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70+ JavaScript Challenges Data Structures & Algorithms - Printable Version

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70+ JavaScript Challenges Data Structures & Algorithms - Farid - 09-07-2023

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70+ Javascript Challenges: Data Structures & Algorithms
Published 9/2023
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 5.58 GB | Duration: 12h 28m
Build better foundational skills as a developer by doing challenges and learning about data structures and algorithms

What you'll learn

Explore 70+ coding challenges from beginner, intermediate and advanced levels

Ace coding interviews by learning how to solve problems with iteration, recursion, array methods & more

Master data structures like stacks, queues, linked lists, trees, maps and hash maps

Learn about sorting algorithms like bubble sort, insertion, merge and quick sort

Full sandbox with explanations and Jest tests for every challenge

You do NOT have to take on the challenges alone. Follow along and learn from the explanations

Requirements

You should know JavaScript & programming fundamentals

Description

Most of my students know me for my practical, project-based courses and tutorials. I wanted to create something to give you more fundamental skills for problem solving. That's where the idea for this challenges course came from. I want to take my down-to-earth explanations to help you get a better understanding of the code that you write and help you write more efficient code.This course is for all levels as long as you have a basic understanding of things like loops, functions, arrays, etc. We are writing JavaScript in this course, but about 95% of it can translate to any other language. So even if you are a Python, PHP or C# developer, you can still follow along.Basic Challenges:We start with a bunch of basic challenges that have to do with iteration and loops. Things like FizzBuzz and string reversals. These are very popular questions for entry-level interviews. We also move on to solving problems with high order array methods like filter and map.Recursion:Recursion is one of the toughest things to learn in programming. We have an entire section dedicated to it with challenges that we solve using recursion.Time & Space Complexity:We talk about how to measure an algorithm or function's efficiency by using time and space complexity to see how the runtime and memory scale when inscreasing the input.Data Structures: Stacks, Queues, Trees, Linked Lists, Graphs, HashMapsWe go over all of the common data structures and create our own implementation of them using JavaScript classes, but like I said, you could use any language. We also learn how to traverse them and complete challenges using them.Sorting Algorithms:We get into different sorting algorithms like bubble sort, insertion, selection, merge and quick sort. These are popular topics for interviews.

Overview

Section 1: Introduction

Lecture 1 Welcome To The Course

Lecture 2 Course Structure

Lecture 3 DSA - The What & Why

Lecture 4 Tools & Basic Setup

Lecture 5 Sandbox Environment Setup

Section 2: Basic Challenges - Part 1

Lecture 6 Hello World (Starter Challenge)

Lecture 7 Get Sum (Starter Challenege)

Lecture 8 Calculator

Lecture 9 Count Occurences

Lecture 10 Find Max Number

Lecture 11 Title Case

Lecture 12 Reverse String

Lecture 13 Palindrome

Lecture 14 Count Vowels

Lecture 15 Remove Duplicates

Section 3: Basic Challenges - Part 2

Lecture 16 FizzBuzz Array

Lecture 17 Array Intersection

Lecture 18 Display Likes

Lecture 19 Find Missing Number

Lecture 20 Find Missing Letter

Lecture 21 Are All Chars Unique?

Lecture 22 First Non-Repeating Character

Lecture 23 Dice Game Simulation

Lecture 24 Format Phone Number

Lecture 25 Validate Email

Section 4: High Order Array Methods

Lecture 26 Simple Examples

Lecture 27 Sum Of Even Squares

Lecture 28 Calculate Total Sales

Lecture 29 Highest Scoring Word

Lecture 30 Valid Anagrams

Lecture 31 Hashtag Generator

Lecture 32 Valid IPv4

Lecture 33 Analyze Car Mileage

Lecture 34 Password Validator

Lecture 35 Find Missing Letter Refactor

Section 5: Recursion

Lecture 36 Recursion Intro (Countdown)

Lecture 37 Recursive Unwinding

Lecture 38 Reverse String Using Recursion

Lecture 39 Fibonacci Sequence

Lecture 40 Factorial

Lecture 41 Power

Lecture 42 Array Sum

Lecture 43 Number Range

Lecture 44 Flatten Array

Lecture 45 Permutations

Section 6: Time & Space Complexity

Lecture 46 What Is Time Complexity?

Lecture 47 Big O Notation

Lecture 48 Constant Time Complexity - O(1)

Lecture 49 Linear Time Complexity - O(n)

Lecture 50 Quadratic Time Complexity - O(n^2)

Lecture 51 Logarithmic Time Complexity - O(log n)

Lecture 52 Space Complexity

Lecture 53 Max Subarray - Quadratic

Lecture 54 Sliding Window Technique

Lecture 55 Max Subarray - Linear

Section 7: Hash Tables, Maps & Sets

Lecture 56 Hash Table Intro

Lecture 57 Maps

Lecture 58 Word Frequency Counter

Lecture 59 Phone Number Directory

Lecture 60 Anagram Grouping

Lecture 61 Sets

Lecture 62 Symmetric Difference

Lecture 63 Two Sum

Lecture 64 Longest Consecutive

Lecture 65 Custom Hash Table - Part 1

Lecture 66 Custom Hash Table - Part 2

Lecture 67 Word Instance Counter Using Custom Hash Table

Lecture 68 Add getValues Method

Lecture 69 Anagram Grouping With Custom Hash Table

Section 8: Stacks, Queues & Linked Lists

Lecture 70 What Is A Stack?

Lecture 71 Stack Implementation

Lecture 72 Reverse String Using A Stack

Lecture 73 Balanced Parenthesis

Lecture 74 What Is A Queue?

Lecture 75 Queue Implementation

Lecture 76 Reverse String With A Queue

Lecture 77 Palindrome With A Queue & Stack

Lecture 78 What Is A LInked LIst?

Lecture 79 Linked List Implementation

Lecture 80 Reverse String With A Linked List

Lecture 81 Fast & Slow Pointers

Lecture 82 Find Middle

Lecture 83 What Is A Doubly Linked List?

Lecture 84 Doubly Linked List Implementation - Part 1

Lecture 85 Doubly Linked List Implementation - Part 2

Lecture 86 Find Pair Sum

Section 9: Binary Trees, BST & Graphs

Lecture 87 What Is a Tree / Binary Tree?

Lecture 88 Tree Node Class

Lecture 89 Depth-First Traversal

Lecture 90 Depth-First Traversal Using Recursion

Lecture 91 Breadth-First Traversal

Lecture 92 Maximum Depth

Lecture 93 What Is A Binary Search Tree?

Lecture 94 Binary Search Tree Implementation - Part 1

Lecture 95 Binary Search Tree Implementation - Part 2

Lecture 96 Validate BST

Lecture 97 What Is A Graph?

Lecture 98 Adjacency Matrix & Adjacency List

Lecture 99 Graph Implementation

Lecture 100 Graph Traversal Visualization

Lecture 101 Graph Depth-First Traversal

Lecture 102 Graph Breadth-First Traversal

Section 10: Sorting Algorithms

Lecture 103 What Are Sorting Algorithms?

Lecture 104 Bubble Sort Algorithm

Lecture 105 Bubble Sort Implementation

Lecture 106 Insertion Sort Algorithm

Lecture 107 Insertion Sort Implementation

Lecture 108 Selection Sort Algorithm

Lecture 109 Selection Sort Implementation

Lecture 110 Merge Sort Algorithm

Lecture 111 Merge Sort Implementation

Lecture 112 Quick Sort Algorithm

Lecture 113 Quick Sort Implementation

Section 11: Wrap Up

Lecture 114 Wrap Up

Developers that want to build better foundational problem solving skills and pass job interviews

70+ JavaScript Challenges Data Structures & Algorithms (5.58 GB)

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