Java Data Structures and Algorithms Masterclass

Description

Welcome to the Java Data Structures and Algorithms Masterclass, the most modern, and the most complete Data Structures and Algorithms in Java course on the internet.

At 45+ hours, this is the most comprehensive course online to help you ace your coding interviews and learn about Data Structures and Algorithms in Java. You will see 100+ Interview Questions done at the top technology companies such as Apple,Amazon, Google and Microsoft and how to face Interviews with comprehensive visual explanatory video materials which will bring you closer towards landing the tech job of your dreams!

Learning Java is one of the fastest ways to improve your career prospects as it is one of the most in demand tech skills! This course will help you in better understanding every detail of Data Structures and how algorithms are implemented in high level programming language.

We’ll take you step-by-step through engaging video tutorials and teach you everything you need to succeed as a professional programmer.

After finishing this course, you will be able to:

Learn basic algorithmic techniques such as greedy algorithms, binary search, sorting and dynamic programming to solve programming challenges.

Learn the strengths and weaknesses of a variety of data structures, so you can choose the best data structure for your data and applications

Learn many of the algorithms commonly used to sort data, so your applications will perform efficiently when sorting large datasets

Learn how to apply graph and string algorithms to solve real-world challenges: finding shortest paths on huge maps and assembling genomes from millions of pieces.

Why this course is so special and different from any other resource available online?

This course will take you from very beginning to a very complex and advanced topics in understanding Data Structures and Algorithms!

You will get video lectures explaining concepts clearly with comprehensive visual explanations throughout the course.

You will also see Interview Questions done at the top technology companies such as Apple,Amazon, Google and Microsoft.

I cover everything you need to know about technical interview process!

So whether you are interested in learning the top programming language in the world in-depth and interested in learning the fundamental Algorithms, Data Structures and performance analysis that make up the core foundational skillset of every accomplished programmer/designer or software architect and is excited to ace your next technical interview this is the course for you!

And this is what you get by signing up today:

Lifetime access to 44+ hours of HD quality videos. No monthly subscription. Learn at your own pace, whenever you want

Friendly and fast support in the course Q&A whenever you have questions or get stuck

FULL money back guarantee for 30 days!

This course is designed to help you to achieve your career goals. Whether you are looking to get more into Data Structures and Algorithms , increase your earning potential or just want a job with more freedom, this is the right course for you!

The topics that are covered in this course.

Section 1 – Introduction

Section 2 – Recursion

• What is Recursion?

• Why do we need recursion?

• How Recursion works?

• Recursive vs Iterative Solutions

• When to use/avoid Recursion?

• How to write Recursion in 3 steps?

• How to find Fibonacci numbers using Recursion?

Section 3 – Cracking Recursion Interview Questions

• Question 1 – Sum of Digits

• Question 2 – Power

• Question 3 – Greatest Common Divisor

• Question 4 – Decimal To Binary

Section 4 – Bonus CHALLENGING Recursion Problems (Exercises)

• power

• factorial

• productofArray

• recursiveRange

• fib

• reverse

• isPalindrome

• someRecursive

• flatten

• captalizeFirst

• nestedEvenSum

• capitalizeWords

• stringifyNumbers

• collectStrings

Section 5 – Big O Notation

• Analogy and Time Complexity

• Big O, Big Theta and Big Omega

• Time complexity examples

• Space Complexity

• Drop the Constants and the non dominant terms

• Add vs Multiply

• How to measure the codes using Big O?

• How to find time complexity for Recursive calls?

• How to measure Recursive Algorithms that make multiple calls?

Section 6 – Top 10 Big O Interview Questions (Amazon, Facebook, Apple and Microsoft)

Section 7 – Arrays

• What is an Array?

• Types of Array

• Arrays in Memory

• Create an Array

• Insertion Operation

• Traversal Operation

• Accessing an element of Array

• Searching for an element in Array

• Deleting an element from Array

• Time and Space complexity of One Dimensional Array

• One Dimensional Array Practice

• Create Two Dimensional Array

• Insertion – Two Dimensional Array

• Accessing an element of Two Dimensional Array

• Traversal – Two Dimensional Array

• Searching for an element in Two Dimensional Array

• Deletion – Two Dimensional Array

• Time and Space complexity of Two Dimensional Array

• When to use/avoid array

Section 8 – Cracking Array Interview Questions (Amazon, Facebook, Apple and Microsoft)

• Question 1 – Missing Number

• Question 2 – Pairs

• Question 3 – Finding a number in an Array

• Question 4 – Max product of two int

• Question 5 – Is Unique

• Question 6 – Permutation

• Question 7 – Rotate Matrix

Section 9 – CHALLENGING Array Problems (Exercises)

• Middle Function

• 2D Lists

• Best Score

• Missing Number

• Duplicate Number

• Pairs

Section 10 – Linked List

• What is a Linked List?

• Linked List vs Arrays

• Types of Linked List

• Linked List in the Memory

• Creation of Singly Linked List

• Insertion in Singly Linked List in Memory

• Insertion in Singly Linked List Algorithm

• Insertion Method in Singly Linked List

• Traversal of Singly Linked List

• Search for a value in Single Linked List

• Deletion of node from Singly Linked List

• Deletion Method in Singly Linked List

• Deletion of entire Singly Linked List

• Time and Space Complexity of Singly Linked List

Section 11 – Circular Singly Linked List

• Creation of Circular Singly Linked List

• Insertion in Circular Singly Linked List

• Insertion Algorithm in Circular Singly Linked List

• Insertion method in Circular Singly Linked List

• Traversal of Circular Singly Linked List

• Searching a node in Circular Singly Linked List

• Deletion of a node from Circular Singly Linked List

• Deletion Algorithm in Circular Singly Linked List

• Method in Circular Singly Linked List

• Deletion of entire Circular Singly Linked List

• Time and Space Complexity of Circular Singly Linked List

Section 12 – Doubly Linked List

• Creation of Doubly Linked List

• Insertion in Doubly Linked List

• Insertion Algorithm in Doubly Linked List

• Insertion Method in Doubly Linked List

• Traversal of Doubly Linked List

• Reverse Traversal of Doubly Linked List

• Searching for a node in Doubly Linked List

• Deletion of a node in Doubly Linked List

• Deletion Algorithm in Doubly Linked List

• Deletion Method in Doubly Linked List

• Deletion of entire Doubly Linked List

• Time and Space Complexity of Doubly Linked List

Section 13 – Circular Doubly Linked List

• Creation of Circular Doubly Linked List

• Insertion in Circular Doubly Linked List

• Insertion Algorithm in Circular Doubly Linked List

• Insertion Method in Circular Doubly Linked List

• Traversal of Circular Doubly Linked List

• Reverse Traversal of Circular Doubly Linked List

• Search for a node in Circular Doubly Linked List

• Delete a node from Circular Doubly Linked List

• Deletion Algorithm in Circular Doubly Linked List

• Deletion Method in Circular Doubly Linked List

• Entire Circular Doubly Linked List

• Time and Space Complexity of Circular Doubly Linked List

• Time Complexity of Linked List vs Arrays

Section 14 – Cracking Linked List Interview Questions (Amazon, Facebook, Apple and Microsoft)

• Linked List Class

• Question 1 – Remove Dups

• Question 2 – Return Kth to Last

• Question 3 – Partition

• Question 4 – Sum Linked Lists

• Question 5 – Intersection

Section 15 – Stack

• What is a Stack?

• What and Why of Stack?

• Stack Operations

• Stack using Array vs Linked List

• Stack Operations using Array (Create, isEmpty, isFull)

• Stack Operations using Array (Push, Pop, Peek, Delete)

• Time and Space Complexity of Stack using Array

• Stack Operations using Linked List

• Stack methods – Push , Pop, Peek, Delete and isEmpty using Linked List

• Time and Space Complexity of Stack using Linked List

• When to Use/Avoid Stack

• Stack Quiz

Section 16 – Queue

• What is a Queue?

• Linear Queue Operations using Array

• Create, isFull, isEmpty and enQueue methods using Linear Queue Array

• Dequeue, Peek and Delete Methods using Linear Queue Array

• Time and Space Complexity of Linear Queue using Array

• Why Circular Queue?

• Circular Queue Operations using Array

• Create, Enqueue, isFull and isEmpty Methods in Circular Queue using Array

• Dequeue, Peek and Delete Methods in Circular Queue using Array

• Time and Space Complexity of Circular Queue using Array

• Queue Operations using Linked List

• Create, Enqueue and isEmpty Methods in Queue using Linked List

• Dequeue, Peek and Delete Methods in Queue using Linked List

• Time and Space Complexity of Queue using Linked List

• Array vs Linked List Implementation

• When to Use/Avoid Queue?

Section 17 – Cracking Stack and Queue Interview Questions (Amazon,Facebook, Apple, Microsoft)

• Question 1 – Three in One

• Question 2 – Stack Minimum

• Question 3 – Stack of Plates

• Question 4 – Queue via Stacks

• Question 5 – Animal Shelter

Section 18 – Tree / Binary Tree

• What is a Tree?

• Why Tree?

• Tree Terminology

• How to create a basic tree in Java?

• Binary Tree

• Types of Binary Tree

• Binary Tree Representation

• Create Binary Tree (Linked List)

• PreOrder Traversal Binary Tree (Linked List)

• InOrder Traversal Binary Tree (Linked List)

• PostOrder Traversal Binary Tree (Linked List)

• LevelOrder Traversal Binary Tree (Linked List)

• Searching for a node in Binary Tree (Linked List)

• Inserting a node in Binary Tree (Linked List)

• Delete a node from Binary Tree (Linked List)

• Delete entire Binary Tree (Linked List)

• Create Binary Tree (Array)

• Insert a value Binary Tree (Array)

• Search for a node in Binary Tree (Array)

• PreOrder Traversal Binary Tree (Array)

• InOrder Traversal Binary Tree (Array)

• PostOrder Traversal Binary Tree (Array)

• Level Order Traversal Binary Tree (Array)

• Delete a node from Binary Tree (Array)

• Entire Binary Tree (Array)

• Linked List vs Python List Binary Tree

Section 19 – Binary Search Tree

• What is a Binary Search Tree? Why do we need it?

• Create a Binary Search Tree

• Insert a node to BST

• Traverse BST

• Search in BST

• Delete a node from BST

• Delete entire BST

• Time and Space complexity of BST

Section 20 – AVL Tree

• What is an AVL Tree?

• Why AVL Tree?

• Common Operations on AVL Trees

• Insert a node in AVL (Left Left Condition)

• Insert a node in AVL (Left Right Condition)

• Insert a node in AVL (Right Right Condition)

• Insert a node in AVL (Right Left Condition)

• Insert a node in AVL (all together)

• Insert a node in AVL (method)

• Delete a node from AVL (LL, LR, RR, RL)

• Delete a node from AVL (all together)

• Delete a node from AVL (method)

• Delete entire AVL