Lectures related to Algorithms Exam Preparation

Algorithms: Final Exam Review

Provides a detailed review of the 2016 final exam, covering various algorithmic problems.

Complexity & Induction: Algorithms & Proofs

Covers worst-case complexity, algorithms, and proofs including mathematical induction and recursion.

Recursion and Binary Search

Introduces recursion and binary search algorithms for efficient problem-solving.

Data Structures: Stacks, Queues, Linked Lists

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

Dynamic Programming: Palindromic Subsequences

Explores dynamic programming for palindromic subsequences, merging binary search trees, and finding the median of two sorted arrays.

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.

Optimal Binary Search Trees

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

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.

Optimal Binary Search Tree

Explores optimal binary search trees to minimize expected search cost efficiently.

Algorithm Analysis: Growth, Search, and Logarithm

Explores algorithm growth, search complexities, and logarithmic properties in depth, with practical exercises included.

Binary Search Trees Operations

Explains binary search tree operations, focusing on insertion, search, and list conversion, with an emphasis on formal verification and debugging.

Algorithms in Computer Science: Search and Sort Techniques

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

Binary Search Trees: Operations and Implementations

Explores binary search trees, covering operations, implementations, and real-world applications involving train tracks.

Complexity & Induction: Algorithms & Proofs

Explores worst-case complexity, mathematical induction, and algorithms like binary search and insertion sort.

Binary Search: Basics and Execution

Explores binary search fundamentals, efficiency, and temporal complexity in algorithmic searching.

Graph Algorithms II: Traversal and Paths

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

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 Algorithm

Explains the binary search algorithm using two pointers to efficiently search a sorted list.

Introduction to Logarithm

Covers the introduction to logarithms, algorithmic notations, and analysis of algorithm travel times.

Binary Search: Implementation and Example

Covers the binary search algorithm and provides a step-by-step example.