Über diesen Kurs
116,598 kürzliche Aufrufe

100 % online

Beginnen Sie sofort und lernen Sie in Ihrem eigenen Tempo.

Flexible Fristen

Setzen Sie Fristen gemäß Ihrem Zeitplan zurück.

Stufe „Mittel“

Ca. 34 Stunden zum Abschließen

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

Englisch

Untertitel: Englisch, Koreanisch

Kompetenzen, die Sie erwerben

GraphsData StructureAlgorithmsData Compression

100 % online

Beginnen Sie sofort und lernen Sie in Ihrem eigenen Tempo.

Flexible Fristen

Setzen Sie Fristen gemäß Ihrem Zeitplan zurück.

Stufe „Mittel“

Ca. 34 Stunden zum Abschließen

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

Englisch

Untertitel: Englisch, Koreanisch

Kursteilnehmer, die sich für Course entscheiden, sind

  • Software Engineers
  • Machine Learning Engineers
  • Data Scientists
  • Data Engineers
  • Systems Engineers

Lehrplan - Was Sie in diesem Kurs lernen werden

Woche
1
10 Minuten zum Abschließen

Introduction

1 Videos (Gesamt 9 min), 2 Lektüren
1 Videos
2 Lektüren
Welcome to Algorithms, Part II1m
Lecture Slides
2 Stunden zum Abschließen

Undirected Graphs

6 Videos (Gesamt 98 min), 2 Lektüren, 1 Quiz
6 Videos
Graph API14m
Depth-First Search26m
Breadth-First Search13m
Connected Components18m
Graph Challenges14m
2 Lektüren
Overview1m
Lecture Slides
1 praktische Übungen
Interview Questions: Undirected Graphs (ungraded)6m
9 Stunden zum Abschließen

Directed Graphs

5 Videos (Gesamt 68 min), 1 Lektüre, 2 Quiz
5 Videos
Digraph API4m
Digraph Search20m
Topological Sort 12m
Strong Components20m
1 Lektüren
Lecture Slides
1 praktische Übungen
Interview Questions: Directed Graphs (ungraded)6m
Woche
2
2 Stunden zum Abschließen

Minimum Spanning Trees

6 Videos (Gesamt 85 min), 2 Lektüren, 1 Quiz
6 Videos
Greedy Algorithm12m
Edge-Weighted Graph API11m
Kruskal's Algorithm12m
Prim's Algorithm33m
MST Context10m
2 Lektüren
Overview1m
Lecture Slides
1 praktische Übungen
Interview Questions: Minimum Spanning Trees (ungraded)6m
10 Stunden zum Abschließen

Shortest Paths

5 Videos (Gesamt 85 min), 1 Lektüre, 2 Quiz
5 Videos
Shortest Path Properties14m
Dijkstra's Algorithm18m
Edge-Weighted DAGs19m
Negative Weights21m
1 Lektüren
Lecture Slides
1 praktische Übungen
Interview Questions: Shortest Paths (ungraded)6m
Woche
3
7 Stunden zum Abschließen

Maximum Flow and Minimum Cut

6 Videos (Gesamt 72 min), 2 Lektüren, 2 Quiz
6 Videos
Ford–Fulkerson Algorithm6m
Maxflow–Mincut Theorem9m
Running Time Analysis8m
Java Implementation14m
Maxflow Applications22m
2 Lektüren
Overview
Lecture Slides
1 praktische Übungen
Interview Questions: Maximum Flow (ungraded)6m
2 Stunden zum Abschließen

Radix Sorts

6 Videos (Gesamt 85 min), 1 Lektüre, 1 Quiz
6 Videos
Key-Indexed Counting12m
LSD Radix Sort15m
MSD Radix Sort13m
3-way Radix Quicksort7m
Suffix Arrays19m
1 Lektüren
Lecture Slides
1 praktische Übungen
Interview Questions: Radix Sorts (ungraded)6m
Woche
4
2 Stunden zum Abschließen

Tries

3 Videos (Gesamt 75 min), 2 Lektüren, 1 Quiz
3 Videos
Ternary Search Tries22m
Character-Based Operations20m
2 Lektüren
Overview10m
Lecture Slides
1 praktische Übungen
Interview Questions: Tries (ungraded)6m
10 Stunden zum Abschließen

Substring Search

5 Videos (Gesamt 75 min), 1 Lektüre, 2 Quiz
5 Videos
Brute-Force Substring Search10m
Knuth–Morris–Pratt33m
Boyer–Moore8m
Rabin–Karp16m
1 Lektüren
Lecture Slides10m
1 praktische Übungen
Interview Questions: Substring Search (ungraded)6m
5.0
136 BewertungenChevron Right

15%

nahm einen neuen Beruf nach Abschluss dieser Kurse auf

20%

ziehen Sie für Ihren Beruf greifbaren Nutzen aus diesem Kurs

13%

erhalten Sie eine Gehaltserhöhung oder Beförderung

Top-Bewertungen von Algorithms, Part II

von 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.

von 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.

Dozenten

Avatar

Robert Sedgewick

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

Kevin Wayne

Phillip Y. Goldman '86 Senior Lecturer
Computer Science

Über 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....

Häufig gestellte Fragen

  • Sobald Sie sich für ein Zertifikat angemeldet haben, haben Sie Zugriff auf alle Videos, Quizspiele und Programmieraufgaben (falls zutreffend). Aufgaben, die von anderen Kursteilnehmern bewertet werden, können erst dann eingereicht und überprüft werden, wenn Ihr Unterricht begonnen hat. Wenn Sie sich den Kurs anschauen möchten, ohne ihn zu kaufen, können Sie womöglich auf bestimmte Aufgaben nicht zugreifen.

  • 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.

Haben Sie weitere Fragen? Besuchen Sie das Hilfe-Center für Teiln..