Your roadmap to real skills.

Why Data Structures Matter

Understand why the choice of data structure determines performance, and evaluate structures by their operation costs.

Arrays and Dynamic Arrays

Explain array memory layout, why random access is O(1), and how dynamic arrays grow with amortized O(1) appends.

Linked Lists

Implement singly, doubly, and circular linked lists; know when they beat arrays and when they do not.

Stacks

Implement a stack and use it for balanced parentheses and expression evaluation.

Queues

Implement queues with a deque, and recognize deques, priority queues, and their uses in BFS and job queues.

Hash Tables

Explain hashing, collision handling, load factor, and why operations are O(1) average and O(n) worst case.

Trees and Binary Search Trees

Implement a BST with insert/search/delete and all four traversals; understand why balancing matters.

Heaps

Implement heap insertion and extraction, and use heaps for priority queues, heap sort, and the top-K pattern.

Graphs

Represent graphs and implement BFS and DFS from scratch.

Tries

Implement a basic trie and explain where prefix trees are used (autocomplete, spell check, IP routing).

Segment Trees and Fenwick Trees

Use segment trees and Fenwick (binary indexed) trees for O(log n) range queries and point updates.

Passion Project: Data Structures Library

Build and publish a tested data structures library implementing the core structures from scratch.

Data Structures Job Readiness

Translate data structures knowledge into resume bullets and confident interview answers.