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Development Software Engineering Data Structures

Amazing Graph Algorithms : Coding in Java,JavaScript, Python

Graph Data Structure, DFS, BFS, Minimum Spanning Tree, Shortest Path, Network Flow, Strongly Connected Components
Rating: 4.7 out of 54.7 (4 ratings)
78 students
Created by Basics Strong
Last updated 1/2021
English
English, French, 
30-Day Money-Back Guarantee

What you'll learn

  • Graph Algorithms
  • Programming Algorithms

Course content

9 sections • 68 lectures • 9h 0m total length

  • Preview04:56
  • Google's Knowledge Graph
    00:02
  • Graphs - Overview
    11:53
  • Terminologies
    01:30
  • Preview03:53
  • Approaching the Problem
    09:12
  • Journey : What We Are Going To Cover
    02:37

  • Course Resources
    00:11

  • Graph Traversal
    02:28
  • Depth First Search Traversal - DFS
    06:17
  • DFS - Recursive Java Implementation
    07:06
  • DFS - Iterative Java Implementation
    04:49
  • DFS - Recursive Javascript Implementation
    06:02
  • DFS - Iterative Javascript Implementation
    03:48
  • DFS - Recursive Python Implementation
    05:15
  • DFS - Complexity Analysis
    00:34
  • Breadth First Search Traversal
    03:26
  • BFS - Java Implementation
    04:58
  • BFS - Javascript Implementation
    04:31
  • BFS - Python Implementation
    04:18
  • BFS - Complexity Analysis
    00:35

  • What Are Spanning Trees; What is MST?
    05:29
  • Preview09:28
  • Prim's Algorithm - Java Implementation
    07:33
  • Prim's Algorithm - Javascript Implementation
    08:07
  • Prim's Algorithm - Python Implementation
    06:07
  • Kruskal's Algorithm
    03:55
  • Union-Find Algorithm
    08:09
  • Kruskal's Algorithm - java Implementation
    13:14
  • Kruskal's Algorithm - Javascript Implementation
    10:37
  • Kruskal's Algorithm - Python Implementation
    08:47

  • Finding Shortest Path
    01:16
  • Dijkstra's Algorithm
    09:21
  • Dijkstra's Algorithm - Java Implementation
    08:58
  • Dijkstra's Algorithm - Javascript Implementation
    07:35
  • Dijkstra's Algorithm - Python Implementation
    07:10
  • BellmanFord's Algo
    06:46
  • BellmanFord's Algo Live Code Java
    11:19
  • BellmanFord's Algo Live Code Javascript
    08:41
  • BellmanFord's Algo Live Code Python
    07:59
  • Floyd Warshall Algorithm
    06:45
  • Floyd-Warshall Algorithm - Java Implementation
    05:46
  • Floyd-Warshall Algorithm - Javascript Implementation
    04:35
  • Floyd-Warshall Algorithm - Python Implementation
    04:42
  • Johnson's Algorithm
    15:40
  • Johnson's Algorithm - Java Implementation
    20:22
  • Johnson's Algorithm - Javascript Implementation
    19:26
  • Johnson's Algorithm - Python Implementation
    17:50

  • What Are Flow Networks?
    04:39
  • Ford-Fulkerson Algorithm
    26:34
  • Ford-Fulkerson Algorithm - Edmond's Karp Java Implementation
    20:15
  • Ford-Fulkerson Algorithm - Edmond's Karp Javascript Implementation
    17:03
  • Ford-Fulkerson Algorithm - Edmond's Karp Python Implementation
    14:20
  • Max-Flow Min-Cut Theorem
    05:45

  • Strongly Connected Components
    02:49
  • Tarjan's Algorithm
    09:54
  • Tarjan's Algorithm - Java Implementation
    12:24
  • Tarjan's Algorithm - Javascript Implementation
    11:07
  • Tarjan's Algorithm - Python Implementation
    09:27
  • Kosaraju's Algorithm
    06:06
  • Kosaraju's Algorithm - Java Implementation
    11:00
  • Kosaraju's Algorithm - Javascript Implementation
    08:48
  • Kosaraju's Algorithm - Python Implementation
    07:23

  • Topological Sort : Kahn's Algo
    06:31
  • Topological Sort Live Code Java
    13:53
  • Topological Sort Live Code Javascript
    07:53
  • Topological Sort Live Code Python
    10:34

  • Thank you!
    00:04

Requirements

  • No

Description


Graphs are Amazing!

We will have a lot to cover in this course also the course is coded in Java, JavaScript & Python.

While solving graph algorithms, We may need to visit and process each node present in the graph. And for that, we must know how to traverse the graphs efficiently,

So, first, we will cover graph traversal, where we gonna see the 2 types of graph traversals, Depth First Search, and Breadth-first Search.

Then we will understand Spanning Trees and will see famous algorithms to find minimum cost spanning tree, basically, a minimum cost spanning tree is a tree from the graph connecting all the vertices with single edges each and that all

Of the lowest cost, so to minimize the cost to connect all the vertices.

For example :

Suppose, you own a telecommunication company

and you have towers that spread across the state.

You want to connect them so that data can be passed from one tower to others.

Connecting different towers involve different costs, so the problem is how will you minimize the cost. Here, comes the need of using Minimum spanning tree algorithms to find

That tree connecting all the towers with edges that have a minimum cost, so that the spanning Tree cost is minimum.

After that, we will look to Shortest Path algorithms, these are useful to find the shortest distance from of a source from all the other vertices (called single-source shortest path)

or shortest distance of each vertex with all the

Other vertices, that's called finding all pair shortest path.

For example, finding the distance of a city, let's say Istambul to all the other famous cities of turkey.

Or let's say A person who is planning a trip may need to answer questions such as, “What is the least expensive way to get from Princeton to San Jose?” A person more interested in time than in money may need to know the answer to the question “What is the fastest way to get from Princeton to San Jose?” To answer such questions, we process information about connections (travel routes) between items (towns and cities).

Then we will move to Flow network problems. These are concerned with the networks or graph, having a flow going through it.

There will be problems that ask to maximize the flow across the network or problems that ask to disconnect the source from the destination or sink in minimum cost.

After that we will discuss, algorithms to find strongly connected components in a graph.

Hope you will enjoy the course.

Happy Learning

Who this course is for:

  • Who wants to deep dive into graphs
  • Want to solve some super complicated graph Algorithms

Instructor

Basics Strong
Team of technocrats and Programming lovers
Basics Strong
  • 4.4 Instructor Rating
  • 1,222 Reviews
  • 11,835 Students
  • 13 Courses

Hi,

We are a team of technocrats from IITs who work for solving problems through technology. We work on mission critical projects in AI, Machine Learning, BlockChain as domain and Java, Python, JavaScript and a lot of tools and technologies in technology space.

We all as a group love to code and Program.

We believe in strong foundation that's why we create courses which helps us students and professionals to build their Basics.

Strong foundation and basics of programming concepts can lead to solve any technical problem and to excel in the career.

That's why we as a team  thinks everyday how to make the complicated concepts easy to learn. All our courses are practical and with hands-on examples and comprehensive working files.

All Our videos are created after a  comprehensive  research and reviews.

Happy Learning! and All The Best for a Great Foundation!


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