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Learning Objectives & Key Takeaways
0 / 4 Completed- Understand Graph Algorithms core architecture and runtime execution model
- Audit real-world latency, throughput benchmarks, and memory footprint
- Implement zero-downtime deployment patterns with resilience guards
- Verify code snippets and architect blueprints against production SLOs
Practise it next
Graph Algorithms interview questions, quiz and handbook in your Learning Dashboard
What you will learn
- BFS finds shortest paths in unweighted graphs; DFS explores and detects cycles.
- Dijkstra finds shortest paths with non-negative weights using a priority queue.
- Topological sort orders tasks with dependencies.
Graphs are everywhere
A graph is just nodes connected by edges. Roads between cities, people who follow each other, packages that depend on packages, and pages that link to pages are all graphs.
Once you recognise a problem as a graph, a small toolkit of algorithms solves most of them.
In the rest of this story
- Choosing the algorithm
- BFS shortest path on a grid
- Interview tips
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