课程信息
4.9
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934 个审阅
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中级

中级

完成时间(小时)

完成时间大约为31 小时

建议:6 weeks of study, 6–10 hours per week....
可选语言

英语(English)

字幕:英语(English), 韩语

您将获得的技能

Data StructurePriority QueueAlgorithmsJava Programming
100% 在线

100% 在线

立即开始,按照自己的计划学习。
可灵活调整截止日期

可灵活调整截止日期

根据您的日程表重置截止日期。
中级

中级

完成时间(小时)

完成时间大约为31 小时

建议:6 weeks of study, 6–10 hours per week....
可选语言

英语(English)

字幕:英语(English), 韩语

教学大纲 - 您将从这门课程中学到什么

1
完成时间(小时)
完成时间为 10 分钟

Course Introduction

Welcome to Algorithms, Part I....
Reading
1 个视频 (总计 9 分钟), 2 个阅读材料
Video1 个视频
Reading2 个阅读材料
Welcome to Algorithms, Part I1分钟
Lecture Slides
完成时间(小时)
完成时间为 6 小时

Union−Find

We illustrate our basic approach to developing and analyzing algorithms by considering the dynamic connectivity problem. We introduce the union−find data type and consider several implementations (quick find, quick union, weighted quick union, and weighted quick union with path compression). Finally, we apply the union−find data type to the percolation problem from physical chemistry....
Reading
5 个视频 (总计 51 分钟), 2 个阅读材料, 2 个测验
Video5 个视频
Quick Find10分钟
Quick Union7分钟
Quick-Union Improvements13分钟
Union−Find Applications9分钟
Reading2 个阅读材料
Overview1分钟
Lecture Slides
Quiz1 个练习
Interview Questions: Union–Find (ungraded)
完成时间(小时)
完成时间为 1 小时

Analysis of Algorithms

The basis of our approach for analyzing the performance of algorithms is the scientific method. We begin by performing computational experiments to measure the running times of our programs. We use these measurements to develop hypotheses about performance. Next, we create mathematical models to explain their behavior. Finally, we consider analyzing the memory usage of our Java programs....
Reading
6 个视频 (总计 66 分钟), 1 个阅读材料, 1 个测验
Video6 个视频
Observations10分钟
Mathematical Models12分钟
Order-of-Growth Classifications14分钟
Theory of Algorithms11分钟
Memory8分钟
Reading1 个阅读材料
Lecture Slides
Quiz1 个练习
Interview Questions: Analysis of Algorithms (ungraded)
2
完成时间(小时)
完成时间为 6 小时

Stacks and Queues

We consider two fundamental data types for storing collections of objects: the stack and the queue. We implement each using either a singly-linked list or a resizing array. We introduce two advanced Java features—generics and iterators—that simplify client code. Finally, we consider various applications of stacks and queues ranging from parsing arithmetic expressions to simulating queueing systems....
Reading
6 个视频 (总计 61 分钟), 2 个阅读材料, 2 个测验
Video6 个视频
Stacks16分钟
Resizing Arrays9分钟
Queues4分钟
Generics9分钟
Iterators7分钟
Stack and Queue Applications (optional)13分钟
Reading2 个阅读材料
Overview1分钟
Lecture Slides
Quiz1 个练习
Interview Questions: Stacks and Queues (ungraded)
完成时间(小时)
完成时间为 1 小时

Elementary Sorts

We introduce the sorting problem and Java's Comparable interface. We study two elementary sorting methods (selection sort and insertion sort) and a variation of one of them (shellsort). We also consider two algorithms for uniformly shuffling an array. We conclude with an application of sorting to computing the convex hull via the Graham scan algorithm....
Reading
6 个视频 (总计 63 分钟), 1 个阅读材料, 1 个测验
Video6 个视频
Selection Sort6分钟
Insertion Sort9分钟
Shellsort10分钟
Shuffling7分钟
Convex Hull13分钟
Reading1 个阅读材料
Lecture Slides
Quiz1 个练习
Interview Questions: Elementary Sorts (ungraded)
3
完成时间(小时)
完成时间为 6 小时

Mergesort

We study the mergesort algorithm and show that it guarantees to sort any array of n items with at most n lg n compares. We also consider a nonrecursive, bottom-up version. We prove that any compare-based sorting algorithm must make at least n lg n compares in the worst case. We discuss using different orderings for the objects that we are sorting and the related concept of stability....
Reading
5 个视频 (总计 49 分钟), 2 个阅读材料, 2 个测验
Video5 个视频
Mergesort23分钟
Bottom-up Mergesort3分钟
Sorting Complexity9分钟
Comparators6分钟
Stability5分钟
Reading2 个阅读材料
Overview
Lecture Slides
Quiz1 个练习
Interview Questions: Mergesort (ungraded)
完成时间(小时)
完成时间为 1 小时

Quicksort

We introduce and implement the randomized quicksort algorithm and analyze its performance. We also consider randomized quickselect, a quicksort variant which finds the kth smallest item in linear time. Finally, we consider 3-way quicksort, a variant of quicksort that works especially well in the presence of duplicate keys....
Reading
4 个视频 (总计 50 分钟), 1 个阅读材料, 1 个测验
Video4 个视频
Quicksort19分钟
Selection7分钟
Duplicate Keys11分钟
System Sorts11分钟
Reading1 个阅读材料
Lecture Slides
Quiz1 个练习
Interview Questions: Quicksort (ungraded)
4
完成时间(小时)
完成时间为 6 小时

Priority Queues

We introduce the priority queue data type and an efficient implementation using the binary heap data structure. This implementation also leads to an efficient sorting algorithm known as heapsort. We conclude with an applications of priority queues where we simulate the motion of n particles subject to the laws of elastic collision. ...
Reading
4 个视频 (总计 74 分钟), 2 个阅读材料, 2 个测验
Video4 个视频
Binary Heaps23分钟
Heapsort14分钟
Event-Driven Simulation (optional)22分钟
Reading2 个阅读材料
Overview10分钟
Lecture Slides
Quiz1 个练习
Interview Questions: Priority Queues (ungraded)
完成时间(小时)
完成时间为 1 小时

Elementary Symbol Tables

We define an API for symbol tables (also known as associative arrays, maps, or dictionaries) and describe two elementary implementations using a sorted array (binary search) and an unordered list (sequential search). When the keys are Comparable, we define an extended API that includes the additional methods min, max floor, ceiling, rank, and select. To develop an efficient implementation of this API, we study the binary search tree data structure and analyze its performance....
Reading
6 个视频 (总计 77 分钟), 1 个阅读材料, 1 个测验
Video6 个视频
Elementary Implementations9分钟
Ordered Operations6分钟
Binary Search Trees19分钟
Ordered Operations in BSTs10分钟
Deletion in BSTs9分钟
Reading1 个阅读材料
Lecture Slides
Quiz1 个练习
Interview Questions: Elementary Symbol Tables (ungraded)8分钟

讲师

Avatar

Kevin Wayne

Senior Lecturer
Computer Science
Avatar

Robert Sedgewick

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

关于 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....

常见问题

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  • 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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