## What you would learn in Java Data Structures and Algorithms Masterclass

## course?

- Learn, implement, and use different Data Structures
- Learn, implement and use different Algorithms
- Become a better developer by mastering computer science fundamentals
- Learn everything you need to ace difficult coding interviews
- Cracking the Coding Interview with 100+ questions with explanations
- Time and Space Complexity of Data Structures and Algorithms
- Recursion
- Big O
- Dynamic Programming
- Divide and Conquer Algorithms
- Graph Algorithms
- Greedy Algorithms

### Course Content:

## Requirements

- Basic Java Programming skills

## 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 **44+ 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 detailof 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**

What are Data Structures?

What is an algorithm?

Why are Data Structures and Algorithms important?

Types of Data Structures

Types of Algorithms

**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)**

Product and Sum

Print Pairs

Print Unordered Pairs

Print Unordered Pairs 2 Arrays

Print Unordered Pairs 2 Arrays 100000 Units

Reverse

O(N) Equivalents

Factorial Complexity

Fibonacci Complexity

Powers of 2

**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

Time and Space complexity of AVL Tree

**Section 21 - Binary Heap**

What is Binary Heap? Why do we need it?

Common operations (Creation, Peek, sizeofheap) on Binary Heap

Insert a node in Binary Heap

Extract a node from Binary Heap

Delete entire Binary Heap

Time and space complexity of Binary Heap

**Section 22 - Trie**

What is a Trie? Why do we need it?

Common Operations on Trie (Creation)

Insert a string in Trie

Search for a string in Trie

Delete a string from Trie

Practical use of Trie

**Section 23 - Hashing**

What is Hashing? Why do we need it?

Hashing Terminology

Hash Functions

Types of Collision Resolution Techniques

Hash Table is Full

Pros and Cons of Resolution Techniques

Practical Use of Hashing

Hashing vs Other Data structures

**Section 24 - Sort Algorithms**

What is Sorting?

Types of Sorting

Sorting Terminologies

Bubble Sort

Selection Sort

Insertion Sort

Bucket Sort

Merge Sort

Quick Sort

Heap Sort

Comparison of Sorting Algorithms

**Section 25 - Searching Algorithms**

Introduction to Searching Algorithms

Linear Search

Linear Search in Python

Binary Search

Binary Search in Python

Time Complexity of Binary Search

**Section 26 - Graph Algorithms**

What is a Graph? Why Graph?

Graph Terminology

Types of Graph

Graph Representation

Graph in Java using Adjacency Matrix

Graph in Java using Adjacency List

**Section 27 - Graph Traversal**

Breadth First Search Algorithm (BFS)

Breadth First Search Algorithm (BFS) in Java - Adjacency Matrix

Breadth First Search Algorithm (BFS) in Java - Adjacency List

Time Complexity of Breadth First Search (BFS) Algorithm

Depth First Search (DFS) Algorithm

Depth First Search (DFS) Algorithm in Java - Adjacency List

Depth First Search (DFS) Algorithm in Java - Adjacency Matrix

Time Complexity of Depth First Search (DFS) Algorithm

BFS Traversal vs DFS Traversal

**Section 28 - Topological Sort**

What is Topological Sort?

Topological Sort Algorithm

Topological Sort using Adjacency List

Topological Sort using Adjacency Matrix

Time and Space Complexity of Topological Sort

**Section 29 - Single Source Shortest Path Problem**

SWhat is Single Source Shortest Path Problem?

Breadth First Search (BFS) for Single Source Shortest Path Problem (SSSPP)

BFS for SSSPP in Java using Adjacency List

BFS for SSSPP in Java using Adjacency Matrix

Time and Space Complexity of BFS for SSSPP

Why does BFS not work with Weighted Graph?

Why does DFS not work for SSSP?

**Section 30 - Dijkstra's Algorithm**

Dijkstra's Algorithm for SSSPP

Dijkstra's Algorithm in Java - 1

Dijkstra's Algorithm in Java - 2

Dijkstra's Algorithm with Negative Cycle

**Section 31 - Bellman Ford Algorithm**

Bellman Ford Algorithm

Bellman Ford Algorithm with negative cycle

Why does Bellman Ford run V-1 times?

Bellman Ford in Python

BFS vs Dijkstra vs Bellman Ford

**Section 32 - All Pairs Shortest Path Problem**

All pairs shortest path problem

Dry run for All pair shortest path

**Section 33 - Floyd Warshall**

Floyd Warshall Algorithm

Why Floyd Warshall?

Floyd Warshall with negative cycle,

Floyd Warshall in Java,

BFS vs Dijkstra vs Bellman Ford vs Floyd Warshall,

**Section 34 - Minimum Spanning Tree**

Minimum Spanning Tree,

Disjoint Set,

Disjoint Set in Java,

**Section 35 - Kruskal's and Prim's Algorithms**

Kruskal Algorithm,

Kruskal Algorithm in Python,

Prim's Algorithm,

Prim's Algorithm in Python,

Prim's vs Kruskal

**Section 36 - Cracking Graph and Tree Interview Questions (Amazon,Facebook, Apple, Microsoft)**

**Section 37 - Greedy Algorithms**

What is Greedy Algorithm?

Well known Greedy Algorithms

Activity Selection Problem

Activity Selection Problem in Python

Coin Change Problem

Coin Change Problem in Python

Fractional Knapsack Problem

Fractional Knapsack Problem in Python

**Section 38 - Divide and Conquer Algorithms**

What is a Divide and Conquer Algorithm?

Common Divide and Conquer algorithms

How to solve Fibonacci series using Divide and Conquer approach?

Number Factor

Number Factor in Java

House Robber

House Robber Problem in Java

Convert one string to another

Convert One String to another in Java

Zero One Knapsack problem

Zero One Knapsack problem in Java

Longest Common Sequence Problem

Longest Common Subsequence in Java

Longest Palindromic Subsequence Problem

Longest Palindromic Subsequence in Java

Minimum cost to reach the Last cell problem

Minimum Cost to reach the Last Cell in 2D array using Java

Number of Ways to reach the Last Cell with given Cost

Number of Ways to reach the Last Cell with given Cost in Java

**Section 39 - Dynamic Programming**

What is Dynamic Programming? (Overlapping property)

Where does the name of DC come from?

Top Down with Memoization

Bottom Up with Tabulation

Top Down vs Bottom Up

Is Merge Sort Dynamic Programming?

Number Factor Problem using Dynamic Programming

Number Factor : Top Down and Bottom Up

House Robber Problem using Dynamic Programming

House Robber : Top Down and Bottom Up

Convert one string to another using Dynamic Programming

Convert String using Bottom Up

Zero One Knapsack using Dynamic Programming

Zero One Knapsack - Top Down

Zero One Knapsack - Bottom Up

**Section 40 - CHALLENGING Dynamic Programming Problems**

Longest repeated Subsequence Length problem

Longest Common Subsequence Length problem

Longest Common Subsequence problem

Diff Utility

Shortest Common Subsequence problem

Length of Longest Palindromic Subsequence

Subset Sum Problem

Egg Dropping Puzzle

Maximum Length Chain of Pairs

**Section 41 - A Recipe for Problem Solving**

Introduction

Step 1 - Understand the problem

Step 2 - Examples

Step 3 - Break it Down

Step 4 - Solve or Simplify

Step 5 - Look Back and Refactor

**Section 41 - Wild West**

## Who this course is for:

- Anybody interested in learning more about data structures and algorithms or the technical interview process!
- Self-taught programmers who have a basic knowledge in Java and want to be professional in Data Structure and Algorithm and begin interviewing in tech positions!
- Students currently studying computer science and want supplementary material on Data Structure and Algorithm and interview preparation for after graduation!
- Professional programmers who need practice for upcoming coding interviews.

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