Course

CS-250: Algorithms I

Lectures in this course (101)

Explores matrix chain multiplication to minimize scalar multiplications efficiently.

Explores dynamic programming with a focus on optimizing Matrix Chain Multiplication.

Explores dynamic programming for matrix chain multiplication and introduces the concept of the longest common subsequence.

Explores dynamic programming with a focus on matrix-chain multiplication and the importance of optimal substructure.

Explores Longest Common Subsequence and Optimal Binary Search Trees, discussing algorithms and probabilities for efficient search structures.

Explores optimal binary search trees to minimize search cost using dynamic programming and recursive formulations.

Explains Optimal Binary Search Trees using dynamic programming and covers a midterm exam from 2016.

Covers elementary graph algorithms, a midterm exam on algorithmic problem-solving, and distance measurement between strings.

Focuses on designing a data structure for fast interval queries on a complete binary tree.

Introduces elementary graph algorithms, focusing on Breadth-First Search and Depth-First Search.

Explores the Depth-First Search algorithm, analyzing edge classifications and key theorems in graph exploration.

Explores depth-first search, breadth-first search, graph representation, and topological sorting in graphs.

Explores topological sort, acyclic graphs, Strongly Connected Components, magic algorithm, component graph, flow networks, and their applications.

Introduces Strongly Connected Components and Flow Networks, discussing algorithms and applications.

Introduces the Ford-Fulkerson Method to find the maximum flow in a network.

Explores the Ford-Fulkerson method for finding max flow and min cut in a network.

Explores the Max-flow Min-cut theorem, integral capacities, Ford-Fulkerson method, bipartite matching, and edge-disjoint paths.

Explores the Ford-Fulkerson method, max-flow, applications of max-flow, and the disjoint-set data structure.

Covers the implementation and analysis of disjoint sets data structure and introduces the concept of minimum spanning trees.

Covers minimum spanning trees, disjoint-set data structures, union methods, and Prim's algorithm for finding minimum spanning trees.