An elite interactive roadmap mastering computer science fundamentals and algorithmic problem-solving. Click any lesson or milestone to explore in-depth notes and curated tutorials.
Master problem-solving and algorithmic thinking.
Memory Architecture, Big O, and Space Complexity.
RAM layout, stack vs. heap memory, variable storage, and memory references.
Mathematical definition of Big O, Omega, Theta; evaluating loops and recursion trees.
Auxiliary space, recursive call stack memory limits, and tail recursion mechanics.
Memory address tracing, complexity matching quiz, and space complexity evaluations.
Arrays, Strings & Bit Manipulation.
Underlying memory reallocation, capacity vs. size, and amortized analysis of append.
Opposite-direction pointers, fast-slow pointers, fixed and variable-size sliding windows.
1D and 2D prefix sum arrays, matrix traversal, and spiral matrix layouts.
String immutability trade-offs, bitwise operators (AND, OR, XOR) for fast optimization.
Build a dynamic array, solve Container With Most Water, matrix rotations, and XOR checks.
Linked Lists, Stacks & Queues.
Node pointers, insertions, deletions, midpoints, and cycle detection (Floyd's algorithm).
Array vs. Linked-list implementations, and the Monotonic Stack pattern.
FIFO mechanics, queue via two stacks, and sliding window maximum using Deque.
Reverse linked lists, cycle detection, Valid parentheses, and circular queue design.
Advanced searching, divide and conquer, and greedy strategies.
Binary search on sorted arrays, and binary search on monotonic answer spaces.
Merge Sort & Quick Sort: merging logic, pivot partitioning, and worst-case handling.
Greedy choice property, optimal substructure, and interval scheduling.
Split array largest sum, implement Merge/Quick sort, activity selection, and jump games.
Constant-time lookups and caching systems.
Direct address tables, hash codes, chaining, and open addressing probing methods.
Using hash sets/maps for tracking states, and hashing complex structures.
Combining Hash Maps with Doubly Linked Lists for O(1) cache operations.
Build a mini hash map, solve Two-Sum variations, Group Anagrams, and implement an LRU Cache.
Trees, Heaps, and Priority Queues.
Tree terminology, DFS (Pre-order, In-order, Post-order), and BFS (Level Order traversal).
BST invariants, searching, inserting, deleting nodes, and validation.
Complete binary tree properties, and min-heap/max-heap heapify operations.
Max tree depth, level order traversal, LCA in a BST, and Kth largest elements.
The Master Level: Networks and optimal substructure.
Adjacency Matrix vs. Adjacency List, Breadth-First Search (BFS), Depth-First Search (DFS).
Dijkstra's algorithm, Disjoint Set Union (DSU / Union-Find), and Kruskal's algorithm.
Memoization (top-down) vs. Tabulation (bottom-up), and overlapping subproblems.
Number of islands, Dijkstra's network delay, 0/1 Knapsack problem, and Fibonacci tabulation.