Algorithms, Part II

• Wann erhalte ich Zugang zu den Vorträgen und Aufgaben?

  Der Zugang zu Vorlesungen und Aufgaben hängt von der Art Ihrer Anmeldung ab. Wenn Sie einen Kurs im Gastmodus belegen, können Sie die meisten Kursmaterialien kostenlos einsehen. Um auf benotete Aufgaben zuzugreifen und ein Zertifikat zu erhalten, müssen Sie während oder nach Ihrer Gastphase das Zertifikat erwerben. Wenn Sie die Gastoption nicht sehen:

  • Der Kurs bietet möglicherweise keine Gastoption an. Sie können stattdessen eine kostenlose Testversion ausprobieren oder finanzielle Unterstützung beantragen.

  • Der Kurs kann stattdessen "Vollständiger Kurs ohne Zertifikat" anbieten. Mit dieser Option können Sie alle Kursmaterialien einsehen, die erforderlichen Aufgaben einreichen und eine Endnote erhalten. Dies bedeutet auch, dass Sie kein Zertifikat erwerben können.

• Wann erhalte ich Zugang zu den Vorträgen und Aufgaben?

  Once you enroll, you’ll have access to all videos and programming assignments.

• Do I need to pay for this course?

  No. All features of this course are available for free.

• Can I earn a certificate in this course?

  No. As per Princeton University policy, no certificates, credentials, or reports are awarded in connection with this course.

• I have no familiarity with Java programming. Can I still take 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.

• Which algorithms and data structures are covered in this course?

  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.

• What kinds of assessments are available in this course?

  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.

• I am/was not a Computer Science major. Is this course for me?

  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.

• How does this course differ from Design and Analysis of Algorithms?

  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 Learner Help Center.