Are you ready to become a top-notch JavaScript developer? Understand two of the most important concepts in programming - Data Structures & Sorting Algorithms.

Learn to make efficient algorithms that save space and time if you want to excel in the field of software development. Take this interactive course to find out how to employ the most effective data structure in any scenario. This course covers sorting algorithms and their time complexity using JavaScript along with various data structures like Trees, Graphs, Heaps, Linked lists  and many more.

Mastering Data Structures and Sorting Algorithms in JavaScript

If an algorithm has logarithmic time complexity, it means that the size of the input we are considering gets split into half with each iteration. Let’s say that we have a function that takes 1 second to execute if the input size is 100. With a logarithmic runtime, it would then take 2 seconds if the input size is 1000, and 3 seconds if the input size is 10,000. The bigger the input size gets, the smaller the difference in runtime!

Consider the following array:

The size of the input gets split into half with each iteration of the function. (Reading time: under 2 minutes)

Big-O Notation

Data Structures

Stacks

Queues

Linked Lists

Binary Search Tree

Hash Table

Graphs

Sorting Algorithms

Bubble Sort

Insertion Sort

Merge Sort

Quicksort

Selection Sort

Counting Sort

Bucket Sort

Radix Sort

Heap Sort

Logarithmic Complexity - O(log(n))