Master recursion in JavaScript to solve problems and excel in coding interviews with practical exercises and visualizations.

If you’ve ever struggled with solving problems using recursion, or if you have to brush up your skills for an interview, this course is for you.

We'll start with the basics of what recursion is and why it’s important before diving into practicing solving actual questions. You’ll have access to detailed explanations and visualizations for each problem to help you along the way. 

By the time you have completed this course, you’ll be able to use all the concepts to solve complex real-world problems. We hope that through practicing recursion, you will be able to ace all recursion related questions in interviews at top tech companies.

Recursion for Coding Interviews in JavaScript

## Problem Statement
Imagine you have been given the task to schedule some tasks. The tasks are represented as *vertices* of the graph, and if a task $u$ must be completed before a task $v$ can be started, then there is an *edge* from $u$ to $v$ in the graph.

Find the order of the *tasks* so that each task can be performed in the right order.

This problem can be solved if we find the *topological sorting* of the graph.

### What is Topological Sort of a Graph?
A **topological sort** gives the order in which to perform the tasks. 

[Topological sorting](https://en.wikipedia.org/wiki/Topological_sorting) for [Directed Acyclic Graph (DAG)](https://en.wikipedia.org/wiki/Directed_acyclic_graph)  is a linear ordering of vertices. For every directed edge $\{u,v\}$ vertex $u$ comes before $v$ in the ordering. 

> Topological sorting for a graph is not possible if the graph is not a *DAG*.

The algorithm for topological sorting can be visualized as follows:

# Problem Statement
Imagine you have been given the task to schedule some tasks. The tasks are represented as *vertices* of the graph, and if a task $u$ must be completed before a task $v$ can be started, then there is an *edge* from $u$ to $v$ in the graph.

Find the order of the *tasks* so that each task can be performed in the right order.

This problem can be solved if we find the *topological sorting* of the graph.

## What is Topological Sort of a Graph?
A **topological sort** gives the order in which to perform the tasks. 

[Topological sorting](https://en.wikipedia.org/wiki/Topological_sorting) for [Directed Acyclic Graph (DAG)](https://en.wikipedia.org/wiki/Directed_acyclic_graph)  is a linear ordering of vertices. For every directed edge $\{u,v\}$ vertex $u$ comes before $v$ in the ordering. 

> Topological sorting for a graph is not possible if the graph is not a *DAG*.

The algorithm for topological sorting can be visualized as follows:

Given a graph, return a list containing all the nodes of the graph in topological order.


Recursion Fundamentals

Iteration Vs Recursion

Recursion with Numbers

Recursion with Strings

Recursion with Arrays

Recursion with Data Structures

Conclusion

Challenge 3: Topological Sorting of a Graph

Problem Statement

What is Topological Sort of a Graph?