23 episodes

This course teaches techniques for the design and analysis of efficient algorithms, emphasizing methods useful in practice. Topics covered include: sorting; search trees, heaps, and hashing; divide-and-conquer; dynamic programming; amortized analysis; graph algorithms; shortest paths; network flow; computational geometry; number-theoretic algorithms; polynomial and matrix calculations; caching; and parallel computing.

Introduction to Algorithms (2005) MIT

    • Technology
    • 4.0, 142 Ratings

This course teaches techniques for the design and analysis of efficient algorithms, emphasizing methods useful in practice. Topics covered include: sorting; search trees, heaps, and hashing; divide-and-conquer; dynamic programming; amortized analysis; graph algorithms; shortest paths; network flow; computational geometry; number-theoretic algorithms; polynomial and matrix calculations; caching; and parallel computing.

    • video
    Lecture 01: Administrivia/Introduction/Analysis of Algorithms, Insertion Sort, Mergesort

    Lecture 01: Administrivia/Introduction/Analysis of Algorithms, Insertion Sort, Mergesort

    • 1 hr 20 min
    • video
    Lecture 02: Asymptotic Notation/Recurrences/Substitution, Master Method

    Lecture 02: Asymptotic Notation/Recurrences/Substitution, Master Method

    • 1 hr 10 min
    • video
    Lecture 03: Divide-and-Conquer: Strassen, Fibonacci, Polynomial Multiplication

    Lecture 03: Divide-and-Conquer: Strassen, Fibonacci, Polynomial Multiplication

    • 1 hr 8 min
    • video
    Lecture 04: Quicksort, Randomized Algorithms

    Lecture 04: Quicksort, Randomized Algorithms

    • 1 hr 20 min
    • video
    Lecture 05: Linear-time Sorting: Lower Bounds, Counting Sort, Radix Sort

    Lecture 05: Linear-time Sorting: Lower Bounds, Counting Sort, Radix Sort

    • 1 hr 16 min
    • video
    Lecture 06: Order Statistics, Median

    Lecture 06: Order Statistics, Median

    • 1 hr 8 min

Customer Reviews

4.0 out of 5
142 Ratings

142 Ratings

ss1271 ,

Good for self-study/review

One more thing: if you keen to start straight away, in Lecture 01, just jump to 17:11 which will lead you to the real content of the course. The first 17 minutes are used for the lecturer to talk about the course credit and exam etc.

Mani Batra ,

Brilliant!!

Feels great listening to some of the most talented profferers on the planet. Making algorithms beautiful !!

mynameissomeone ,

Great series!

Well if it had 20 and 21 would be better! Really helped me out about teta(n) .

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