Informações sobre o curso
95,295 visualizações recentes

100% online

Comece imediatamente e aprenda em seu próprio cronograma.

Prazos flexíveis

Redefinir os prazos de acordo com sua programação.

Nível intermediário

Aprox. 34 horas para completar

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

Inglês

Legendas: Inglês, Coreano

Habilidades que você terá

GraphsData StructureAlgorithmsData Compression

100% online

Comece imediatamente e aprenda em seu próprio cronograma.

Prazos flexíveis

Redefinir os prazos de acordo com sua programação.

Nível intermediário

Aprox. 34 horas para completar

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

Inglês

Legendas: Inglês, Coreano

Programa - O que você aprenderá com este curso

Semana
1
10 minutos para concluir

Introduction

Welcome to Algorithms, Part II.

...
1 vídeo ((Total 9 mín.)), 2 leituras
1 vídeos
2 leituras
Welcome to Algorithms, Part II1min
Lecture Slides
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.

...
6 vídeos ((Total 98 mín.)), 2 leituras, 1 teste
6 videos
Graph API14min
Depth-First Search26min
Breadth-First Search13min
Connected Components18min
Graph Challenges14min
2 leituras
Overview1min
Lecture Slides
1 exercício prático
Interview Questions: Undirected Graphs (ungraded)6min
7 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.

...
5 vídeos ((Total 68 mín.)), 1 leitura, 2 testes
5 videos
Digraph API4min
Digraph Search20min
Topological Sort 12min
Strong Components20min
1 leituras
Lecture Slides
1 exercício prático
Interview Questions: Directed Graphs (ungraded)6min
Semana
2
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.

...
6 vídeos ((Total 85 mín.)), 2 leituras, 1 teste
6 videos
Greedy Algorithm12min
Edge-Weighted Graph API11min
Kruskal's Algorithm12min
Prim's Algorithm33min
MST Context10min
2 leituras
Overview1min
Lecture Slides
1 exercício prático
Interview Questions: Minimum Spanning Trees (ungraded)6min
8 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.

...
5 vídeos ((Total 85 mín.)), 1 leitura, 2 testes
5 videos
Shortest Path Properties14min
Dijkstra's Algorithm18min
Edge-Weighted DAGs19min
Negative Weights21min
1 leituras
Lecture Slides
1 exercício prático
Interview Questions: Shortest Paths (ungraded)6min
Semana
3
7 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.

...
6 vídeos ((Total 72 mín.)), 2 leituras, 2 testes
6 videos
Ford–Fulkerson Algorithm6min
Maxflow–Mincut Theorem9min
Running Time Analysis8min
Java Implementation14min
Maxflow Applications22min
2 leituras
Overview
Lecture Slides
1 exercício prático
Interview Questions: Maximum Flow (ungraded)6min
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.

...
6 vídeos ((Total 85 mín.)), 1 leitura, 1 teste
6 videos
Key-Indexed Counting12min
LSD Radix Sort15min
MSD Radix Sort13min
3-way Radix Quicksort7min
Suffix Arrays19min
1 leituras
Lecture Slides
1 exercício prático
Interview Questions: Radix Sorts (ungraded)6min
Semana
4
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.

...
3 vídeos ((Total 75 mín.)), 2 leituras, 1 teste
3 videos
Ternary Search Tries22min
Character-Based Operations20min
2 leituras
Overview10min
Lecture Slides
1 exercício prático
Interview Questions: Tries (ungraded)6min
8 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.

...
5 vídeos ((Total 75 mín.)), 1 leitura, 2 testes
5 videos
Brute-Force Substring Search10min
Knuth–Morris–Pratt33min
Boyer–Moore8min
Rabin–Karp16min
1 leituras
Lecture Slides10min
1 exercício prático
Interview Questions: Substring Search (ungraded)6min
Semana
5
2 horas para concluir

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 vídeos ((Total 83 mín.)), 2 leituras, 1 teste
5 videos
REs and NFAs13min
NFA Simulation18min
NFA Construction11min
Regular Expression Applications20min
2 leituras
Overview10min
Lecture Slides10min
1 exercício prático
Interview Questions: Regular Expressions (ungraded)6min
8 horas para concluir

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 vídeos ((Total 80 mín.)), 1 leitura, 2 testes
4 videos
Run-Length Coding5min
Huffman Compression24min
LZW Compression27min
1 leituras
Lecture Slides10min
1 exercício prático
Interview Questions: Data Compression (ungraded)6min
Semana
6
1 hora para concluir

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 vídeos ((Total 40 mín.)), 2 leituras, 1 teste
4 videos
Designing Algorithms8min
Establishing Lower Bounds9min
Classifying Problems12min
2 leituras
Overview10min
Lecture Slides10min
1 exercício prático
Interview Questions: Reductions (ungraded)6min
1 hora para concluir

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 vídeos ((Total 61 mín.)), 1 leitura, 1 teste
4 videos
Simplex Algorithm11min
Simplex Implementations16min
Linear Programming Reductions11min
1 leituras
Lecture Slides10min
1 exercício prático
Interview Questions: Linear Programming (ungraded)6min
2 horas para concluir

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 vídeos ((Total 85 mín.)), 1 leitura, 1 teste
6 videos
Search Problems10min
P vs. NP16min
Classifying Problems13min
NP-Completeness12min
Coping with Intractability 14min
1 leituras
Lecture Slides10min
1 exercício prático
Interview Questions: Intractability (ungraded)6min
5.0
118 avaliaçõesChevron Right

17%

comecei uma nova carreira após concluir estes cursos

19%

consegui um benefício significativo de carreira com este curso

10%

recebi um aumento ou promoção

Principais avaliações do Alogarítimos, Parte II

por 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.

por 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.

Instrutores

Avatar

Robert Sedgewick

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

Kevin Wayne

Phillip Y. Goldman '86 Senior Lecturer
Computer Science

Sobre 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....

Perguntas Frequentes – FAQ

  • Ao se inscrever para um Certificado, você terá acesso a todos os vídeos, testes e tarefas de programação (se aplicável). Tarefas avaliadas pelos colegas apenas podem ser enviadas e avaliadas após o início da sessão. Caso escolha explorar o curso sem adquiri-lo, talvez você não consiga acessar certas tarefas.

  • 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.

Mais dúvidas? Visite o Central de Ajuda ao Aprendiz.