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Elite Computer Science Mastery
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Module 4
Hashing, Sets, and Range Queries
Hash Table Collision Resolution
Implement a hash table using both chaining and open addressing for collision resolution.
Designing Effective Hash Functions
Design effective hash functions and explain their impact on performance and key distribution.
3
Hash Tables: Problem-Solving Powerhouse
Apply hash tables to solve common problems like 'Two Sum', 'Group Anagrams', and frequency counting.
4
Optimizing Disjoint Set Union
Implement a Disjoint Set Union (DSU) data structure with path compression and union by rank optimizations.
5
Segment Tree for Range Queries and Point Updates
Implement a segment tree to perform range sum/min/max queries and handle point updates.
6
Fenwick Tree: Prefix Sums and Point Updates
Implement a Fenwick tree (Binary Indexed Tree) for efficient prefix sum queries and point updates.
7
Tries vs. Hash Tables: Prefix Problem Trade-offs
Contrast the trade-offs between Tries and Hash Tables for prefix-based string problems.
8
Segment Trees vs. Fenwick Trees
Contrast Segment Trees with Fenwick Trees for range and prefix query use cases.
Previous module
Hierarchical Data Structures: Trees, Tries, and Heaps
Next module
Graph Algorithms