Acerca de este Curso
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Fechas límite flexibles

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Nivel intermedio

Aprox. 33 horas para completar

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

Inglés (English)

Subtítulos: Inglés (English), Coreano, Ruso (Russian)

Habilidades que obtendrás

Data StructureAlgorithmsJava Programming

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. 33 horas para completar

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

Inglés (English)

Subtítulos: Inglés (English), Coreano, Ruso (Russian)

Programa - Qué aprenderás en este curso

Semana
1
10 minutos para completar

Course Introduction

1 video (Total 9 minutos), 2 lecturas
1 video
2 lecturas
Welcome to Algorithms, Part I1m
Lecture Slides
9 horas para completar

Union−Find

5 videos (Total 51 minutos), 2 lecturas, 2 cuestionarios
5 videos
Quick Find10m
Quick Union7m
Quick-Union Improvements13m
Union−Find Applications9m
2 lecturas
Overview1m
Lecture Slides
1 ejercicio de práctica
Interview Questions: Union–Find (ungraded)
1 hora para completar

Analysis of Algorithms

6 videos (Total 66 minutos), 1 lectura, 1 cuestionario
6 videos
Observations10m
Mathematical Models12m
Order-of-Growth Classifications14m
Theory of Algorithms11m
Memory8m
1 lectura
Lecture Slides
1 ejercicio de práctica
Interview Questions: Analysis of Algorithms (ungraded)
Semana
2
9 horas para completar

Stacks and Queues

6 videos (Total 61 minutos), 2 lecturas, 2 cuestionarios
6 videos
Resizing Arrays9m
Queues4m
Generics9m
Iterators7m
Stack and Queue Applications (optional)13m
2 lecturas
Overview1m
Lecture Slides
1 ejercicio de práctica
Interview Questions: Stacks and Queues (ungraded)
1 hora para completar

Elementary Sorts

6 videos (Total 63 minutos), 1 lectura, 1 cuestionario
6 videos
Selection Sort6m
Insertion Sort9m
Shellsort10m
Shuffling7m
Convex Hull13m
1 lectura
Lecture Slides
1 ejercicio de práctica
Interview Questions: Elementary Sorts (ungraded)
Semana
3
9 horas para completar

Mergesort

5 videos (Total 49 minutos), 2 lecturas, 2 cuestionarios
5 videos
Bottom-up Mergesort3m
Sorting Complexity9m
Comparators6m
Stability5m
2 lecturas
Overview
Lecture Slides
1 ejercicio de práctica
Interview Questions: Mergesort (ungraded)
1 hora para completar

Quicksort

4 videos (Total 50 minutos), 1 lectura, 1 cuestionario
4 videos
Selection7m
Duplicate Keys11m
System Sorts11m
1 lectura
Lecture Slides
1 ejercicio de práctica
Interview Questions: Quicksort (ungraded)
Semana
4
9 horas para completar

Priority Queues

4 videos (Total 74 minutos), 2 lecturas, 2 cuestionarios
4 videos
Binary Heaps23m
Heapsort14m
Event-Driven Simulation (optional)22m
2 lecturas
Overview10m
Lecture Slides
1 ejercicio de práctica
Interview Questions: Priority Queues (ungraded)
1 hora para completar

Elementary Symbol Tables

6 videos (Total 77 minutos), 1 lectura, 1 cuestionario
6 videos
Elementary Implementations9m
Ordered Operations6m
Binary Search Trees19m
Ordered Operations in BSTs10m
Deletion in BSTs9m
1 lectura
Lecture Slides
1 ejercicio de práctica
Interview Questions: Elementary Symbol Tables (ungraded)8m
4.9
1180 revisionesChevron Right

32%

comenzó una nueva carrera después de completar estos cursos

34%

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

17%

consiguió un aumento de sueldo o ascenso

Principales revisiones sobre Algorithms, Part I

por RMJun 1st 2017

This is a great class. I learned / re-learned a ton. The assignments were challenge and left a definite feel of accomplishment. The programming environment and automated grading system were excellent.

por RPJun 11th 2017

Incredible learning experience. Every programmer in industry should take this course if only to dispel the idea that with the advent of cloud computing exponential algorithms can still ruin your day!

Instructores

Avatar

Kevin Wayne

Phillip Y. Goldman '86 Senior Lecturer
Computer Science
Avatar

Robert Sedgewick

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

Acerca de Universidad 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....

Preguntas Frecuentes

  • 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 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.

    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.

  • Weekly exercises, weekly programming assignments, weekly interview questions, and a final exam.

    The exercises are primarily composed of short drill questions (such as tracing the execution of an algorithm or data structure), designed to help you master the material.

    The programming assignments involve either implementing algorithms and data structures (deques, randomized queues, and kd-trees) or applying algorithms and data structures to an interesting domain (computational chemistry, computational geometry, and mathematical recreation). 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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