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    About JAVA Foundation with DSA & Algo Combo Course

  • Curriculum Walkthrough
  • What is a Data Structure?
  • What is an Algorithm?
  • Why Are Data Structures and Algorithms Important?
  • Types of Data Structures
  • Types of Algorithms
  • Lecture Notes
  • Motivation

  • What is Big O?
  • Big O Notations (Big O, Big Omega, Big Theta)
  • Big O - O(1)
  • Big O - O(N)
  • Drop Constants
  • Big O - O(N²)
  • Drop Non-Dominant Terms
  • Big O - O(log N)
  • Add vs Multiply
  • Space Complexity
  • How to Measure the Code using Big O?

  • Types of Arrays
  • Arrays in Memory
  • Create an Array
  • Insertion in Array
  • Accessing Elements in Array
  • Array Traversal
  • Search for Array Element
  • Delete Array Element
  • Time and Space Complexity of 1D Arrays
  • Create Two Dimensional Array
  • Insertion - Two Dimensional Array
  • Accessing Two Dimensional Array Element
  • Traverse Two Dimensional Array
  • Searching Two Dimensional Array
  • Delete Two Dimensional Array Element
  • Time and Space Complexity of 2D Arrays
  • When to Use/Avoid Arrays

  • Goals - What You Will Make by the End of This Section
  • Calculate Average Temperature
  • Find the Days Above Average Temperature

  • Middle Function
  • Solution to Middle Function
  • 2D Arrays
  • Solution to 2D Arrays
  • Best Score
  • Solution to Best Score
  • Missing Number
  • Solution to Missing Number
  • Duplicate Number
  • Solution to Duplicate Number
  • Remove Duplicates from Sorted Array - LeetCode 26
  • Solution to Remove Duplicates from Sorted Array - LeetCode 26
  • Best Time to Buy and Sell Stock - LeetCode 121
  • Solution to Best Time to Buy and Sell Stock - LeetCode 121
  • Two Sum - LeetCode 1
  • Solution to Two Sum - LeetCode 1
  • Finding a Number in an Array
  • Solution - Finding a Number in an Array
  • Max Product of Two Integers
  • Solution - Max Product of Two Integers
  • IsUnique / Contains Duplicate - LeetCode 217
  • Solution - IsUnique / Contains Duplicate - LeetCode 217
  • Permutation
  • Solution - Permutation
  • Rotate Matrix
  • Rotate Matrix / Image - LeetCode 48

  • What is ArrayList?
  • ArrayList in Memory
  • Creating ArrayList
  • Insertion in ArrayList
  • Accessing Elements in ArrayList
  • Traversal of ArrayList
  • Search for an Element in ArrayList
  • Delete an Element from ArrayList
  • Time and Space Complexity of ArrayList

  • Question 1 - Time Complexity of Method that returns Sum and Product of Array
  • Question 2 - Time Complexity of Print Pairs Method
  • Question 3 - Time Complexity of Print Unordered Pairs Method
  • Question 4 - Find Time Complexity for Given Method
  • Question 5 - Find Time Complexity for Given Method
  • Question 6 - Time Complexity of Reverse Array Function
  • Question 7 - Equivalent to O(N)

  • What is a Linked List?
  • Linked List vs Array
  • Types of Linked List
  • Linked List in the Memory
  • Creation of Singly Linked List
  • Insertion in Singly Linked List in Memory
  • Insertion Algorithm in Singly Linked List
  • Insertion Method in Singly Linked List
  • Traversal of Singly Linked List
  • Searching in Singly Linked List
  • Deletion of a 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

  • Singly Linked List - Push
  • Solution to Singly Linked List - Push
  • Singly Linked List - Pop
  • Solution to Singly Linked List - Pop
  • Singly Linked List - Insert
  • Solution to Singly Linked List - Insert
  • Singly Linked List - Get
  • Solution to Singly Linked List - Get
  • Singly Linked List - Rotate
  • Solution to Singly Linked List - Rotate
  • Singly Linked List - Set
  • Solution to Singly Linked List - Set
  • Singly Linked List - Remove
  • Solution to Singly Linked List - Remove

  • Create 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
  • Deletion Method in Circular Singly Linked List
  • Delete Entire Circular Singly Linked List
  • Time and Space Complexity of Circular Singly Linked List

  • Implement a Circular Singly Linked List
  • Solution - Implement a Circular Singly Linked List
  • Delete a Node from a Circular Singly Linked List
  • Solution - Delete a Node from a Circular Singly Linked List
  • Count the Number of Nodes

  • Create 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
  • Delete Entire Doubly Linked List
  • Time and Space Complexity of Doubly Linked List

  • Create 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
  • Deletion in Circular Doubly Linked List
  • Deletion Algorithm in Circular Doubly Linked List
  • Deletion Method in Circular Doubly Linked List
  • Delete Entire Circular Doubly Linked List
  • Time and Space Complexity of Circular Doubly Linked List
  • Time Complexity of Array vs Linked List

  • Linked List Class
  • Remove Dups
  • Solution - Remove Dups
  • Return Nth to Last
  • Solution - Return Nth to Last
  • Partition
  • Solution - Partition
  • Sum Lists
  • Solution - Sum Lists
  • Intersection

  • 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

  • Implement Stack
  • Solution and Explanation - Implement Stack Class
  • Push Method
  • Solution and Explanation - Push Method
  • Pop Method
  • Solution/Explanation and Time/Space Complexity - Pop Method
  • Balanced Parentheses Checker

  • 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?

  • Goals
  • Three in One
  • Solution - Three in One
  • Stack Minimum
  • Solution - Stack Minimum
  • Stack of Plates
  • Solution Part 1 - Stack of Plates
  • Solution Part 2 - Stack of Plates
  • Solution Part 3 - Follow UP
  • Queue via Stacks
  • Solution - Queue via Stacks
  • Animal Shelter

  • Goals: what you will learn by the end of this section
  • What is Recursion?
  • Why do we need Recursion?
  • The Logic Behind Recursion
  • Recursive vs Iterative Solution
  • When to Use/Avoid Recursion?
  • How to Write Recursion in 3 Steps?
  • Fibonacci Series using Recursion
  • How to Measure Recursive Algorithm?
  • How to Measure Recursive Algorithm with Multiple Calls?

  • Question 1 - Sum of Digits
  • Question 2 - Power
  • Question 3 - GCD
  • Question 4 - Decimal to Binary

  • Important Note!
  • Power
  • Factorial
  • Product of Array
  • RecursiveRange
  • Fib
  • Solutions Part 1
  • Reverse
  • IsPalindrome
  • SomeRecursive
  • First Uppercase

  • What is a Tree?
  • Why Tree?
  • Tree Terminology
  • Creating a Basic Tree in Java
  • What is A Binary Tree?
  • Types of Binary Tree
  • Binary Tree Representation
  • Create Binary Tree using Linked List
  • PreOrder Traversal in Binary Tree using Linked List
  • InOrder Traversal in Binary Tree using Linked List
  • PostOrder Traversal in Binary Tree using Linked List
  • LevelOrder Traversal in Binary Tree using Linked List
  • Search Method in Binary Tree (Linked List)
  • Insert Method in Binary Tree (Linked List)
  • Delete a Node in Binary Tree (Linked List)
  • Delete Entire Binary Tree (Linked List)
  • Create Binary Tree (Array)
  • Insert Method Binary Tree (Array)
  • PreOrder Traversal Binary Tree (Array)
  • InOrder Traversal Binary Tree (Array)
  • PostOrder Traversal Binary Tree (Array)
  • LevelOrder Traversal Binary Tree (Array)
  • Search Method Binary Tree (Array)
  • Delete a Node Binary Tree (Array)
  • Delete Binary Tree (Array)
  • Array vs Linked List in Binary Tree Implementation

  • Implement Binary Tree
  • In-Order Traversal (Iterative)
  • Solution to In-Order Traversal (Iterative) / Time and Space Complexity
  • Pre-Order Traversal (Iterative)
  • Solution to Pre-Order Traversal (Iterative) / Time and Space Complexity
  • Post-Order Traversal (Iterative)

  • What is a Binary Search Tree? Why do we need it?
  • Create Binary Search Tree
  • Insert a Node to Binary Search Tree
  • PreOrder Traversal Binary Search Tree
  • InOrder Traversal Binary Search Tree
  • PostOrder Traversal Binary Search Tree
  • Level Order Traversal Binary Search Tree
  • Search in Binary Search Tree
  • Delete a Node in Binary Search Tree
  • Delete BST
  • Time and Space Complexity of BST

  • What is an AVL Tree?
  • Why Do We Need AVL Tree?
  • Common Operations on AVL Tree
  • 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 in Practice)
  • Delete a Node from AVL (LL, LR, RR, RR)
  • Delete a Node from ALL (All Together)
  • Delete a Node from AVL (Method in practice)
  • Delete Entire AVL Tree
  • Time and Space Complexity of AVL
  • Binary Search Tree vs AVL

  • What is Binary Heap? Why do we need Binary Heap?
  • Common Operations 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

  • What is a Trie? Why we need Trie?
  • Common Operations on a Trie (Creation)
  • Insert a String in Trie
  • Search for a String in Trie
  • Delete a String from Trie
  • Practical Uses of Trie

  • What is Hashing? Why we need it?
  • Hashing Terminology
  • Hash Functions
  • Types of Collision Resolution Techniques - Direct Chaining (Insert)
  • Direct Chaining Implementation - (Search, Delete)
  • Hash Table is Full
  • Collision Resolution Technique - Linear Probing (Insert)
  • Collision Resolution Technique - Linear

  • What is Sorting?
  • Types of Sorting
  • Sorting Terminology
  • Bubble Sort
  • Selection Sort
  • Insertion Sort
  • Bucket Sort
  • Merge Sort
  • Quick Sort
  • Heap Sort
  • Comparison of Sorting Algorithms

  • Introduction to Search Algorithms
  • Linear Search
  • Linear Search in Java
  • Binary Search
  • Binary Search in Java
  • Time Complexity of Binary Search

  • What you will learn
  • What is a graph? Why do we need graphs?
  • Graph terminology
  • Types of graphs
  • Graph representation
  • Graph in Java using adjacency matrix
  • Graph in Java using adjacency list

  • 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

  • What is Topological Sort?
  • Topological Sort Algorithm
  • Topological Sort using Adjacency List
  • Topological Sort using Adjacency Matrix
  • Time and Space Complexity of Topological Sort

  • What 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?

  • Dijkstra's Algorithm for SSSPP
  • Dijkstra's Algorithm in Java  
  • Dijkstra's Algorithm with Negative Cycle

  • Bellman Ford Algorithm for SSSPP
  • Bellman Ford Algorithm with Negative Cycle
  • Why Bellman Ford runs V-1 times?
  • Bellman Ford Algorithm Implementation in Java
  • BFS vs Dijkstra vs Bellman Ford

  • What is All Pairs Shortest Path Problem?
  • Dry Run for All Pairs Shortest Path Problem

  • Floyd Warshall Algorithm
  • Why Floyd Warshall Algorithm?
  • Floyd Warshall with Negative Cycle
  • Floyd Warshall in Java
  • BFS vs Dijkstra vs Bellman Ford vs Floyd Warshall Algorithms

  • What is Minimum Spanning Tree?
  • What is Disjoint Set?
  • Disjoint Set in Java

  • What is Minimum Spanning Tree?
  • What is Disjoint Set?
  • Disjoint Set in Java
  • Kruskal Algorithm
  • Kruskal Algorithm in Java
  • Prim's Algorithm
  • Prim's Algorithm in Java
  • Kruskal vs Prim's Algorithms

  • Introduction
  • Route Between Nodes
  • Solution to Route Between Nodes
  • Minimal Tree
  • Solution to Minimal Tree
  • Check Balanced
  • Solution to Check Balanced
  • Validate BST
  • Solution to Validate BST
  • Successor
  • Solution to Successor
  • Build Order

  • What is Greedy Algorithm?
  • Known Greedy Algorithms
  • Activity Selection Problem
  • Activity Selection Problem in Java
  • Coin Change Problem
  • Coin Change Problem in Java
  • Fractional Knapsack Problem
  • Fractional Knapsack Problem in Java

  • 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 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 Subsequence Problem
  • Longest Common Subsequence Problem in Java
  • Longest Palindromic Subsequence Problem
  • Longest Palindromic Subsequence Problem in Java
  • Minimum Cost to Reach Last Cell
  • Minimum Cost to Reach Last Cell in Java
  • Number of Paths To Reach The Last Cell with Given Cost
  • Number of Paths To Reach The Last Cell with Given Cost in Java

  • Divide and Conquer - countZeroes
  • Solution to Divide and Conquer - countZeroes
  • Divide and Conquer - sortedFrequency
  • Solution to Divide and Conquer - sortedFrequency
  • Divide and Conquer - findRotatedIndex

  • What is Dynamic Programming? (Overlapping property)
  • Where Does the Name of DP 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 Approach
  • Number Factor Bottom Up Approach
  • Number Factor: Top Down and Bottom Up
  • House Robber Problem using Dynamic Programming
  • House Robber Top Down Approach
  • House Robber Bottom Up Approach
  • Convert one string to another using Dynamic Programming
  • Convert One String to Another using Top Down Approach
  • Convert One String to Another using Bottom Up Approach

  • 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

  • What is Backtracking?
  • Backtracking vs Brute Force
  • Backtracking Quiz
  • N - Queens Problem
  • N - Queens Problem in Java
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    Frequently Asked Question

    About JAVA Foundation with DSA & Algo Combo Course

    About JAVA Foundation with DSA & Algo Combo Course:
    This online JAVA Foundation with DSA & Algo Combo Course certification course gives you an in-depth understanding and advanced knowledge of the eight most important JAVA Foundation with DSA & Algo Combo Course domains and includes real-world projects for gaining domain experience to help you become industry-ready. You’ll be exposed to 30 JAVA Foundation with DSA & Algo Combo Course tools extensive project experience and a JAVA Foundation with DSA & Algo Combo Course capstone project to make you job-ready.
    Course Objectives:
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    There’s no denying that cloud-based apps now become the future in today’s tech-dominating landscape. As most of the industries are aggressively adopting the best cloud-based solutions, the demand for skilled JAVA Foundation with DSA & Algo Combo Course professionals has been increased worldwide.The reasons behind the popularity of JAVA Foundation with DSA & Algo Combo Course are as follows:
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