xraxus/algorithms-and-data-structures

JavaScript Algorithms and Data Structures Solutions

This repository contains my solutions for exercises from the JavaScript Algorithms and Data Structures Masterclass course created by Colt Steele.

Course Overview

JavaScript Algorithms and Data Structures Masterclass offers comprehensive coverage of essential algorithms, data structures, and problem-solving techniques necessary for excelling in coding interviews and becoming a proficient developer. The course includes:

• Mastery of dozens of popular algorithms, including 6 sorting algorithms.
• Implementation of 10+ data structures from scratch.
• Enhancement of problem-solving skills.
• In-depth coverage of advanced topics such as Heaps, Graphs, and Dijkstra's Shortest Path Algorithm.

What You'll Learn

• How to ace difficult coding interviews.
• Analyzing code's time and space complexity using Big O notation.
• Recursion and its applications.
• Problem-solving approaches and patterns.
• Implementation of various searching and sorting algorithms.
• Creation of data structures like linked lists, trees, heaps, hash tables, and graphs.
• Traversal techniques for trees and graphs.
• Application of Dynamic Programming principles.

Course Structure

The course is divided into several sections, each focusing on specific topics:

1. Introduction: Overview of the curriculum and how to approach the course.
2. Big O Notation: Understanding time and space complexity.
3. Analyzing Performance of Arrays and Objects: Examining the efficiency of common data structures.
4. Problem Solving Approach: Step-by-step problem-solving techniques.
5. Problem Solving Patterns: Identifying and utilizing common coding patterns.
6. Problem Solving Challenges: Additional practice exercises.
7. Recursion: Understanding and implementing recursion.
8. Searching Algorithms: Implementing various searching techniques.
9. Sorting Algorithms: Implementation and analysis of sorting algorithms.
10. Data Structures Introduction: Overview and implementation of fundamental data structures.
11. Singly Linked Lists: Implementation and manipulation of linked lists.
12. Doubly Linked Lists: Implementation of doubly linked lists.
13. Stacks Queues: Implementation and applications of stacks and queues.
14. Binary Search Trees: Understanding and working with binary search trees.
15. Tree Traversal: Techniques for traversing trees.
16. Binary Heaps: Implementation and applications of binary heaps.
17. Hash Tables: Understanding and utilizing hash tables.
18. Graphs: Introduction to graphs and their representations.
19. Graph Traversal: Techniques for traversing graphs.
20. Dijkstra's Algorithm: Understanding and implementing Dijkstra's shortest path algorithm.
21. Dynamic Programming: Introduction to dynamic programming concepts.

Usage

You can navigate through the repository to find solutions to specific exercises as per the course structure.

Course Link