Data Structures & Algorithms JavaScript

Data Structures & Algorithms JavaScript

What you’ll learn

Mastery of Data Structures and Algorithms
Confidently answer technical interview questions
Time and Space Complexity of Data Structures and Algorithms
Strengthen your skills as a developer

Requirements

Basic programming
No experience with data structures or algorithms required

Description

This course is different…After each line of code, an animation of the data structure or algorithm is updated to show exactly what that line of code did.The advanced level animations provide huge advantages to students:Increased understanding of the conceptsGreater rate of retentionThe material can be covered in a fraction of the timeThat means that you can actually learn more material in less time and have higher retention of the material.That is the key combination of factors to prepare you for the technical interview that lands you your dream job!I invite you to watch a few of the videos in this course to see what I mean. The difference will be noticeable right away! I spent over a year to create this course with the goal that an absolute beginner can take it and understand all of the concepts the first time through.What you will get in this course…Over 100 hand crafted HD videos that use animations to illustrate technical concepts.Here is what you will learn in this course:TechnicalBig O notationData StructuresArraysLinked ListsDoubly Linked ListsStacks & QueuesBinary TreesHash TablesGraphsAlgorithmsSorting Bubble SortSelection SortInsertion SortMerge SortQuick SortSearchingBreadth First SearchDepth First SearchI am excited to help you move forward with your coding and career goals.  Let’s get started!

Overview

Section 1: Introduction

Lecture 1 Introduction

Lecture 2 Overview (Please Watch)

Lecture 3 Code Editor

Section 2: Big O

Lecture 4 Big O: Intro

Lecture 5 Big O: Worst Case

Lecture 6 Big O: O(n)

Lecture 7 Big O: Drop Constants

Lecture 8 Big O: O(n^2)

Lecture 9 Big O: Drop Non-Dominants

Lecture 10 Big O: O(1)

Lecture 11 Big O: O(log n)

Lecture 12 Big O: Different Terms for Input

Lecture 13 Big O: Arrays

Lecture 14 Big O: Wrap Up

Section 3: Classes & Pointers

Lecture 15 Classes

Lecture 16 Pointers

Section 4: Data Structures: Linked Lists

Lecture 17 Linked List: Intro

Lecture 18 LL: Big O

Lecture 19 LL: Under the Hood

Lecture 20 LL: Constructor

Lecture 21 LL: Push

Lecture 22 LL: Reminder

Lecture 23 LL: Pop – Intro

Lecture 24 LL: Pop – Code

Lecture 25 LL: Unshift

Lecture 26 LL: Shift

Lecture 27 LL: Get

Lecture 28 LL: Set

Lecture 29 LL: Insert

Lecture 30 LL: Remove

Lecture 31 LL: Reverse

Section 5: Data Structures: Doubly Linked Lists

Lecture 32 DLL: Constructor

Lecture 33 DLL: Push

Lecture 34 DLL: Pop

Lecture 35 DLL: Unshift

Lecture 36 DLL: Shift

Lecture 37 DLL: Get

Lecture 38 DLL: Set

Lecture 39 DLL: Insert

Lecture 40 DLL: Remove

Section 6: Data Structures: Stacks & Queues

Lecture 41 Stack: Intro

Lecture 42 Stack: Constructor

Lecture 43 Stack: Push

Lecture 44 Stack: Pop

Lecture 45 Queue: Intro

Lecture 46 Queue: Constructor

Lecture 47 Queue: Enqueue

Lecture 48 Queue: Dequeue

Section 7: Data Structures: Trees

Lecture 49 Trees: Intro & Terminology

Lecture 50 Binary Search Trees: Example

Lecture 51 BST: Big O

Lecture 52 BST: Constructor

Lecture 53 BST: Insert – Intro

Lecture 54 BST: Insert – Code

Lecture 55 BST: Contains

Lecture 56 BST: Minimum Value

Section 8: Data Structures: Hash Tables

Lecture 57 Hash Table: Intro

Lecture 58 HT: Collisions

Lecture 59 HT: Constructor

Lecture 60 HT: Set

Lecture 61 HT: Get

Lecture 62 HT: Keys

Lecture 63 HT: Big O

Lecture 64 HT: Interview Question

Section 9: Data Structures: Graphs

Lecture 65 Graph: Intro

Lecture 66 Graph: Adjacency Matrix

Lecture 67 Graph: Adjacency List

Lecture 68 Graph: Big O

Lecture 69 Graph: Add Vertex

Lecture 70 Graph: Add Edge

Lecture 71 Graph: Remove Edge

Lecture 72 Graph: Remove Vertex

Section 10: Algorithms: Recursion

Lecture 73 Recursion: Intro

Lecture 74 Call Stack

Lecture 75 Factorial

Section 11: Algorithms: Basic Sorts

Lecture 76 Bubble Sort: Intro

Lecture 77 Bubble Sort: Code

Lecture 78 Selection Sort: Intro

Lecture 79 Selection Sort: Code

Lecture 80 Insertion Sort: Intro

Lecture 81 Insertion Sort: Code

Lecture 82 Insertion Sort: Big O

Section 12: Algorithms: Merge Sort

Lecture 83 Merge Sort: Overview

Lecture 84 Merge: Intro

Lecture 85 Merge: Code

Lecture 86 Merge Sort: Intro

Lecture 87 Merge Sort: Code

Lecture 88 Merge Sort: Big O

Section 13: Algorithms: Quick Sort

Lecture 89 Quick Sort: Intro

Lecture 90 Pivot: Intro

Lecture 91 Pivot: Code

Lecture 92 Quick Sort: Code

Lecture 93 Quick Sort: Big O

Section 14: Algorithms: Tree Traversal

Lecture 94 Tree Traversal: Intro

Lecture 95 BFS (Breadth First Search): Intro

Lecture 96 BFS: Code

Lecture 97 DFS (Depth First Search): PreOrder – Intro

Lecture 98 DFS: PreOrder – Code

Lecture 99 DFS: PostOrder – Intro

Lecture 100 DFS: PostOrder – Code

Lecture 101 DFS: InOrder – Intro

Lecture 102 DFS: InOrder – Code

Section 15: Coding Exercises

JavaScript Programmers preparing for an interview,University Students of Data Structure & Algorithm classes

Course Information:

Udemy | English | 6h 49m | 1.56 GB
Created by: Scott Barrett

You Can See More Courses in the Developer >> Greetings from CourseDown.com