Data Structures and Algorithms in C++ For Coding Interview

Course Curriculum

Chapter 1: Introduction

Lecture 1: Introduction to Course

Lecture 2: What is LeetCode, and How will we use it?

Chapter 2: ———————-ARRAYS AND STRINGS DATA STRUCTURES————————

Lecture 1: Start of Arrays And Strings Data Structure

Chapter 3: Arrays Data Structures: Two Sum

Lecture 1: Two Sum problem Statement and O(n^2) Solution

Lecture 2: Implementation of O(n^2) naive solution

Lecture 3: Optimizing Further for O(nlogn) Solution

Lecture 4: Implementing the O(nlogn) Solution

Chapter 4: Arrays Data Structures Maximum Consecutive Ones

Lecture 1: Problem Statement

Lecture 2: O(n^2) Naive Solution

Lecture 3: O(n^2) Naive Solution Implementation

Lecture 4: O(n) Solution idea and optimizations

Lecture 5: O(n) Solution Implementation

Chapter 5: Arrays Data Structures: Finding Maximum of three numbers

Lecture 1: Problem Statement

Lecture 2: O(n^3) Naive Solution

Lecture 3: O(nlogn) Improved Solution

Lecture 4: Implementation of O(nlogn) solution

Lecture 5: Optimizing further and reaching O(n) Solution

Lecture 6: Implementation of O(n) Solution

Chapter 6: ——————————STACK DATA STRUCTURE——————————

Lecture 1: Start of Stack Section

Chapter 7: Stack Data Structure: Valid Parenthesis

Lecture 1: Problem Statement

Lecture 2: Incorrect Approaches/Algorithms to the Problem

Lecture 3: Recursive Algorithm Solution That runs in O(n^2) Time

Lecture 4: Implementation of O(n^2) Recursive Algorithm

Lecture 5: Optimizing further With Stacks to get O(n) Solution Idea

Lecture 6: O(n) Solution Implementation

Chapter 8: Stack Data Structure: Baseball Game

Lecture 1: Problem Statement and Example

Lecture 2: Naive O(n^2) Solution with additional boolean array

Lecture 3: Implementation of O(n^2) Solution

Lecture 4: Optimizing on the last algorithm to an O(n) Solution

Lecture 5: Implementation of O(n) Solution

Chapter 9: —————————-HASH MAP DATA STRUCTURE—————————-

Lecture 1: Start of Hash Map Data Structure

Chapter 10: Hashmap and Hash Set Datastructure: Contains Duplicate II

Lecture 1: Problem Statement

Lecture 2: Bruteforce Algorithm Idea: O(nk) Solution

Lecture 3: Bruteforce Implementation and Time Limit Exceeded

Lecture 4: Optimizing Using Hashmaps to get O(n) Solution on average

Lecture 5: Implementing the O(n) Solution

Chapter 11: Hash map and Hash Set Data structure: Valid Anagram

Lecture 1: Problem Statement

Lecture 2: O(n!) Brute force Solution

Lecture 3: O(n^2) Solution idea for Valid anagram

Lecture 4: O(n^2) Solution Implementation

Lecture 5: O(nlogn) Solution by Optimizing bottleneck

Lecture 6: O(nlogn) Solution Implementation

Lecture 7: O(n) Solution Idea, The final optimization with Hashtable

Lecture 8: O(n) Solution Implementation

Chapter 12: ——————————HEAP DATA STRUCTURE——————————

Lecture 1: Start of Heap Data Structure

Chapter 13: Heap Data Structure: Kth Largest Element in an Array

Lecture 1: Problem Statement

Lecture 2: O(nlogn) Naive Solution Idea

Lecture 3: O(nlogn) Naive Solution Implementation

Lecture 4: O(nlogk) Optimized Solution Using a Heap

Lecture 5: Implementation of O(nlogk) Heap Solution

Chapter 14: Heap Data Structure: Find K Pairs with Smallest Sums

Lecture 1: Problem Statement

Lecture 2: Idea of O(n^2Logn) Naive Solution and O(n^2logk) Optimized Solution using Heap

Lecture 3: Implementation of O(n^2Logn) and O(n^2Logk) Solutions

Chapter 15: —————————BINARY TREE DATA STRUCTURE—————————

Lecture 1: Start of Tree Data Structure Section

Chapter 16: Tree Data Structure: Invert Binary Tree

Lecture 1: Problem Statement

Lecture 2: O(n) Recursive Solution Idea

Lecture 3: O(n) Solution implementation

Chapter 17: Tree Data Structure: Same Tree

Lecture 1: Problem Statement

Lecture 2: O(n) Recursive Solution Idea

Lecture 3: O(n) Solution Implementation

Chapter 18: Tree Data Structure: Maximum Depth of Binary Tree

Lecture 1: Problem Statement

Lecture 2: O(n) Recursive Solution Idea

Lecture 3: O(n) Solution Implementation

Chapter 19: ——————————Assignments Section——————————