Coding Interview Patterns: The Complete Pattern Hub
Master coding interviews by learning patterns, not memorizing problems. A categorized map of the core techniques that solve most LeetCode-style questions.
Topics
Topic hubs for coding interview prep. Each hub maps a core interview topic to the day lessons, blog deep dives, and complexity references you need to master it.
Dynamic Programming for Coding Interviews
A complete dynamic programming interview prep hub: what DP is, the core DP patterns interviewers test, a day-by-day curriculum covering memoization, tabulation, knapsack, LCS, LIS, edit distance, and coin change, plus a complexity quick reference.
Array Interview Questions and Algorithms
An arrays interview prep hub: why arrays dominate FAANG interviews, the core techniques (two pointers, sliding window, prefix sums, in-place operations), the day lessons that teach them, and a complexity quick reference for array operations and sorting.
Linked Lists: A Study Guide
How linked lists work, their operations and Big-O, the two-pointer tricks interviewers love, common pitfalls, and the curriculum days that cover them.
Stacks and Queues: A Study Guide
Stacks (LIFO) and queues (FIFO): their operations and Big-O, Python implementations, the patterns they unlock, pitfalls, and the days that teach them.
Big-O Cheat Sheet: Time & Space Complexity Reference
A complete Big-O cheat sheet: time and space complexity of common data structures, sorting algorithms, and coding-interview patterns, with plain-English explanations.
Trees: A Study Guide
Binary trees and BSTs: structure, traversals, operations and their Big-O, a Python traversal example, common pitfalls, and the days that cover trees.
Big-O Quiz: Guess the Time Complexity
Test your Big-O intuition. Read each snippet and guess its time complexity, then get instant feedback and an explanation. 10 interview-style questions.
Heaps: A Study Guide
Binary heaps and priority queues: how they work, operations and Big-O, a Python heapq example, common pitfalls, and the days that teach heaps and heapsort.
Binary Search Visualizer: Watch It Narrow the Range
Interactive binary search visualizer. Enter a target and step through how the low, mid, and high pointers halve the search space until they find it.
Hashing: A Study Guide
Hash tables and hash sets: how hashing works, operations and Big-O, a Python example, collisions and other pitfalls, and the days that cover hashing.
Greedy Algorithms: A Study Guide
The greedy approach: when local choices give a global optimum, complexity, a Python example, common pitfalls, and the days that cover greedy algorithms.
Backtracking: A Study Guide
Backtracking explained: the choose-explore-unchoose template, complexity, a Python example, common pitfalls, and the days that cover backtracking.
Strings: A Study Guide
String algorithms for interviews: operations and Big-O, pattern matching with KMP and Rabin-Karp, a Python example, pitfalls, and the days that cover them.
Graph Algorithms You Must Know for FAANG Interviews
A complete topic hub for graph algorithms in coding interviews. Covers what graphs are and how to represent them (adjacency list vs. matrix), when to choose BFS vs. DFS with full Python implementations, the shortest-path ladder from plain BFS through Dijkstra, Bellman-Ford, and Floyd-Warshall, and the five interview patterns that account for most graph questions: connected components and island counting, cycle detection, topological sort with Kahn's algorithm, grid-as-graph BFS, and union-find. Includes a curated problem list ordered from easy to hard, complexity tables, and links to the day-by-day graph lessons in the 60-day curriculum.