In this lecture, Professor Demaine continues with cache-oblivious algorithms, including their applications in searching and sorting.

Lecture 24: Cache-Oblivious Algorithms: Searching & Sorting

In this lecture, Professor Demaine introduces cache-oblivious algorithms.

Lecture 23: Cache-Oblivious Algorithms: Medians & Matrices

In this recitation, problems related to cryptography are discussed.

Recitation 11: Cryptography: More Primitives

In this lecture, Professor Devadas continues with cryptography, introducing encryption methods.

Lecture 22: Cryptography: Encryption

In this lecture, Professor Devadas covers the basics of cryptography, including desirable properties of cryptographic functions, and their applications to security.

Lecture 21: Cryptography: Hash Functions

In this recitation, problems related to distributed algorithms are discussed.

Recitation 10: Distributed Algorithms

In this lecture, Professor Lynch introduces asynchronous distributed algorithms.

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

In this lecture, Professor Lynch introduces synchronous distributed algorithms.

Lecture 19: Synchronous Distributed Algorithms: Symmetry-Breaking

In this recitation, problems related to approximation algorithms are discussed, namely the traveling salesman problem.

Recitation 9: Approximation Algorithms: Traveling Salesman Problem

In this lecture, Professor Demaine tackles NP-hard problems using fixed-parameter algorithms.

Lecture 18: Complexity: Fixed-Parameter Algorithms

Design and Analysis of Algorithms (2015)

In this lecture, Professor Devadas introduces the concept of dynamic programming.

Lecture 10: Dynamic Programming: Advanced DP

In this lecture, Professor Demaine covers different algorithmic solutions for the All-Pairs Shortest Paths problem.

Lecture 11: Dynamic Programming: All-Pairs Shortest Paths

In this recitation, problems related to dynamic programming are discussed.

Recitation 5: Dynamic Programming

In this video, the instructor discusses assessment strategies used in the course and the challenge of assessing students' abilities to apply algorithms in new and creative ways.

On the Challenge of Assessing Students' Abiliites to Apply Algorithms in New and Creative Ways 

In this lecture, Professor Demaine introduces greedy algorithms, which make locally-best choices without regards to the future.

Lecture 12: Greedy Algorithms: Minimum Spanning Tree

In this lecture, Professor Demaine reviews hashing in the context of randomized algorithms.

Lecture 8: Randomization: Universal & Perfect Hashing

In this lecture, Professor Demaine covers the augmentation of data structures, updating common structures to store additional information.

Lecture 9: Augmentation: Range Trees

In this video, the instructor suggests that one of the best ways to engage learners with the content is to communicate one's own excitement about algorithms.

Engaging Students

In this lecture, Professor Devadas introduces approximation algorithms in the context of NP-hard problems.

Lecture 17: Complexity: Approximation Algorithms

In this recitation, problems related to NP-Completeness are discussed.

Recitation 8: NP-Complete Problems

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