Data Structures Algorithms in JS + 100 LEETCODE Problems

Data Structures & Algorithms in JS + 100 LEETCODE Problems, available at $49.99, has an average rating of 4.78, with 205 lectures, based on 67 reviews, and has 271 subscribers.

You will learn about Master Data Structures & Algorithms in Javascript from Scratch Solve more than 100 Leetcode problems with detailed solutions Learn DSA required for coding interviews in Javascript Learn algorithms asked in coding interviews and their application This course is ideal for individuals who are People who want to study data structure & algorithms or People preparing for coding interviews It is particularly useful for People who want to study data structure & algorithms or People preparing for coding interviews.

Enroll now: Data Structures & Algorithms in JS + 100 LEETCODE Problems

Summary

Title: Data Structures & Algorithms in JS + 100 LEETCODE Problems

Price: $49.99

Average Rating: 4.78

Number of Lectures: 205

Number of Published Lectures: 205

Number of Curriculum Items: 205

Number of Published Curriculum Objects: 205

Original Price: $19.99

Quality Status: approved

Status: Live

What You Will Learn

Master Data Structures & Algorithms in Javascript from Scratch

Solve more than 100 Leetcode problems with detailed solutions

Learn DSA required for coding interviews in Javascript

Learn algorithms asked in coding interviews and their application

Who Should Attend

People who want to study data structure & algorithms

People preparing for coding interviews

Target Audiences

People who want to study data structure & algorithms

People preparing for coding interviews

This course is designed to help you master DSA and ace coding interviews in Javascript.

Jump into the world of Javascript Data Structures & Algorithms with us, starting from the very basics to advanced

What sets this course apart?

We put a lot of emphasis on solving problems and making concepts easy to understand. Forget complex jargon – we focus on practical problem solving techniques you will use.

And here’s exciting news..

We’ve curated 100+ Leetcode Practice Problems to accompany the theory lectures.

Still wondering why should you choose this course?

You’ll love our two-step approach:we start with the theoretical concepts of each data structure and technique, and then provide abundant practice problems to hone your skills and cultivate a problem-solving mindset.

Expect regular updates with over 120 lectures distributed across 12+ sectionsto ensure you stay abreast of industry trends and the latest interview questions.

Explore various data structures comprehensively, including Arrays, Linked Lists, Stacks, Queues, Hash Tables, Deques, Binary Search Trees, Trees, Heaps, Graphs, and Disjoint Set Data Structures.

Delve into algorithms and problem-solving techniquessuch as Binary Search, Binary Search over a range, Binary Search over a partially sorted range, Sliding Window Method, Two-Pointer Method, Greedy Algorithms, Dynamic Programming, Backtracking, and Bit Manipulation.

Course Curriculum

Chapter 1: Course Introduction

Lecture 1: How to get started with Leetcode ?

Chapter 2: Algorithm Analysis

Lecture 1: Introduction to Time & Space Complexity

Lecture 2: What is Big O Notation ?

Lecture 3: Calculating Time Complexity Example 1

Lecture 4: Calculating Time Complexity Example 2

Lecture 5: Calculating Space Complexity

Lecture 6: Calculating time complexity of recursive cases

Lecture 7: Space complexity calculation simple case

Lecture 8: Recursive time complexity example 2

Lecture 9: Recursive space complexity example 2

Lecture 10: Time complexity live demonstration

Chapter 3: Arrays

Lecture 1: What are arrays and how they are stored

Lecture 2: How are arrays accessed

Lecture 3: Disadvantage of standard arrays

Lecture 4: How are resizable arrays implemented

Lecture 5: Resizable array implementation javascript

Lecture 6: Resizable array complexity analysis

Lecture 7: Practice Problem 1 – Maximum Sum Subarray

Lecture 8: Practice Problem 1-Best Time to Buy And Sell A Stock

Lecture 9: Practice Problem 4-Maximum Product Subarray

Lecture 10: Practice Problem 5-Product Of Array Except Self

Lecture 11: Practice Problem 6-Max Consecutive Ones

Lecture 12: Practice Problem 7 – Set Matrix Zeroes

Lecture 13: Practice Problem 8 – Valid Sudoku

Lecture 14: Practice Problem 9 – Rotate Array

Lecture 15: Practice Problem 10 – Spiral Matrix

Chapter 4: Two Pointer Method

Lecture 1: Practice Problem 1 – Trapping Rain Water

Lecture 2: Practice Problem 3-Two Sum II – Input Array Is Sorted

Lecture 3: Practice Problem 3 – Container With Most Water

Lecture 4: Practice Problem 4 – Valid Palindrome

Chapter 5: Sorting

Lecture 1: Module Introduction

Lecture 2: Bubble Sort Working

Lecture 3: Bubble Sort Implementation

Lecture 4: Selection Sort Working

Lecture 5: Selection Sort Implementation

Lecture 6: Merge Two Sorted Arrays Theory

Lecture 7: Merge Two Sorted Arrays Implementation

Lecture 8: Merge Sor theory

Lecture 9: Merge Sort Implementation

Lecture 10: Merge Sort Complexity Analysis

Lecture 11: Two Way Partitioning Algorithm

Lecture 12: Two Way Partitioning Implementation

Lecture 13: Quick Sort Theory

Lecture 14: Quick Sort Implementation

Lecture 15: Counting Sort Algorithm

Lecture 16: Counting Sort Implementation

Lecture 17: How to make Counting Sort stable

Lecture 18: Radix Sort Introduction

Lecture 19: Practice Problem 2-Sort Colors

Lecture 20: Practice Problem 3-Majority Element

Lecture 21: Practice Problem 4-Find the Duplicate Number

Lecture 22: Practice Problem – Move Zeroes

Chapter 6: Hash Table

Lecture 1: What is Hash Table

Lecture 2: Advantage of Hash Table

Lecture 3: How is Hash Table implemented

Lecture 4: Types of Hash Table

Lecture 5: Hash Table Usage

Lecture 6: Practice Problem 1 – Two Sum

Lecture 7: Practice Problem 2 – Three Sum

Lecture 8: Practice Problem 3 – Valid Anagram

Lecture 9: Practice Problem 4 – Longest Consecutive Sequence

Lecture 10: Practice Problem 5 – Contains Duplicate

Lecture 11: Practice Problem 6 – Group Anagrams

Chapter 7: Linked List

Lecture 1: Drawback of Arrays

Lecture 2: What is linked list

Lecture 3: Linked List Implementation

Lecture 4: Inserting at the front

Lecture 5: Insert at the front implementation

Lecture 6: Iterating over linked list

Lecture 7: Iterating over linked list implementation

Lecture 8: Practice Problem 1-Linked List Cycle

Lecture 9: Practice Problem 2-Linked List Cycle II

Lecture 10: Practice Problem 3 – Merge Two Sorted Lists

Lecture 11: Practice Problem 4-Reverse Linked List

Lecture 12: Practice Problem 5-Palindrome Linked List

Lecture 13: Practice Problem 6 – Remove Nth Node From End Of List

Lecture 14: Practice Problem 7 – Intersection Of Two Linked Lists

Chapter 8: Stacks

Lecture 1: What is stack

Lecture 2: Using stack as an array

Lecture 3: Using stack as a linked list theory

Lecture 4: Using stack as a linked list implementation

Lecture 5: Practice Problem 1 – Valid Paranthesis

Lecture 6: Practice Problem 1-Min Stack

Lecture 7: Practice Problem 4-Next Greater Element II

Lecture 8: Practice Problem 5-Merge Intervals

Chapter 9: Queue

Lecture 1: What is queue

Lecture 2: Queue using linked list

Lecture 3: Queue Implementation

Chapter 10: Binary Search

Lecture 1: Introduction to Binary Search

Lecture 2: Binary Search Implementation

Instructors

Pratik Singhal
Senior Software Engineer @ Amazon

Rating Distribution

1 stars: 1 votes

2 stars: 2 votes

3 stars: 3 votes

4 stars: 4 votes

5 stars: 57 votes

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