About this Course
최근 조회 115,092

100% 온라인

지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.

유동적 마감일

일정에 따라 마감일을 재설정합니다.

중급 단계

완료하는 데 약 34시간 필요

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

영어

자막: 영어, 한국어

귀하가 습득할 기술

GraphsData StructureAlgorithmsData Compression

100% 온라인

지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.

유동적 마감일

일정에 따라 마감일을 재설정합니다.

중급 단계

완료하는 데 약 34시간 필요

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

영어

자막: 영어, 한국어

강의 계획 - 이 강좌에서 배울 내용

1
완료하는 데 10분 필요

Introduction

1개 동영상 (총 9분), 2 readings
1개의 동영상
2개의 읽기 자료
Welcome to Algorithms, Part II1m
Lecture Slides
완료하는 데 2시간 필요

Undirected Graphs

6개 동영상 (총 98분), 2 readings, 1 quiz
6개의 동영상
Graph API14m
Depth-First Search26m
Breadth-First Search13m
Connected Components18m
Graph Challenges14m
2개의 읽기 자료
Overview1m
Lecture Slides
1개 연습문제
Interview Questions: Undirected Graphs (ungraded)6m
완료하는 데 9시간 필요

Directed Graphs

5개 동영상 (총 68분), 1 reading, 2 quizzes
5개의 동영상
Digraph API4m
Digraph Search20m
Topological Sort 12m
Strong Components20m
1개의 읽기 자료
Lecture Slides
1개 연습문제
Interview Questions: Directed Graphs (ungraded)6m
2
완료하는 데 2시간 필요

Minimum Spanning Trees

6개 동영상 (총 85분), 2 readings, 1 quiz
6개의 동영상
Greedy Algorithm12m
Edge-Weighted Graph API11m
Kruskal's Algorithm12m
Prim's Algorithm33m
MST Context10m
2개의 읽기 자료
Overview1m
Lecture Slides
1개 연습문제
Interview Questions: Minimum Spanning Trees (ungraded)6m
완료하는 데 10시간 필요

Shortest Paths

5개 동영상 (총 85분), 1 reading, 2 quizzes
5개의 동영상
Shortest Path Properties14m
Dijkstra's Algorithm18m
Edge-Weighted DAGs19m
Negative Weights21m
1개의 읽기 자료
Lecture Slides
1개 연습문제
Interview Questions: Shortest Paths (ungraded)6m
3
완료하는 데 7시간 필요

Maximum Flow and Minimum Cut

6개 동영상 (총 72분), 2 readings, 2 quizzes
6개의 동영상
Ford–Fulkerson Algorithm6m
Maxflow–Mincut Theorem9m
Running Time Analysis8m
Java Implementation14m
Maxflow Applications22m
2개의 읽기 자료
Overview
Lecture Slides
1개 연습문제
Interview Questions: Maximum Flow (ungraded)6m
완료하는 데 2시간 필요

Radix Sorts

6개 동영상 (총 85분), 1 reading, 1 quiz
6개의 동영상
Key-Indexed Counting12m
LSD Radix Sort15m
MSD Radix Sort13m
3-way Radix Quicksort7m
Suffix Arrays19m
1개의 읽기 자료
Lecture Slides
1개 연습문제
Interview Questions: Radix Sorts (ungraded)6m
4
완료하는 데 2시간 필요

Tries

3개 동영상 (총 75분), 2 readings, 1 quiz
3개의 동영상
Ternary Search Tries22m
Character-Based Operations20m
2개의 읽기 자료
Overview10m
Lecture Slides
1개 연습문제
Interview Questions: Tries (ungraded)6m
완료하는 데 10시간 필요

Substring Search

5개 동영상 (총 75분), 1 reading, 2 quizzes
5개의 동영상
Brute-Force Substring Search10m
Knuth–Morris–Pratt33m
Boyer–Moore8m
Rabin–Karp16m
1개의 읽기 자료
Lecture Slides10m
1개 연습문제
Interview Questions: Substring Search (ungraded)6m
5.0
136개의 리뷰Chevron Right

15%

이 강좌를 수료한 후 새로운 경력 시작하기

20%

이 강좌를 통해 확실한 경력상 이점 얻기

13%

급여 인상 또는 승진하기

Algorithms, Part II의 최상위 리뷰

대학: IOJan 21st 2018

Pretty challenging course, but very good. Having a book is a must (at least it was for me), video lectures complement book nicely, and some topics are explained better in the Algorithms, 4th ed. book.

대학: AKApr 17th 2019

Amazing course! Loved the theory and exercises! Just a note for others: Its part 1 had almost no dependency on book, but this part 2 has some dependency (e.g. chapter on Graph) on book as well.

강사

Avatar

Robert Sedgewick

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

Kevin Wayne

Phillip Y. Goldman '86 Senior Lecturer
Computer Science

프린스턴 대학교 정보

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....

자주 묻는 질문

  • 강좌에 등록하면 바로 모든 비디오, 테스트 및 프로그래밍 과제(해당하는 경우)에 접근할 수 있습니다. 상호 첨삭 과제는 이 세션이 시작된 경우에만 제출하고 검토할 수 있습니다. 강좌를 구매하지 않고 살펴보기만 하면 특정 과제에 접근하지 못할 수 있습니다.

  • 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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