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Data Structures & Algorithms
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Chapter 1: Algorithmic Thinking
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Why DSA Matters
4
Computational Thinking
4
Algorithms — Core Concepts
4
Measuring Algorithm Efficiency
3
Asymptotic Notation
4
Case Analysis & Cost Models
4
Problem Constraints & Trade-offs
5
Expressing Algorithms Clearly
5
Chapter 2: DSA Foundations & Classification
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Chapter 3: Primitive Data Structures
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Chapter 4: Strings
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Chapter 5: Arrays
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Chapter 6: Linked Lists
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Chapter 7: Stacks
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Chapter 8: Queues
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Chapter 9: Recursion
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Chapter 10: Hash Tables
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Chapter 11: Trees
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Chapter 12: Binary Search Trees
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Chapter 13: Balanced Search Trees
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Chapter 14: Heaps & Priority Queues
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Chapter 15: Tries
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Chapter 16: Graphs
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Chapter 17: Searching Algorithms
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Chapter 18: Sorting Algorithms
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Chapter 19: Divide and Conquer
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Chapter 20: Greedy Algorithms
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Chapter 21: Dynamic Programming
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Chapter 22: Backtracking
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Chapter 23: Graph Algorithms
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Graph Traversal Overview
4
BFS — Algorithm & Apps
5
DFS — Algorithm & Apps
5
Connected Components
4
Cycle Detection
4
Topological Sorting
5
Shortest Path (Unweighted)
4
Dijkstra's Algorithm
5
Bellman-Ford Algorithm
5
Floyd-Warshall
4
Choosing Algorithm
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1.
Algorithm Comparison Table — A Comprehensive Reference for Shortest Path Selection
2.
Non-Negative Weights — When Dijkstra's Algorithm Is the Optimal Choice
3.
Negative Weights — When Bellman-Ford Algorithm Is Essential
4.
All Pairs — When Floyd-Warshall Algorithm Is the Right Choice
5.
Decision Framework — A Systematic Approach to Shortest Path Algorithm Selection
Chapter 24: Advanced Graph Algorithms
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Chapter 25: String Algorithms
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Chapter 26: Bit Manipulation
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Chapter 27: Advanced Data Structures
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Chapter 28: Problem Solving Strategies
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