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Skillshare

Data Structures and Algorithms using C++ : Zero To Mastery 2023!

via Skillshare

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Overview

You may be new to Data Structure or you have already Studied and Implemented Data Structures but still you feel you need to learn more about Data Structure in detail so that it helps you solve challenging problems and used Data Structure efficiently.

 Every Data Structure is discussed, analysed and implemented with a Practical line-by-line coding.

After completing this course, you will have a solid understanding of data structures and algorithms (both the theory, and the implementation).

Here's why this course is worth your time:

  • It's interactive - I give you a chance to try every problem before I show you my solution.

  • Every single problem has a complete solution walk through video as well as accompanying solution file.

  • I cover helpful "tips and tricks" to solve common problems, but we also focus on building an approach to ANY problem.

Are you looking to level-up your developer skills? Sign up today!

Syllabus

  • Introduction to Course
  • Introduction to recursion
  • Recursion and pmi
  • Fibonaci Numbers
  • Power
  • Print Numbers
  • count Digits
  • sum of digits
  • multiplication
  • count zeroes
  • geometric sum
  • Check if Array is sorted
  • Sum of Array
  • Check if element is present
  • First Index of element
  • Last Index of element
  • Print All position of element
  • Count Occurence of element First Approach
  • Count Occurence of element Second Approach
  • Store All Position of element
  • Check Palindrome
  • print and reverse print
  • Length Recursively
  • Replace Character Recursively
  • Remove Character Recursively
  • Remove Consecutive Duplicates
  • Print All Subsequences of String
  • Store All Subsequences of String
  • Convert String to Integer
  • Print All Permutation of String
  • Staircase Problem
  • Tower of Hanoi
  • Print Steps in Tower of Hanoi
  • Merge Sort Introduction
  • Merge Sort Solution
  • Quick Sort Introduction
  • Quick Sort Solution
  • Quick Sort Testing
  • Experimental Analysis
  • Theoretical Analysis
  • Linear Searrch Time Complexity
  • Selection Sort TIme Complexity
  • Theoretical Analysis Recursive Algo
  • Merge Sort Time Complexity
  • Fibonacci Time Complexity
  • Space Complexity Analysis
  • Merge Sort Space Complexity
  • Fibonacci Space Complexity
  • What are Data Structures
  • What is Linked List
  • Print a LInkedList
  • takeInput
  • takeInput2
  • length
  • printIthNode
  • Insert Node at ith pos question
  • Insert Node at ith pos solution
  • deleteithNode question
  • deleteithNode solution with memory leak
  • deleteithNode solution without memory leak
  • length recursive
  • find element
  • find element recursive
  • mid point of LL
  • reverse a list
  • remove kth node from end of ll
  • merge two sorted LL
  • merge two sorted LL recursive
  • merge sort LL
  • Doubly LL
  • circular singly list
  • circular doubly list
  • Stack Introduction
  • Stack Implementation using Array Part 1
  • Stack Implementation using Array Part 2
  • Dynamic Stack
  • templates
  • Stack using Templates
  • Stack using LL introduction
  • Stack using LL solution
  • Inbuilt Stack
  • Queue Introduction
  • Queue using Array Introduction
  • Queue using Array Code
  • Dynamic Queue
  • Queue using LL introduction
  • Queue using LL solution
  • Inbuilt Queue
  • Reverse a queue
  • Trees Introduction
  • Vectors
  • TreeNode Class
  • Print Recursive
  • Take Input Recursive
  • Take Input Level Wise
  • Level Order Print Introduction
  • Level Order Print Solution
  • Count Nodes
  • Height of a Tree
  • Print All Nodes at Level K
  • Count Leaf Nodes
  • PreOrder Traversal
  • PostOrder Traversal
  • Delete Tree
  • Destructor
  • Binary Tree Introduction
  • Print Tree Recusrive
  • Take Input Recursive
  • Take Input Level Wise
  • level order traversal
  • Count Nodes leetcode
  • Binary Tree Inorder Traversal
  • Binary Tree PreOrder Traversal
  • Binary Tree PostOrder Traversal
  • maxDepth of binary tree
  • Symmetric Binary Tree
  • Find Node
  • Min Value
  • Max Value
  • Count Leaf Nodes
  • Construct Tree from PreOrder and Inorder Traversal Introduction
  • Construct Tree from PreOrder and Inorder Traversal Solution
  • Construct Tree from PostOrder and Inorder Traversal Introduction
  • Construct Tree from PostOrder and Inorder Traversal Solution
  • Diameter of Binary Tree
  • Diameter of Binary Tree Better Approach
  • Root to Node Path
  • BST Introduction
  • Search in BST
  • Min Node in BST
  • Find Max in BST
  • Range Sum Of BST
  • Validate Binary Search Tree
  • Convert Sorted Array to BST
  • BST Class Implementation
  • BST class How to Insert
  • BST class Insert Implementation
  • BST class How to Delete
  • BST class Delete Implementation
  • Convert BST to sorted singly list
  • Convert BST to sorted singly list solution
  • Types of balanced BST
  • Introduction to hashmap
  • Inbuilt Hashmap
  • Rremove Duplicates
  • iterators
  • Bucket Array and Hash Function
  • collision handling
  • HashMap Implementation Insert
  • HashMap Implementation delete&search
  • Time Complexity & Load Factor
  • rehashing
  • Introduction to Priority Queue
  • ways to implement priority queue
  • Heaps Introduction
  • CBT and its implementation
  • Insert & Delete in Heaps
  • Example Solution & Max Heap
  • Implementation of Priority Queue Part 1
  • Implementation Insert
  • Remove Min Explanation
  • Remove Min Solution & Complexity Analysis
  • Inplace Heap Sort
  • Inplace Heap Sort Solution
  • Inbuilt Priority Queue
  • K sorted Array
  • K smallest element
  • Inbuilt Min PQ
  • Fibonaci
  • Hint Minimum Steps to 1
  • minimum steps to 1 brute force mathod
  • minimum steps to 1 memorization method
  • minimum steps to 1 bottom up method
  • Graph Introduction
  • Graph Terminology
  • Graph Implementation
  • Adjacency Matrix
  • DFS Traversal
  • BFS Traversal
  • BFS Traversal Solution
  • DFS for disconnected graph
  • BFS for disconnected graph
  • No of Connected Component
  • DFS to find No of Connected component
  • BFS to find No of Connected component

Taught by

Harsh Kajla

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