Algorithms: Final Exam Review

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Related lectures (20)

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Graph Algorithms II: Traversal and Paths

Explores graph traversal methods, spanning trees, and shortest paths using BFS and DFS.

Graphs: Properties and Representations

Covers graph properties, representations, and traversal algorithms using BFS and DFS.

Algorithms Exam Preparation

Offers a recap before the Algorithms exam, covering problem-solving strategies and algorithm implementation with sample problems.

Algorithmic Paradigms for Dynamic Graph Problems

Covers algorithmic paradigms for dynamic graph problems, including dynamic connectivity, expander decomposition, and local clustering, breaking barriers in k-vertex connectivity problems.

Introduction to Algorithms: Basics and Importance

Covers the basics of algorithms, the importance of studying them, data structures, and the impact of algorithms on various fields.

Binary Search Trees: Implementation and Operations

Covers the implementation and operations of basic data structures like stacks, queues, and linked lists, and introduces binary search trees.

Algorithms in Computer Science: Search and Sort Techniques

Provides an overview of essential search and sort algorithms in computer science.

Data Structures: Stacks, Queues, Linked Lists

Covers stacks, queues, linked lists, and binary search trees in data structures.

Optimal Binary Search Trees

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

Minimum Spanning Trees: Prim's Algorithm

Explores Prim's algorithm for minimum spanning trees and introduces the Traveling Salesman Problem.