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約32時間で修了

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

英語

字幕:英語, 韓国語

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Data StructurePriority QueueAlgorithmsJava Programming

100%オンライン

自分のスケジュールですぐに学習を始めてください。

柔軟性のある期限

スケジュールに従って期限をリセットします。

中級レベル

約32時間で修了

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

英語

字幕:英語, 韓国語

シラバス - 本コースの学習内容

1
10分で修了

Course Introduction

Welcome to Algorithms, Part I.

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1件のビデオ (合計9分), 2 readings
1件のビデオ
2件の学習用教材
Welcome to Algorithms, Part I1 分
Lecture Slides
6時間で修了

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.

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5件のビデオ (合計51分), 2 readings, 2 quizzes
5件のビデオ
Quick Find10 分
Quick Union7 分
Quick-Union Improvements13 分
Union−Find Applications9 分
2件の学習用教材
Overview1 分
Lecture Slides
1の練習問題
Interview Questions: Union–Find (ungraded)
1時間で修了

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.

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6件のビデオ (合計66分), 1 reading, 1 quiz
6件のビデオ
Observations10 分
Mathematical Models12 分
Order-of-Growth Classifications14 分
Theory of Algorithms11 分
Memory8 分
1件の学習用教材
Lecture Slides
1の練習問題
Interview Questions: Analysis of Algorithms (ungraded)
2
6時間で修了

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.

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6件のビデオ (合計61分), 2 readings, 2 quizzes
6件のビデオ
Stacks16 分
Resizing Arrays9 分
Queues4 分
Generics9 分
Iterators7 分
Stack and Queue Applications (optional)13 分
2件の学習用教材
Overview1 分
Lecture Slides
1の練習問題
Interview Questions: Stacks and Queues (ungraded)
1時間で修了

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.

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6件のビデオ (合計63分), 1 reading, 1 quiz
6件のビデオ
Selection Sort6 分
Insertion Sort9 分
Shellsort10 分
Shuffling7 分
Convex Hull13 分
1件の学習用教材
Lecture Slides
1の練習問題
Interview Questions: Elementary Sorts (ungraded)
3
6時間で修了

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.

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5件のビデオ (合計49分), 2 readings, 2 quizzes
5件のビデオ
Mergesort23 分
Bottom-up Mergesort3 分
Sorting Complexity9 分
Comparators6 分
Stability5 分
2件の学習用教材
Overview
Lecture Slides
1の練習問題
Interview Questions: Mergesort (ungraded)
1時間で修了

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.

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4件のビデオ (合計50分), 1 reading, 1 quiz
4件のビデオ
Quicksort19 分
Selection7 分
Duplicate Keys11 分
System Sorts11 分
1件の学習用教材
Lecture Slides
1の練習問題
Interview Questions: Quicksort (ungraded)
4
6時間で修了

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.

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4件のビデオ (合計74分), 2 readings, 2 quizzes
4件のビデオ
Binary Heaps23 分
Heapsort14 分
Event-Driven Simulation (optional)22 分
2件の学習用教材
Overview10 分
Lecture Slides
1の練習問題
Interview Questions: Priority Queues (ungraded)
1時間で修了

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.

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6件のビデオ (合計77分), 1 reading, 1 quiz
6件のビデオ
Elementary Implementations9 分
Ordered Operations6 分
Binary Search Trees19 分
Ordered Operations in BSTs10 分
Deletion in BSTs9 分
1件の学習用教材
Lecture Slides
1の練習問題
Interview Questions: Elementary Symbol Tables (ungraded)8 分
4.9
1041件のレビューChevron Right

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15%

昇給や昇進につながった

Algorithms, Part I からの人気レビュー

by 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.

by 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!

講師

Avatar

Kevin Wayne

Phillip Y. Goldman '86 Senior Lecturer
Computer Science
Avatar

Robert Sedgewick

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

プリンストン大学(Princeton University)について

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....

よくある質問

  • 修了証に登録すると、すべてのビデオ、テスト、およびプログラミング課題(該当する場合)にアクセスできます。ピアレビュー課題は、セッションが開始してからのみ、提出およびレビューできます。購入せずにコースを検討することを選択する場合、特定の課題にアクセスすることはできません。

  • 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.

さらに質問がある場合は、受講者向けヘルプセンターにアクセスしてください。