Data Structures in JavaScript: Master The Fundamentals
Created by Eduonix Learning Solutions, Last Updated 08-Nov-2019, Language:English
Data Structures in JavaScript: Master The Fundamentals
Learn the fundamentals of computer programming using JavaScript data structures
Created by Eduonix Learning Solutions, Last Updated 08-Nov-2019, Language:English
What Will I Get ?
- Learn fundamental concepts of Data Structures and Algorithms
- Learn to implement popular data structures in JavaScript
- Learn how data structures are used for creating software
Requirements
- Basic knowledge of JavaScript is required for completing this course
Description
If you want to be a good programmer or want to build good software, then the knowledge of data structures and their role in software development becomes essential. Data Structure is basically a process for collecting and organizing the data in the best way possible for performing operations efficiently. They form the fundamentals of computer science. With a good understanding of data structure, we master the way of organizing and storing data for a specific purpose. This course is aimed for helping you understand the core concepts behind these data structures and how they are used to build algorithms that solve business problems.
Why this course is important?
This course gives insight into the data science and algorithms in JavaScript covering all the essential topics. It unfolds with the basic introduction, then covers all the aspects of arrays such as arrays vs lists, common array iterations, array functions and others. Following this, lists, big o time space asymptomatic analysis, linked lists and stacks are also covered in details. Lastly, introduction to queues, its implementation, various aspects of recursion, trees, hash maps and graphs are also covered for the complete understanding of data science and algorithms.
This course includes-
1. Introduction to the data structure
2. Arrays, common array comparisons, array functions, searching arrays, 2d arrays, iterating over 2d arrays, Minesweeper challenge, minesweeper solution and others
3. Lists, implementing list push, implementing list remove and so on
4. Big o time space asymptomatic analysis- its introduction, big o of n squared, no constants, big o challenge and big o solution
5. Linked lists, coding linked lists, linked list class, remove at index and add at index
6. Stacks- introduction, implementation, stack out of linked list, stack out of array, condense challenge and others
7. Queues, recursion, trees, hash maps, graphs and much more important things!
Get started with this course now to learn data structures and algorithms for acing any job interview or building better software!
Who this course is for:
- Anyone who wants to learn software engineering will find this course very useful
- Learn to build better software with conceptual understanding of the fundamental data structures.
Course Content
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Introduction
1 Lectures 00:01:07-
Introduction
Preview00:01:07
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Arrays
14 Lectures 02:42:47-
Arrays vs Lists
Preview00:04:28 -
Common Array Iterations
Preview00:24:45 -
Pairwise Array Comparisons
Preview00:16:02 -
Array Functions
Preview00:09:10 -
Searching Arrays
00:10:08 -
Is Sorted Challenge
00:02:00 -
Is Sorted Solution
00:10:20 -
2d Arrays
00:09:33 -
Iterating Over 2d Arrays
00:05:20 -
2d Bounds Checking
00:28:28 -
Minesweeper Challenge
00:06:55 -
Mnesweeper Solution
00:10:38 -
Tally Sort Challenge
00:09:43 -
Tally Sort Solution
00:15:17
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Lists
9 Lectures 01:14:24-
Lists Out of Arrays
00:16:13 -
Implementing List Push and Grow
00:20:40 -
Implementing List Remove
00:13:59 -
Implement List Insert
00:06:19 -
List Contains Challenge
00:02:39 -
List Contains Solution
00:02:44 -
List Get and Set
00:03:28 -
Concat Challenge
00:02:53 -
Concat Solution
00:05:29
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Big o Time Space Asymptotic Analysis
6 Lectures 00:42:14-
Intro to Big o
00:13:41 -
Big o of n Squared
00:11:22 -
Timing Big o of one Versus n Versus n Squared
00:08:08 -
No Constants- n Big o Notation
00:05:05 -
Big o Challenge
00:00:26 -
Big o Solution
00:03:32
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Linked Lists
10 Lectures 02:06:18-
Linked Lists
00:08:53 -
Coding Linked Lists
00:13:00 -
Linked List Manipulation Challenge
00:16:24 -
Linked List Manipulation Solution
00:16:30 -
Linked List Class
00:13:37 -
Get at Index
00:09:00 -
Remove at Index
00:22:17 -
Add at Index
00:11:21 -
Summarizing Arrays vs Linked Lists
00:06:54 -
Prefer Manipulating Pointers to Copying Data
00:08:22
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Stacks
11 Lectures 01:23:45-
Intro to Stacks
00:06:26 -
Stack Implementations
00:04:09 -
Stack out of Linked List
00:05:44 -
Stack out of Array
00:07:01 -
Balance Parenthesis Challenge
00:06:30 -
Balance Parenthesis Solution
00:07:25 -
Paren Bracket Curly Balance Challenge
00:04:44 -
Paren Bracket Curly Balance Solution
00:08:35 -
Condense Challenge
00:03:42 -
Condense Inefficient Solution
00:13:34 -
Condense Efficient Solution
00:15:55
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-
Queues
7 Lectures 00:58:05-
Intro to Queues
00:08:21 -
Implementing a Queue
00:10:20 -
Josephus Challenge
00:05:03 -
Josephus Solution
00:11:21 -
Sieve of Eratosthenes Challenge
00:07:27 -
Sieve of Eratosthenes Solution
00:06:38 -
Native js Arrays Stacks and Queues
00:08:55
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Recursion
6 Lectures 01:21:15-
Intro to Recursion
00:27:40 -
Recursive Fibonacci
00:27:00 -
Palindrome Challenge
00:05:27 -
Palindrome Hints
00:03:42 -
Palindrome Solution
00:09:22 -
Palindrome Bonus
00:08:04
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Trees
17 Lectures 01:54:43-
Intro to Trees
00:03:46 -
Iterating Over Trees
00:19:16 -
Tree Sum Challenge
00:02:43 -
Tree Sum Solution
00:05:02 -
Tree Contains Challenge
00:00:42 -
Tree Contains Solution
00:04:22 -
Tree Size Leaves Challenge
00:01:27 -
Tree Size Leaves Solution
00:03:54 -
Tree Min Max Height Challenge
00:03:04 -
Tree Min Max Height Solution
00:11:25 -
Binary Search Trees
00:12:24 -
Binary Search Tree Add
00:16:19 -
Binay Search Tree Contains Challenge
00:01:24 -
Binary Search Tree Contains Solution
00:05:39 -
Unbalanced Binary Search Trees
00:08:00 -
Morse Code Challenge
00:04:42 -
Morse Code Solution
00:10:34
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Hash Maps
4 Lectures 01:03:33-
Intro to Hash Maps
00:26:21 -
Handling Collisions with Linear Probing
00:25:52 -
Handling Collisions by Chaining Linked Lists
00:03:15 -
Coding Linked List Collisions
00:08:05
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Graphs
3 Lectures 00:35:21-
Intro to Graphs
00:11:59 -
Coding a Graph Class
00:09:26 -
Breadth First and Depth First Traversals
00:13:56
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