課程信息
487,711 次近期查看

Learner Career Outcomes

33%

完成這些課程後已開始新的職業生涯

34%

通過此課程獲得實實在在的工作福利

17%

加薪或升職

100% 在線

立即開始,按照自己的計劃學習。

可靈活調整截止日期

根據您的日程表重置截止日期。

中級

完成時間大約為33 小時

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

英語(English)

字幕:英語(English), 韓語, 俄語(Russian)

您將獲得的技能

Data StructureAlgorithmsJava Programming

Learner Career Outcomes

33%

完成這些課程後已開始新的職業生涯

34%

通過此課程獲得實實在在的工作福利

17%

加薪或升職

100% 在線

立即開始,按照自己的計劃學習。

可靈活調整截止日期

根據您的日程表重置截止日期。

中級

完成時間大約為33 小時

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

英語(English)

字幕:英語(English), 韓語, 俄語(Russian)

教學大綱 - 您將從這門課程中學到什麼

1
完成時間為 10 分鐘

Course Introduction

1 個視頻 (總計 9 分鐘), 2 個閱讀材料
1 個視頻
2 個閱讀材料
Welcome to Algorithms, Part I1分鐘
Lecture Slides
完成時間為 9 小時

Union−Find

5 個視頻 (總計 51 分鐘), 2 個閱讀材料, 2 個測驗
5 個視頻
Quick Find10分鐘
Quick Union7分鐘
Quick-Union Improvements13分鐘
Union−Find Applications9分鐘
2 個閱讀材料
Overview1分鐘
Lecture Slides
1 個練習
Interview Questions: Union–Find (ungraded)
完成時間為 1 小時

Analysis of Algorithms

6 個視頻 (總計 66 分鐘), 1 個閱讀材料, 1 個測驗
6 個視頻
Observations10分鐘
Mathematical Models12分鐘
Order-of-Growth Classifications14分鐘
Theory of Algorithms11分鐘
Memory8分鐘
1 個閱讀材料
Lecture Slides
1 個練習
Interview Questions: Analysis of Algorithms (ungraded)
2
完成時間為 9 小時

Stacks and Queues

6 個視頻 (總計 61 分鐘), 2 個閱讀材料, 2 個測驗
6 個視頻
Stacks16分鐘
Resizing Arrays9分鐘
Queues4分鐘
Generics9分鐘
Iterators7分鐘
Stack and Queue Applications (optional)13分鐘
2 個閱讀材料
Overview1分鐘
Lecture Slides
1 個練習
Interview Questions: Stacks and Queues (ungraded)
完成時間為 1 小時

Elementary Sorts

6 個視頻 (總計 63 分鐘), 1 個閱讀材料, 1 個測驗
6 個視頻
Selection Sort6分鐘
Insertion Sort9分鐘
Shellsort10分鐘
Shuffling7分鐘
Convex Hull13分鐘
1 個閱讀材料
Lecture Slides
1 個練習
Interview Questions: Elementary Sorts (ungraded)
3
完成時間為 9 小時

Mergesort

5 個視頻 (總計 49 分鐘), 2 個閱讀材料, 2 個測驗
5 個視頻
Mergesort23分鐘
Bottom-up Mergesort3分鐘
Sorting Complexity9分鐘
Comparators6分鐘
Stability5分鐘
2 個閱讀材料
Overview
Lecture Slides
1 個練習
Interview Questions: Mergesort (ungraded)
完成時間為 1 小時

Quicksort

4 個視頻 (總計 50 分鐘), 1 個閱讀材料, 1 個測驗
4 個視頻
Quicksort19分鐘
Selection7分鐘
Duplicate Keys11分鐘
System Sorts11分鐘
1 個閱讀材料
Lecture Slides
1 個練習
Interview Questions: Quicksort (ungraded)
4
完成時間為 9 小時

Priority Queues

4 個視頻 (總計 74 分鐘), 2 個閱讀材料, 2 個測驗
4 個視頻
Binary Heaps23分鐘
Heapsort14分鐘
Event-Driven Simulation (optional)22分鐘
2 個閱讀材料
Overview10分鐘
Lecture Slides
1 個練習
Interview Questions: Priority Queues (ungraded)
完成時間為 1 小時

Elementary Symbol Tables

6 個視頻 (總計 77 分鐘), 1 個閱讀材料, 1 個測驗
6 個視頻
Elementary Implementations9分鐘
Ordered Operations6分鐘
Binary Search Trees19分鐘
Ordered Operations in BSTs10分鐘
Deletion in BSTs9分鐘
1 個閱讀材料
Lecture Slides
1 個練習
Interview Questions: Elementary Symbol Tables (ungraded)8分鐘
4.9
1182 條評論Chevron Right

來自算法,第一部分的熱門評論

創建者 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.

創建者 BJJun 3rd 2018

Good contents and the logic of the whole course structure is very clear for a novice like me. The weekly homework is also awesome. Would recommend to anyone who wants to learn about computer science.

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

關於 普林斯顿大学

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....

常見問題

  • 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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