Acerca de este Curso

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Resultados profesionales del estudiante

18%

comenzó una nueva carrera después de completar estos cursos

22%

consiguió un beneficio tangible en su carrera profesional gracias a este curso

16%

consiguió un aumento de sueldo o ascenso
100 % en línea
Comienza de inmediato y aprende a tu propio ritmo.
Fechas límite flexibles
Restablece las fechas límite en función de tus horarios.
Nivel intermedio
Aprox. 58 horas para completar
Inglés (English)
Subtítulos: Inglés (English), Coreano

Habilidades que obtendrás

GraphsData StructureAlgorithmsData Compression

Resultados profesionales del estudiante

18%

comenzó una nueva carrera después de completar estos cursos

22%

consiguió un beneficio tangible en su carrera profesional gracias a este curso

16%

consiguió un aumento de sueldo o ascenso
100 % en línea
Comienza de inmediato y aprende a tu propio ritmo.
Fechas límite flexibles
Restablece las fechas límite en función de tus horarios.
Nivel intermedio
Aprox. 58 horas para completar
Inglés (English)
Subtítulos: Inglés (English), Coreano

ofrecido por

Logotipo de Universidad de Princeton

Universidad de Princeton

Programa - Qué aprenderás en este curso

Calificación del contenidoThumbs Up96%(4,087 calificaciones)Info
Semana
1

Semana 1

10 minutos para completar

Introduction

10 minutos para completar
1 video (Total 9 minutos), 2 lecturas
1 video
2 lecturas
Welcome to Algorithms, Part II1m
Lecture Slides
2 horas para completar

Undirected Graphs

2 horas para completar
6 videos (Total 98 minutos), 2 lecturas, 1 cuestionario
6 videos
Graph API14m
Depth-First Search26m
Breadth-First Search13m
Connected Components18m
Graph Challenges14m
2 lecturas
Overview1m
Lecture Slides
1 ejercicio de práctica
Interview Questions: Undirected Graphs (ungraded)6m
9 horas para completar

Directed Graphs

9 horas para completar
5 videos (Total 68 minutos), 1 lectura, 2 cuestionarios
5 videos
Digraph API4m
Digraph Search20m
Topological Sort 12m
Strong Components20m
1 lectura
Lecture Slides
1 ejercicio de práctica
Interview Questions: Directed Graphs (ungraded)6m
Semana
2

Semana 2

2 horas para completar

Minimum Spanning Trees

2 horas para completar
6 videos (Total 85 minutos), 2 lecturas, 1 cuestionario
6 videos
Greedy Algorithm12m
Edge-Weighted Graph API11m
Kruskal's Algorithm12m
Prim's Algorithm33m
MST Context10m
2 lecturas
Overview1m
Lecture Slides
1 ejercicio de práctica
Interview Questions: Minimum Spanning Trees (ungraded)6m
10 horas para completar

Shortest Paths

10 horas para completar
5 videos (Total 85 minutos), 1 lectura, 2 cuestionarios
5 videos
Shortest Path Properties14m
Dijkstra's Algorithm18m
Edge-Weighted DAGs19m
Negative Weights21m
1 lectura
Lecture Slides
1 ejercicio de práctica
Interview Questions: Shortest Paths (ungraded)6m
Semana
3

Semana 3

7 horas para completar

Maximum Flow and Minimum Cut

7 horas para completar
6 videos (Total 72 minutos), 2 lecturas, 2 cuestionarios
6 videos
Ford–Fulkerson Algorithm6m
Maxflow–Mincut Theorem9m
Running Time Analysis8m
Java Implementation14m
Maxflow Applications22m
2 lecturas
Overview
Lecture Slides
1 ejercicio de práctica
Interview Questions: Maximum Flow (ungraded)6m
2 horas para completar

Radix Sorts

2 horas para completar
6 videos (Total 85 minutos), 1 lectura, 1 cuestionario
6 videos
Key-Indexed Counting12m
LSD Radix Sort15m
MSD Radix Sort13m
3-way Radix Quicksort7m
Suffix Arrays19m
1 lectura
Lecture Slides
1 ejercicio de práctica
Interview Questions: Radix Sorts (ungraded)6m
Semana
4

Semana 4

2 horas para completar

Tries

2 horas para completar
3 videos (Total 75 minutos), 2 lecturas, 1 cuestionario
3 videos
Ternary Search Tries22m
Character-Based Operations20m
2 lecturas
Overview10m
Lecture Slides
1 ejercicio de práctica
Interview Questions: Tries (ungraded)6m
10 horas para completar

Substring Search

10 horas para completar
5 videos (Total 75 minutos), 1 lectura, 2 cuestionarios
5 videos
Brute-Force Substring Search10m
Knuth–Morris–Pratt33m
Boyer–Moore8m
Rabin–Karp16m
1 lectura
Lecture Slides10m
1 ejercicio de práctica
Interview Questions: Substring Search (ungraded)6m

Revisiones

Principales revisiones sobre ALGORITHMS, PART II

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Preguntas Frecuentes

  • Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:

    • The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.

    • The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.

  • Once you enroll, you’ll have access to all videos and programming assignments.

  • 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.

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