Courses  /  Data Structures & Algorithms
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Data Structures & Algorithms

Master DSA from absolute zero to interview-ready. Covers Big O, arrays, trees, graphs, dynamic programming, and 120+ LeetCode problems — designed so even a kid can start and reach mastery.

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1

Big O & Complexity

Understand how to measure code speed and memory. The foundation of everything in DSA.

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2

Arrays

The most fundamental data structure. Learn to manipulate arrays and solve classic problems.

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3

Strings

Strings are everywhere. Learn pattern matching, reversal, and classic string problems.

0/7
4

Hash Maps & Sets

The secret weapon for O(1) lookups. Hash maps solve a huge number of interview problems.

0/7
5

Two Pointers

A powerful technique using two references to solve problems in O(n) time.

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6

Sliding Window

Process subarrays efficiently by sliding a window across the data.

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7

Binary Search

Cut the search space in half every step. The key to O(log n) solutions.

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8

Sorting Algorithms

Implement the most important sorting algorithms from scratch and understand their trade-offs.

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9

Linked Lists

Dynamic data structures where elements point to each other. A favorite in interviews.

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10

Stacks

Last-In-First-Out. Stacks power undo operations, parsing, and monotonic patterns.

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11

Queues & Deques

First-In-First-Out. Queues model real-world lines and power BFS algorithms.

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12

Recursion

Functions that call themselves. The gateway to trees, graphs, and dynamic programming.

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13

Binary Trees

Hierarchical data structures. Trees appear in almost every coding interview.

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14

Binary Search Trees

Trees with a sorting property that enable O(log n) search, insert, and delete.

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15

Heaps & Priority Queues

Always access the min/max in O(1). Heaps power scheduling and top-K problems.

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16

Graphs — BFS & DFS

Model connections between things. Learn traversal, components, and pathfinding.

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17

Advanced Graphs

Topological sort, shortest paths, and union-find for complex graph problems.

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18

Dynamic Programming — 1D

Break problems into overlapping subproblems. The most feared yet most rewarding topic.

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19

Dynamic Programming — 2D

Multi-dimensional DP for grids, strings, and sequence comparison problems.

0/6
20

Greedy Algorithms

Make the locally optimal choice at each step. Elegant solutions to optimization problems.

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21

Backtracking

Explore all possibilities and backtrack when stuck. Powers combinatorial problems.

0/6
22

Tries

Prefix trees for lightning-fast string lookups. Powers autocomplete and spell-check.

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23

Bit Manipulation

Work directly with binary. Incredibly efficient for certain problems.

0/6
24

Master Level Finale

The hardest problems combining multiple techniques. If you can solve these, you're interview-ready.

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