Data Structures & Algorithms

Master the Patterns, Ace the Interviews.

Course Overview

This is not a typical theory course. It's an intensive 12-week program designed to make you a proficient problem-solver and prepare you for the most challenging technical interviews. Starting with the foundational building blocks of computer science, you will learn to implement every major data structure from scratch. You will then use these tools to master the key algorithmic patterns—like Two Pointers, Sliding Window, and Dynamic Programming—that are the key to solving any coding challenge.

What You'll Learn

  • ✓ A deep understanding of Time & Space Complexity (Big O Notation).
  • ✓ How to implement all major data structures from scratch in JavaScript/TypeScript.
  • ✓ Mastery of the 14 essential algorithmic patterns for coding interviews.
  • ✓ A systematic framework for breaking down and solving any new algorithmic problem.
  • ✓ Practical experience solving dozens of curated problems from real-world interviews.
  • ✓ The confidence to excel in whiteboarding and live coding interview sessions.

Week-by-Week Curriculum

Weeks 1-2: Module 1 - The Engineer's Toolkit & Big O

  • Why DSA Matters: The Foundation of all Software
  • Mastering Complexity Analysis: Time Complexity (O(n), O(log n), etc.)
  • Mastering Complexity Analysis: Space Complexity
  • Practical Implementation: Arrays & Dynamic Arrays
  • Practical Implementation: Hash Maps (Hash Tables) from scratch

Weeks 3-4: Module 2 - Linear Structures & Pointers

  • Practical Implementation: Linked Lists (Singly & Doubly)
  • Practical Implementation: Stacks & Queues
  • Pattern Recognition: The Two Pointers Pattern (for Arrays & Linked Lists)
  • Solving Problems: Cycle Detection, Palindromes, Merging Sorted Lists

Weeks 5-6: Module 3 - Sliding Window & Core Patterns

  • Pattern Recognition: The Sliding Window Pattern
  • Solving Problems: Max Subarray Sum, Longest Substring challenges
  • Pattern Recognition: Recursion & Backtracking
  • Solving Problems: Subsets, Permutations, and Combinations

Weeks 7-8: Module 4 - Trees & Traversal Patterns

  • Practical Implementation: Trees (Binary Trees, Binary Search Trees)
  • Pattern Recognition: Breadth-First Search (BFS) for Level-Order Traversal
  • Pattern Recognition: Depth-First Search (DFS) for Tree Traversals (In-order, Pre-order, Post-order)
  • Solving Problems: Validating BSTs, Finding Tree Depth, Path Sum

Weeks 9-10: Module 5 - Advanced Structures & Graph Patterns

  • Practical Implementation: Heaps (Priority Queues)
  • Practical Implementation: Tries (for String problems)
  • Practical Implementation: Graphs (Adjacency Lists)
  • Applying BFS & DFS Patterns to Graphs: Shortest Path, Connected Components

Weeks 11-12: Module 6 - Dynamic Programming & Interview Mastery

  • Pattern Recognition: The Dynamic Programming (DP) Mindset
  • DP Techniques: Memoization and Tabulation
  • Solving Classic DP Problems: Fibonacci, Climbing Stairs, Knapsack
  • Mock Interviews & Whiteboarding Sessions