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How can I learn Data Structure & Algorithms(DSA) online for free?

Learning Should Not Stop: Learn online (FREE) from Goeduhub and Get training certificate at the end. This page contain information for online free training in DSA Using Python.

In the Outbreak of COVID-19, we want you to stay safe, stay home and use the best of your abilities to learn. Join Winter Online Live Internship Program-2020. Join Goeduhub to work on a real-time industrial-based Online Live Internship Program.

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 Technology: Data Structure & Algorithms(DSA) with Python
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Data Structures and Algorithms using Python

Data Structures and Algorithms are the building blocks for computer science and hence are among the essential topics for any programmer. DSA helps you understand a problem at a deeper level and is very much in demand in the job Market. Our Data Structures and Algorithms course is tailored in such a way that they are easy to learn and master. This will position you better for a job search, placements and will help you in your job. Here is a brief summary of the content.

  • Basics of algorithms, stacks, queues, Linked List, graphs, trees, and heap
  • Sorting Algorithms, Searching Algorithms, 1D & 2D Arrays, and Binary Tree
  • Divide and Conquer Algorithms and Dynamic Programming
  • Coding Questions and MCQ Questions in both Practice and Assessment mode
  • Assignment after every class
  • Valid certification on successful completion of the course 

2 Answers

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Best answer

Detailed Course Content:- 

DSA Online Training Program: PART-1

1) Introduction and Analysis of Algorithms

  • Data Types
  • Data Structures
  • Abstract Data Types (ADTs) 
  • Algorithm o Analysis of Algorithms 
  • Asymptotic Notation 
  • Master Theorem for Divide and Conquer Recurrences
  • Divide and Conquer Master Theorem: Problems & Solutions 
  • Master Theorem for Subtract and Conquer Recurrences

2) Searching Algorithms

  • Linear Search
  • Binary Search

3) Sorting Algorithms

  • Bubble Sort 
  • Insertion Sort
  • Selection Sort
  • Merge Sort
  • Quick Sort
  • Counting Sort
  • Radix Sort
  • Heap Sort

4) Linked List

Singly Linked List

  • Linked List in Data Structure
  • Singly Linked List in
    • Insertion in singly Linked List
    • Insertion at beginning in singly Linked List 
    • Insertion at nth position in singly Linked List 
    • Insertion at end in singly Linked List 
  • Deletion in singly Linked List 
    • Deletion from beginning in singly linked list : 
    • Deletion from nth position in singly linked list : 
    • Deletion from end in singly linked list : 
  • Reverse a linked list without changing links between nodes (Data reverse only)  Reverse a linked list by changing links between nodes 
  • Print reverse of a linked list without actually reversing 
  • Search an element in a linked list 
  • Insertion in a Sorted Linked List 
  • Delete alternate nodes of a Linked List 
  • Find middle of the linked list
  • Reverse a linked list in groups of given size 
  • Find kth node from end of the linked list 
  • Append the last n nodes of a linked list to the beginning of the list 
  • Check whether linked list is palindrome or not 
  • Fold a Linked List 

Doubly Linked List

  • Introduction to Doubly Linked list in Data Structure
  • Doubly Linked List in
  • Insertion in doubly linked list
    • Insertion at beginning in doubly linked list
    • Insertion at end in doubly linked list
    • Insertion at nth node in doubly linked list
  • Deletion in doubly linked list  
    • Deletion from beginning in doubly linked list
    • Deletion from nth in doubly linked list
    • Deletion from end in doubly linked list

Circular Linked List

  • Introduction to Circular Linked List
  • Circular Linked List in
  • Insertion in Circular Linked List
    • Insertion at the beginning
    • Insertion at the end
    • Insertion at nth position
  • Deletion in Circular Linked List
    • Deletion from beginning in Circular Linked List
    • Deletion from nth position in Circular Linked List
    • Deletion from end in Circular Linked List
  • Split a Circular Linked List in two halves
  • Count nodes in Circular Linked List
  • Sorted Insert In Circular Linked List 

5) Stacks and Queues

  • Introduction to Stack in Data Structure
  • Operations on a Stack
  • Stack: Infix, Prefix and Postfix conversions
  • Stack Representation in
  • Representation of a Stack as an Array
  • Representation of a Stack as a Linked List.
  • Infix to Postfix Conversion
  • Infix to prefix conversion in
  • Postfix to Prefix Conversion in


  • Queues in Data Structures (Introduction)
  • Queues Program in C and implementation
  • Implementation of Queues using Arrays | C Program
  • Types of Queues in Data Structure
  • Insertion in Queues Program in C (Enqueuing)
  • Deletion (Removal) in Queues Program in C (Dequeuing)
  • Application of Queue Data Structure
  • Reverse a Queue
  • Queues using Linked Lists
  • Implement Queue using Stack
  • Implement Queue using two Stacks

Circular Queues

  • Circular queue in Data Structure
  • Circular queue in C
  • Circular queue using Array
  • Applications of Circular Queues
  • Circular Queue using Linked Lists

Priority Queue

  • Priority Queue Introduction
  • Priority Queue Implementation using Array
  • Application of Priority Queue
  • Priority Queue Example in C
  • Priority Queue using Linked List
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DSA Online Training Program: PART-2

6) Trees

Introduction to Trees

  • Trees in Data Structure (Introduction)
  • Types of Trees in Data Structures

Binary Trees

  • Binary Tree in Data Structures (Introduction)
  • Tree Traversals: Inorder Postorder Preorder
  • Inorder Postorder PreOrder Traversals Examples
    • Inorder Tree Traversal in Binary Tree
    • Preorder Tree Traversal in Binary Tree
    • Postorder Tree Traversal in Binary Tree
  • Tree Traversal without Recursion
    • Postorder Preorder Inorder Traversal without recursion
    • Inorder Tree Traversal without Recursion
    • Preorder Tree Traversal without Recursion
    • Preorder Tree Traversal without Recursion

Binary Search Trees

  • Binary search tree in Data Structures (Introduction)
    • BST: Introduction to Binary Search Tree
    • BST: Binary Search Tree Program
    • BST: Search a node in Binary Search Tree
    • BST: Insertion in a Binary Search Tree
    • BST: Deletion in a Binary Search Tree


  • Traversal in Trees
  • Tree Traversals: Breadth-First Search (BFS)
  • Tree Traversals: Depth First Search (BFS)
  • Construct a Binary Tree from Postorder and Inorder

B – Trees

  • B-Tree
    • B-Tree: Introduction
    • B-Tree: Insertion 
    • B-Tree: Deletion

AVL Trees

  • AVL Trees
    • AVL Trees: Introduction
    • AVL Tree: Insertion
    • AVL Tree: Deletion
    • Insertion in a Binary Tree (Level Order)
    • Searching in Binary Tree
    • Searching in a Binary Search Tree

Complete Programs for Trees

  • Depth First Traversals 
  • Level Order Traversal 
  • Construct Tree from given Inorder and Preorder traversals 
  • Construct Tree from given Postorder and Inorder traversals 
  • Construct Tree from given Postorder and Preorder traversal 
  • Find size of the Binary tree 
  • Find the height of binary tree 
  • Find maximum in binary tree 
  • Check whether two tree are identical
  • Spiral Order traversal of Tree
  • Level Order Traversal LIne by Line
  • Hand shaking lemma and some Impotant Tree Properties.
  • Check If binary tree if Foldable or not
  • check whether tree is Symmetric .
  • Check for Children-Sum in Binary Tree
  • Sum of all nodes in Binary Tree
  • Lowest Common Ancestor in Binary Tree.

7) Arrays

  • Introduction to Arrays 
  • Introduction to 2-D Arrays
  • Sorting of Array
  • Array Rotation 
  • Reverse an array or string
  • Find pairs in array with given sum 
  • Sort the array in Waveform 
  • Majority Element in Array 
  • Boyer-Moore’s Voting Algorithm 
  • K-pairs with smallest sum in 2 arrays 
  • Largest Sum Contigous SubArray 
  • Maximum Average Sub-array of K length 
  • Size of sub-array with max sum 
  • Sub-array with given sum 
  • Triplet that sum to a given value 
  • Segregate 0’s and 1’s in array 
  • Segregate 0’s 1’s and 2’s in array 
  • Sort elements in array by frequency 
  • Finding pythagorean triplets in an array 
  • Reorder array using given indexes 
  • Merging two sorted arrays
  • Minimum number of Merge Operations to make an Array Palindrome 
  • Find Zeros to be Flipped so that number of Consecutive 1’s is maximized 


8) Graph

  • Terminologies 
  • Applications of Graphs 
  • Graph Representation 
  • Graph Traversals 
  • Topological Sort 
  • Shortest Path Algorithms
  • Minimal Spanning Tree

9) Divide and Conquer Algorithms

  • What is the Divide and Conquer Strategy? 
  • Does Divide and Conquer Always Work? 
  • Divide and Conquer Visualization 
  • Advantages of Divide and Conquer 
  • Disadvantages of Divide and Conquer Applications

10) Dynamic Programming

  • What is Dynamic Programming Strategy? 
  • Properties of Dynamic Programming Strategy 
  • Can Dynamic Programming Solve All Problems? 
  • Dynamic Programming Approaches 
  • Examples of Dynamic Programming Algorithms 
  • Longest Common Subsequence

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An alumna of MNIT-Jaipur and ACCENTURE, Pune


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