражнение
Interview Questions: Directed Graphs (ungraded)6мин
Неделя
2
Часов на завершение
2 ч. на завершение

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 материалов для самостоятельного изучения, 1 тест
Video6 видео
Greedy Algorithm12мин
Edge-Weighted Graph API11мин
Kruskal's Algorithm12мин
Prim's Algorithm33мин
MST Context10мин
Reading2 материала для самостоятельного изучения
Overview1мин
Lecture Slides0
Quiz1 практическое упражнение
Interview Questions: Minimum Spanning Trees (ungraded)6мин
Часов на завершение
5 ч. на завершение

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 материал для самостоятельного изучения, 2 тестов
Video5 видео
Shortest Path Properties14мин
Dijkstra's Algorithm18мин
Edge-Weighted DAGs19мин
Negative Weights21мин
Reading1 материал для самостоятельного изучения
Lecture Slides0
Quiz1 практическое упражнение
Interview Questions: Shortest Paths (ungraded)6мин
Неделя
3
Часов на завершение
4 ч. на завершение

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 материалов для самостоятельного изучения, 2 тестов
Video6 видео
Ford–Fulkerson Algorithm6мин
Maxflow–Mincut Theorem9мин
Running Time Analysis8мин
Java Implementation14мин
Maxflow Applications22мин
Reading2 материала для самостоятельного изучения
Overview0
Lecture Slides0
Quiz1 практическое упражнение
Interview Questions: Maximum Flow (ungraded)6мин
Часов на завершение
2 ч. на завершение

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 материал для самостоятельного изучения, 1 тест
Video6 видео
Key-Indexed Counting12мин
LSD Radix Sort15мин
MSD Radix Sort13мин
3-way Radix Quicksort7мин
Suffix Arrays19мин
Reading1 материал для самостоятельного изучения
Lecture Slides0
Quiz1 практическое упражнение
Interview Questions: Radix Sorts (ungraded)6мин
Неделя
4
Часов на завершение
2 ч. на завершение

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 материалов для самостоятельного изучения, 1 тест
Video3 видео
R-way Tries32мин
Ternary Search Tries22мин
Character-Based Operations20мин
Reading2 материала для самостоятельного изучения
Overview10мин
Lecture Slides0
Quiz1 практическое упражнение
Interview Questions: Tries (ungraded)6мин
Часов на завершение
5 ч. на завершение

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 материал для самостоятельного изучения, 2 тестов
Video5 видео
Brute-Force Substring Search10мин
Knuth–Morris–Pratt33мин
Boyer–Moore8мин
Rabin–Karp16мин
Reading1 материал для самостоятельного изучения
Lecture Slides10мин
Quiz1 практическое упражнение
Interview Questions: Substring Search (ungraded)6мин

Преподавателя

Avatar

Robert Sedgewick

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

Kevin Wayne

Senior Lecturer
Computer Science

О 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....

Часто задаваемые вопросы

  • Зарегистрировавшись на сертификацию, вы получите доступ ко всем видео, тестам и заданиям по программированию (если они предусмотрены). Задания по взаимной оценке сокурсниками можно сдавать и проверять только после начала сессии. Если вы проходите курс без оплаты, некоторые задания могут быть недоступны.

  • Оплатив сертификацию, вы получите доступ ко всем материалам курса, включая оцениваемые задания. После успешного прохождения курса на странице ваших достижений появится электронный сертификат. Оттуда его можно распечатать или прикрепить к профилю LinkedIn. Просто ознакомиться с содержанием курса можно бесплатно.

  • 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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