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A series of lecture on Data Structures and Algorithms - 1.

The bugs people actually hit with graph algorithms — shown, explained, and fixed. A gallery of real mistakes: what they look like, ...

The bugs people actually hit with graph traversal — shown, explained, and fixed. A gallery of real mistakes: what they look like, ...

Linear vs Non-Linear Data Structures, Static vs Dynamic Data StructuresMaster the structural architecture of data by exploring ...

The bugs people actually hit with graph representations — shown, explained, and fixed. A gallery of real mistakes: what they look ...

When to reach for sorting and searching — and when not to. The design tradeoffs, side by side. We compare sorting and ...

The cost of every graph algorithm operation in one place — big-O, and the traps that bite in practice. We build the complexity table ...

Two questions, two different winners: listing a vertex's neighbours favours the adjacency list, testing one specific edge favours the ...

A tight recap of sorting and searching: the mental model, the operations, and the costs — everything worth keeping. The essential ...

Adding one undirected edge in both representations — and the bug that quietly turns an undirected graph into a directed one.

The Trie abstract data type: describing the type by what it promises, not how it's built. We separate the interface (the operations ...

The bugs people actually hit with tries — shown, explained, and fixed. A gallery of real mistakes: what they look like, why they ...

Update a whole range in O(log n): mark a node "I owe my subtree +delta", and push that tag down only when something has to ...

Three ideas hold this chapter together: relaxation, spanning trees and topological order. Before any single algorithm, we name the ...

The Traversal abstract data type: describing the type by what it promises, not how it's built. We separate the interface (the ...

The cost of every graph representation operation in one place — big-O, and the traps that bite in practice. We build the complexity ...

The invariants of graph traversal: the facts that must stay true after every operation. We state each invariant plainly and show how ...

When to reach for graph algorithms — and when not to. The design tradeoffs, side by side. We compare graph algorithms against ...

A plain, precise definition of sorting — and the one idea everything else follows from. We define it exactly, picture it, and pull out ...

Programming, Data Structures And Algorithms Using Python Week 5 || NPTEL 2026 #nptel #myswayam YouTube Description: ...