Design and Analysis of Algorithms | Electrical Engineering and Computer Science | MIT OpenCourseWare

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Spring 2015

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Lecture Videos

Lecture 1: Overview, Interval Scheduling

Lecture 2: Divide & Conquer: Convex Hull, Median Finding

Lecture 3: Divide & Conquer: FFT

Lecture 4: Divide & Conquer: van Emde Boas Trees

Lecture 5: Amortization: Amortized Analysis

Lecture 6: Randomization: Matrix Multiply, Quicksort

Lecture 7: Randomization: Skip Lists

Lecture 8: Randomization: Universal & Perfect Hashing

Lecture 9: Augmentation: Range Trees

Lecture 10: Dynamic Programming: Advanced DP

Lecture 11: Dynamic Programming: All-Pairs Shortest Paths

Lecture 12: Greedy Algorithms: Minimum Spanning Tree

Lecture 13: Incremental Improvement: Max Flow, Min Cut

Lecture 14: Incremental Improvement: Matching

Lecture 15: Linear Programming: LP, reductions, Simplex

Lecture 16: Complexity: P, NP, NP-completeness, Reductions

Lecture 17: Complexity: Approximation Algorithms

Lecture 18: Complexity: Fixed-Parameter Algorithms

Lecture 19: Synchronous Distributed Algorithms: Symmetry-Breaking. Shortest-Paths Spanning Trees

Lecture 20: Asynchronous Distributed Algorithms: Shortest-Paths Spanning Trees

Lecture 21: Cryptography: Hash Functions

Lecture 22: Cryptography: Encryption

Lecture 23: Cache-Oblivious Algorithms: Medians & Matrices

Lecture 24: Cache-Oblivious Algorithms: Searching & Sorting

Course Info

Instructors

Departments

As Taught In

Spring 2015

Level

Topics

Learning Resource Types

Lecture Videos

Problem-solving Videos

Exams with Solutions

Lecture Notes

Instructor Insights

Problem Sets

Problem Set Solutions

Download Course