Gain insights into efficient algorithm creation with JavaScript. Delve into data structures and sorting algorithms, including Trees, Graphs, Heaps, and Linked lists, optimizing space and time.

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

## Best, average and worst:
There are nested for-loops. We iterate over the outer for-loop **n** times, and the inner for loop **k** times. This results in **O(n×k)**.

**Worst space**: Outside the for-loops, there are four constant variables: **O(n)**, and inside the for-loops there are four constant variables: **O(k)**. This results in **`O(n) + O(k) = O(n + k)`**.

# Best, average and worst:
There are nested for-loops. We iterate over the outer for-loop **n** times, and the inner for loop **k** times. This results in **O(n×k)**.

**Worst space**: Outside the for-loops, there are four constant variables: **O(n)**, and inside the for-loops there are four constant variables: **O(k)**. This results in **`O(n) + O(k) = O(n + k)`**.

best, average and worst case time complexity of the radix sort algorithm. (Reading time: 1 minute)

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

Radix Sort (Time Complexity)

Best, average and worst: