Dijkstra's Shortest Path Algorithm Visually Explained | How it Works | With Examples

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Master Dijkstra’s Algorithm in 10 minutes — see every step visualised and learn how to use priority queues to find shortest paths in any weighted graph.

Dijkstra’s Algorithm is the go-to method for GPS routing, network optimisation, and game AI.
In this concise, animation-driven lesson you’ll learn:

→ Graph basics in 60 sec – vertices, edges, weights
→ How to build the distance table & priority queue
→ Step-by-step walkthrough of each relaxation update
→ What “decrease-key” really does and why Fibonacci heaps can speed things up
→ Time & space complexity breakdown so you can ace your next interview

Whether you’re prepping for a coding interview, cramming for an algorithms exam, or building path-finding into your own project, this video will give you the intuition and the maths.

Chapters:
0:00 Intro – The sample graph
0:12 Building the tracking table
0:36 Choosing the start node
0:49 Filling the priority queue
1:01 Main loop begins
1:11 Visitng A's neighbours
2:36 Processing node b
3:09 Updating E & C via B
3:40 Tie-break: picking E, decrease-key
4:39 What "decrease key" means
8:32 Queue empties -algorithm ends
8:42 Back-tracing shortest path A → C
9:17 Time & space complexity

More Visually Explained algorithms:

Tools & Credits
Manim (Python library by 3Blue1Brown) for all visuals
Adobe Premiere Pro for editing
Music: “Sovereign” by Kevin MacLeod (CC-BY 3.0) via Incompetech / Chosic

#DijkstrasAlgorithm #ShortestPath #GraphTheory #DataStructures #AlgorithmVisualization #CodingInterview #Manim

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