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.
oferecido por
Alogarítimos, Parte II
Universidade de PrincetonInformações sobre o curso
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Resultados de carreira do aprendiz
10%
comecei uma nova carreira após concluir estes cursos
17%
consegui um benefício significativo de carreira com este curso
15%
recebi um aumento ou promoção
100% on-line
Comece imediatamente e aprenda em seu próprio cronograma.
Prazos flexíveis
Redefinir os prazos de acordo com sua programação.
Nível intermediário
Aprox. 63 horas para completar
Inglês
Legendas: Árabe, Francês, Portuguese (European), Italiano, Vietnamita, Coreano, Alemão, Russo, Inglês, Espanhol
Habilidades que você terá
GraphsData StructureAlgorithmsData Compression
Resultados de carreira do aprendiz
10%
comecei uma nova carreira após concluir estes cursos
17%
consegui um benefício significativo de carreira com este curso
15%
recebi um aumento ou promoção
100% on-line
Comece imediatamente e aprenda em seu próprio cronograma.
Prazos flexíveis
Redefinir os prazos de acordo com sua programação.
Nível intermediário
Aprox. 63 horas para completar
Inglês
Legendas: Árabe, Francês, Portuguese (European), Italiano, Vietnamita, Coreano, Alemão, Russo, Inglês, Espanhol
oferecido por
Universidade de Princeton
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.
Programa - O que você aprenderá com este curso
10 minutos para concluir
Introduction
Welcome to Algorithms, Part II.
10 minutos para concluir
1 vídeo (Total 9 mín.), 2 leituras
2 horas para concluir
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.
2 horas para concluir
6 vídeos (Total 98 mín.), 2 leituras, 1 teste
10 horas para concluir
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.
10 horas para concluir
5 vídeos (Total 68 mín.), 1 leitura, 2 testes
2 horas para concluir
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.
2 horas para concluir
6 vídeos (Total 85 mín.), 2 leituras, 1 teste
10 horas para concluir
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.
10 horas para concluir
5 vídeos (Total 85 mín.), 1 leitura, 2 testes
8 horas para concluir
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.
8 horas para concluir
6 vídeos (Total 72 mín.), 2 leituras, 2 testes
2 horas para concluir
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.
2 horas para concluir
6 vídeos (Total 85 mín.), 1 leitura, 1 teste
2 horas para concluir
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.
2 horas para concluir
3 vídeos (Total 75 mín.), 2 leituras, 1 teste
10 horas para concluir
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.
10 horas para concluir
5 vídeos (Total 75 mín.), 1 leitura, 2 testes
Avaliações
Principais avaliações do ALOGARÍTIMOS, PARTE II
por IO20 de Jan de 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.
por MS27 de Fev de 2021
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.
por AK16 de Abr de 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.
por HT7 de Fev de 2020
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.
Perguntas Frequentes – FAQ
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I have no familiarity with Java programming. Can I still take this course?
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How does this course differ from Design and Analysis of Algorithms?
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