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Princeton University

Analysis of Algorithms

Princeton University via Coursera


This course teaches a calculus that enables precise quantitative predictions of large combinatorial structures. In addition, this course covers generating functions and real asymptotics and then introduces the symbolic method in the context of applications in the analysis of algorithms and basic structures such as permutations, trees, strings, words, and mappings.

All the features of this course are available for free. It does not offer a certificate upon completion.

Taught by

Robert Sedgewick


4.0 rating, based on 6 Class Central reviews

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  • Mauro Lacy completed this course, spending 7 hours a week on it and found the course difficulty to be very hard.

    Difficult, and mathematically demanding.
    Self-paced and ungraded, due to both, the inherent difficulty of the subject, and the difficulty of grading the exercises.
  • Anonymous
    Some mistakes. Master theorem a basic tool was wrong. Proofs are not well laid out. The mooc is not self sufficient, but needs the book to be useful.

    I would not recommend this course though the instructor is extremely knowledgeable. I liked his other course on algorithms in Coursera a lot.
  • Anonymous
    I haven't completed this course completely tbh. But the materials and notes were great , author goes into good detail in some topics.

    Might be a bit hard mathematically for those who suck.

    Author uses Java
  • Andrei Razvan Maresu

    Andrei Razvan Maresu completed this course.

  • Juliano Ignacio completed this course.

  • Christopher Pitt

    Christopher Pitt completed this course.

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