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Best of All-Time Online Course

Divide and Conquer, Sorting and Searching, and Randomized Algorithms

Stanford University via Coursera

Overview

The primary topics in this part of the specialization are: asymptotic ("Big-oh") notation, sorting and searching, divide and conquer (master method, integer and matrix multiplication, closest pair), and randomized algorithms (QuickSort, contraction algorithm for min cuts).

Syllabus

Week 1
-Introduction; "big-oh" notation and asymptotic analysis.

Week 2
-Divide-and-conquer basics; the master method for analyzing divide and conquer algorithms.

Week 3
-The QuickSort algorithm and its analysis; probability review.

Week 4
-
Linear-time selection; graphs, cuts, and the contraction algorithm.

Taught by

Tim Roughgarden

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Reviews

4.7 rating, based on 67 reviews

Start your review of Divide and Conquer, Sorting and Searching, and Randomized Algorithms

  • Dhawal Shah completed this course, spending 12 hours a week on it and found the course difficulty to be medium.

    This course helped me get a job. Before doing this course, I had trouble clearing technical interviews. Infact, I couldn't even clear the phone interviews. "Algorithms: Design and Analysis, Part 1" was instrumental in clearing my first technical interview...
  • Henrik Warne completed this course, spending 10 hours a week on it and found the course difficulty to be medium.

    I took courses on algorithms and data structures when I went to university, and I really enjoyed both of them. Since then I have been working as a software developer for more than 20 years, so I thought it would be interesting with a refresher. I am...
  • Martin Rožnovják

    Martin Rožnovják completed this course, spending 8 hours a week on it and found the course difficulty to be hard.

    This was my very first course of algorithms, I had had some experience with programming before. The course was moderately challenging - I would say right at my limits but not overwhelming thus making the most out of its content - I wish I would learn...
  • Tian Qiu completed this course, spending 6 hours a week on it and found the course difficulty to be hard.

    This a good intro to algorithms course for those who already have some exposure to programming. The aim of the course is to introduce some classic algorithms and show us the toolbox of algorithms design and analysis by giving very detailed analysis on...
  • Wei En

    Wei En completed this course, spending 4 hours a week on it and found the course difficulty to be medium.

    Professor Roughgarden has done a great job in explaining the content. I've finally understood what big-O notation, etc. means, after taking this course. The lack of interactive visuals (which I find to be necessary for studying how an algorithm works) may bother you.

    The exercises are quite well done and provide a few challenging questions. Additionally, there are theory problems in the course pages which are optional and gets students to think creatively.

    In general, this is a great introduction to algorithms, if you're not particularly bothered by the lack of interactive visuals.
  • Shubham Agarwal completed this course, spending 7 hours a week on it and found the course difficulty to be medium.

    It is one of the must course one should do to achieve expertise in Data Structure and Algorithms. The instructor Tim Roughgarden, one of the best instructor i have ever seen. The methodology and material is awesome. And i will advise to complete all the assignments to get the best of the course.
  • square-B

    square-B completed this course and found the course difficulty to be hard.

    I thought this was a great learning experience. I would certainly recommend Coursera and this class specifically, to anyone. Be prepared as this course will take up A LOT of your time and it can be VERY challenging. Having said that, if you put in the work and tough it out, you will learn a lot. I know I did.
  • Jiting Tian completed this course, spending 12 hours a week on it and found the course difficulty to be hard.

    This is an introductory course on the principles of computational algorithms, but, it's very hard. The related mathematics is challenging and the concepts are difficult to understand. However, the teacher has cleverly cut the materials into small pieces and provide them in a gradual and clear way, so students can master the materials finally if they have taken great efforts to study it.
  • Shubham Agarwal

    Shubham Agarwal completed this course.

    Great course. Worth spending time. Not only videos by Tim are awesome but also the programming assignment and problem sets. If properly and seriously done, can improve your algorithmic skill to a great extent in just one and half month.
  • Anna K

    Anna K completed this course, spending 2 hours a week on it and found the course difficulty to be medium.

    This course requires too much time to watch the videos.. Several hours of videos per 1 week, and the lecturer gets repetitive and some information is not necessary.. Sorry, did not fly with me...
  • Anonymous

    Anonymous completed this course.

    The course is very good, but it is focused on providing proofs of correctness and running time of algorithms, and so it is more theoretical than applied. Still, I learned a lot about algorithms in this course!
  • Profile image for Luiz Cunha
    Luiz Cunha

    Luiz Cunha completed this course, spending 10 hours a week on it and found the course difficulty to be hard.

    In my top 3 MOOC.
    Great content and delivery by Prof. Roughgarden on a rather dry topic.
    The videos are great quality.
    The assignments are very challenging but interesting.
    I just wished this MOOC would be longer
  • Anonymous

    Anonymous completed this course.

    Hard but worth every penny. Got to learn more from this course than every other algorithms courses i've taken. Don't expect to be spoonfed, and expect to do background reading. Wonderful!
  • Eli Bendersky

    Eli Bendersky completed this course and found the course difficulty to be very easy.

    The teacher is pretty good – I actually enjoyed watching the lectures and wasn't bored, which is unusual with me when it comes to lectures. I really liked the "optional" videos (watched them all). Not sure whether they would have been taught in the real...
  • Jeffrey Yun (Haoyu) completed this course, spending 8 hours a week on it and found the course difficulty to be medium.

    I took the Algorithms specialization during my winter break of my 2nd year as an Computer Science student in college, after taking introductory data structures + algorithms classes and developing a competitive programming hobby.

    Tim Roughgarden is an amazing instructor, and the Algorithms specialization is one of my all-time favorite MOOCs.

  • Anonymous

    Anonymous completed this course.

    Very much worth the time. I especially enjoyed the programming assignments as they made very clear the dramatic impact algorithm improvements can have when operating on large data sets. The professor made video lectures more engaging than I thought would be possible. I just finished Part 1 and will be taking Part 2 when it starts.
  • Anonymous

    Anonymous completed this course.

    Landed my first job all thanks to this wonderful course. Programming assignments were a little tough at times but nothing that can't be handled. Probably one of the best online courses available for learning algorithms and data structures.
  • Anonymous

    Anonymous completed this course.

    I took this course in Summer 2012 (2nd iteration). Lectures were great. Everything was on time. Programming assignments and problem sets were very insightful. Definitely recommend this course.
  • Akamal8 completed this course, spending 9 hours a week on it and found the course difficulty to be medium.

    Very brillian course. It developed the way I think of algorithms and approach problems. I recommend it for any software engineering student.
  • Anonymous

    Anonymous completed this course.

    Excellent course, great teacher and challenging assignments fun to do. I definitely enjoyed the course and learned a lot.

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