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Data Structures and Algorithms Course | Best DSA Course

Live Online Course

  4.7/5 Ratings     4.5/5Ratings

30 Sessions

  Live Classes

93 Videos

Video Course

100 Labs

Hands-on Labs

Data Structures and Algorithms Course Overview

The Data Structures and Algorithms Course is intended for individuals with an interest in software engineering who wish to advance their careers by landing an interview with one of the most prestigious firms in the world. So that you are ready for these important interviews, this program will teach you everything from problem-solving techniques to coding. Get hands-on practice by solving 100+ data structures and algorithms problems. You will begin the course by learning to solve problems related to each data structure and algorithm. Prepare for the top product-based companies like Meta, Microsoft, Amazon, Adobe, Netflix and Google.

DSA Course objectives

Participants in this training will learn data structures and algorithms and at the completion of this course, attendees will be able to:

  1. Identify techniques to design algorithms and measure their efficiency.
  2. Sort data by using bubble sort, selection sort, insertion sort, shell sort, quick sort, and merge sort.
  3. Search data by using linear search and binary search techniques.
  4. Store and search data using hashing.
  5. Solve problems using arrays, lists, linked lists, queues, and stacks.
  6. Solve problems using non-leaner data structures like trees, and graphs.

Why Learn Data Structures and Algorithms?

DSA is a fundamental skill for careers in software development, data science, Machine learning, and many more. These stats back the statement.

Data Structures and Algorithms Career Scope

DSA skilled is employed by the world's leading product based companies. Discover the salary and skills to become SDE.

Tools and Technologies Covered

Java
Logic Building
Code Debugging
Arrays
Big-O
Complexity Analysis
Linked List
Stack
Queue
Tree
Graph
VS Code IDE
GitHub

Data Structures and Algorithms Course Key Features

  • 10 Weeks of Intensive Live Training
  • Learn from SDEs in Product Based Companies
  • Learn to implement DSA
  • Career Coaching
  • Resume & Portfolio Building
  • Job Assistance

Data Structures and Algorithms Course Eligibility

Pre-requisites

There are no prerequisites to join the DSA course for computer science background students and working professionals.

Who can Join the DSA Course?

Students in college, recent graduates, and working professionals who are preparing for SDE interviews with prestigious organizations like Microsoft, Amazon, Adobe, and other top product-based corporations should learn data structures and algorithms courses.

Included in this Data Structures and Algorithms Training

  •   Live Sessions30 Classes
  •   Video Course 93 Videos
  •   Labs 100 labs
DSA Foundation

Data Structures

  • Introduction to Data Structure
  • Types of Data Structure
  • Abstract Data Type

Complexity Analysis

  • Complexity Analysis
  • Time complexity
  • Space complexity
  • Big O Notation
  • Iteration
  • Recursion
  • Exercises and Summary

Arrays and Strings

  • Arrays
  • Arrays Types
  • Strings
  • Iterations
  • Exercises and Summary

Sorting Algorithms

  • Bubble Sort
  • Insertion Sort
  • Selection Sort
  • Quick Sort
  • Merge Sort
  • Heap Sort
  • Count Sort
  • Bucket Sort
  • Exercises and Summary

Searching Algorithms

  • Introduction
  • Linear Search and its Implementation
  • Binary Search and its Implementation
  • Ternary Search and its Implementation
  • Jump Search and its Implementation
  • Exponential Search and its Implementation
  • Exercises and Summary

String Algorithms

  • Introduction
  • Count Vowels
  • Reverse a String
  • Reverse Words
  • Rotations
  • Remove Duplicates
  • Most Repeated Char
  • Sentence Capitalization
  • Exercises and Summary

Lists

  • Linked List
  • Singly Linked List
  • Doubly Linked List
  • Circular Linked List
  • Exercises and Summary

Stacks

  • Introduction
  • What are stacks
  • Working with Stacks
  • Building Stack using an Array
  • Exercises and Summary

Queues

  • What are queues
  • Working with Queues
  • Building Queues using an Array
  • Implementing Queues using a Stack
  • Priority Queues with different approaches
  • Exercises and Summary

Hash

  • What are Hash Tables
  • Working with Hash Tables
  • Hash Functions
  • Collision and Chaining
  • Building a Hash Table
  • Exercises and Summary
DSA Advanced

Binary Trees

  • What are Trees
  • Populating a Binary Tree
  • Building a Binary Tree
  • Traversing Trees
  • Working with Recursion
  • Depth First Traversals
  • Depth and Height of Nodes
  • Minimum values in a Tree
  • Level Order Traversal
  • Exercises and Summary

AVL Trees

  • Introduction
  • Balanced and Unbalanced Trees
  • Implementing Rotations
  • Building AVL Trees
  • Exercises and Summary

Heaps

  • What are Heaps
  • Working with Heaps
  • Building and Implementation Heaps
  • Heap Sort and its Implementation
  • Implementing Priority Queues
  • Working with Heapify
  • Exercises and Summary

Tries

  • What are the Tries?
  • Populating a Trie?
  • Implementation Tries with Hash Table
  • Abstraction and Traversal
  • Exercises and Summary

Graphs

  • What are Graphs
  • Adjacency Matrix and Adjacency List
  • Building Graphs
  • Adding Nodes and Edges
  • Removing Nodes and Edges
  • Traversal Algorithms
  • Depth-First Traversal
  • Breadth-First Traversal
  • Topological Sorting
  • Cycle Detection using Directed Graphs
  • Exercise and Summary

Undirected Graphs

  • Introduction
  • Weighted Graphs
  • Dijkstra’s Shortest Path Algorithm
  • Shortest Path Algorithm
  • Cycle Detection using Undirected Graphs
  • Minimum Spanning Tree
  • Prim’s Algorithm
  • Exercises and Summary

Greedy Algorithms

  • Greedy Algorithms
  • The strategies of Greedy Algorithms
  • Applications of Greedy Algorithms
  • Exercises and Summary

Divide and Conquer

  • Divide and Conquer Techniques
  • Master theorem Applications
  • Sliding Window problems
  • Merge Intervals problems
  • Exercises and Summary

Backtracking

  • Backtracking
  • Brute Force Approach
  • N Queens Problem
  • KMP
  • Exercises and Summary

Dynamic Programming

  • Dynamic Programming
  • Approaches of Dynamic Programming
  • Top-down approach
  • Bottom-up approach
  • Pattern matching algorithm
  • Exercises and Summary
Download Curriculum
Hands-On Labs Labs(100)

Java: Count the frequency of an element in an Array

00:20:00

Java: Find all triplets with zero sum

00:20:00

Java: Leaders in an array

00:20:00

Java: Meeting Rooms

00:25:00

Java: Merge Two Sorted Arrays

00:20:00

Java: Minimum Number of Jumps to Reach End in Array

00:25:00

Java: Move all Zeros to the beginning of an array

00:25:00

Java: Remove Duplicates from an Array

00:20:00

Java: Rotate a Matrix by 90 degrees

00:25:00

Java: Rotate an Array to the left

00:20:00

Java: Find the length of the largest subarray with 0 Sum

00:25:00

Java: Longest Increasing Consecutive Subsequence

00:25:00

Java: Find Whether an Array is a Subset of Another Array

00:20:00

Java: Camel Case of a given Sentence

00:20:00

Java: Count ways to increase LCS length of two Strings by one

00:25:00

Java: Minimum rotations required to get the same string

00:15:00

Java: Multiply Large Numbers represented as Strings

00:25:00

Java: Find Itinerary from a given list of tickets

00:25:00

Java: Construct a linked list from 2D matrix

00:30:00

Java: Convert given Binary Tree to Doubly Linked List in Linear Time

00:25:00

Java: Count Nodes in Circular Linked List

00:25:00

Java: Delete all Prime Nodes from a Doubly Linked List

00:35:00

Java: Deletion from a Circular Linked List

00:35:00

Java: Remove Duplicates from a sorted Linked List

00:25:00

Java: Reverse a Doubly Linked List

00:20:00

Java: Traversal of Circular Linked List

00:25:00

Java: Reverse a Stack using Recursion

00:25:00

Java: Find next right node of a given key

00:30:00

Java: Traversing directory in Java using BFS

00:20:00

Java: Delete consecutive same words in a sequence

00:25:00

Java: Sort a Stack using another stack

00:30:00

Java: Minimum time required to rot all oranges

00:40:00

Java: Next Greater Element

00:30:00

Java: Trapping rain water

00:30:00

Java: Largest rectangle in histogram

00:25:00

Java: Check whether a Binary Tree is BST or Not

00:30:00

Java: Deletion in a Binary Tree

00:40:00

Java: Check if two nodes are cousins in a Binary Tree

00:50:00

Java: Check whether the two Binary Search Trees are Identical or Not

00:35:00

Java: Find the Closest Element in Binary Search Tree

00:35:00

Java: Convert Binary Tree to Doubly Linked List

00:50:00

Java: Height of a Generic Tree from Parent Array

00:50:00

Java: Insertion in a Binary Tree in Level Order

00:35:00

Java: Find right Sibling of a binary tree with parent pointers

00:40:00

Java: Find Distance between two nodes of a Binary Tree

00:50:00

Java: Binary Tree to Binary Search Tree Conversion

00:40:00

Java: Transpose Graph

00:40:00

Java: Count Number of Trees in a Forest

00:40:00

Java: Depth First Search or DFS for a Graph

00:40:00

Java: Breadth First Search or BFS for a Graph

00:40:00

Java: Iterative Depth First Traversal of Graph

00:30:00

Java: Detect Cycle in a Directed Graph

00:30:00

Java: Detect Cycle in an Undirected Graph

00:30:00

Java: Dijkstra’s Shortest Path Algorithm

00:40:00

Java: Connect n ropes with minimum cost

00:30:00

Java: Continuous Median

00:25:00

Java: Kth Largest Element in a Stream

00:25:00

Java: Kth smallest Element in row-wise and column-wise sorted 2D array

00:30:00

Java: Last Stone Weight

00:20:00

Java: Heap Sort for decreasing order using min heap

00:30:00

Java: Iterative HeapSort

00:30:00

Java: Maximum distinct elements after removing k elements

00:30:00

Java: Print all nodes less than a value x in a Min Heap.

00:40:00

Java: Convert Min Heap to Max Heap

00:30:00

Java: Ceiling in a Sorted Array

00:25:00

Java: Count 1’s in a Sorted Binary Array

00:20:00

Java: Find a Fixed Point (Value equal to Index) in given Array

00:25:00

Java: Search an Element in a Sorted and Rotated Array

00:30:00

Java: Two Elements whose Sum is Closest to Zero

00:30:00

Java: Search in an Almost Sorted Array

00:25:00

Java: Median of Two Sorted Arrays of Different Sizes

00:30:00

Java: A Pair with a Given Sum in the Rotated Sorted Array

00:25:00

Java: Sort Elements by Frequency

00:30:00

Java: Sort a Linked List of 0s, 1s and 2s

00:35:00

Java: Find Missing Elements of a Range

00:25:00

Java: Sort a Nearly Sorted (or K sorted) Array

00:20:00

Java: Chocolate Distribution Problem

00:30:00

Java: Minimum Swaps required to convert binary tree to binary search tree

00:30:00

Java: Count Distinct Occurrences as a Subsequence

00:30:00

Java: Sort a Matrix in all way Increasing Order

00:20:00

Java: Split n into Maximum Composite Numbers

00:20:00

java: Assign Mice to Holes

00:30:00

Java: Fitting Shelves Problem

00:40:00

Java: Greedy Algorithm to find Minimum number of Coins

00:30:00

Java: Job Sequencing Problem

00:30:00

Java: Minimize Cash Flow among a given set of friends who have borrowed money from each other

00:40:00

Java: Minimum Swaps for Bracket Balancing

00:30:00

Java: Coin Change

00:15:00

Java: Print all subsets of a given Set or Array

00:20:00

Java: Print all palindromic partitions of a string

00:40:00

Java: Minimum Number of Jumps to Reach End

00:20:00

Java: 0/1 Knapsack Problem

00:30:00

Java: N Queen Problem | Backtracking-3

00:30:00

Java: Count all possible Paths between two Vertices

00:40:00

Java: Weighted Job Scheduling

00:30:00

Java: Partition Problem

00:40:00

Java: Algorithm to Solve Sudoku | Sudoku Solver

00:40:00

Java: Combinational Sum

00:30:00

Java: Matrix Chain Multiplication

00:35:00

Java: Floyd Warshall Algorithm

00:40:00

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Frequently Asked Questions

Q1. What are the different kinds of data structures used in programming?

Data structures come in two different varieties: linear data structures and non-linear data structures. Both are discussed in this DSA course.

Q2. What justifies learning about data structures and algorithms?

Data structures and algorithms help developers to become more problem-solving capable. One can write the same code that is written previously in several lines in only a few using data structures and algorithms. They reduce the amount of time and memory needed for a task that the application needs to complete. Scalability and less coding are two more benefits.

Q3. Do you offer a certificate of completion?

Yes. our DSA certificate is valid and can be used for interviews. Additionally, the student can register for the Certification exam after completing this course.

Q1. Do you prepare me for the job interview?

Yes, we do. We will discuss all possible technical interview questions and answers during the training program so that you can prepare yourself for interview.

Q2. Do you provide training on latest technology version?

Yes we do. As the technology upgrades we do update our content and provide your training on latest version of that technology.

Q3. Do you provide any course material or live session videos?

Yes we do. You will get access to the entire content including class videos, mockups, and assignments through LMS.

Q4. Can I share my course with someone else?

In short, no. Check our licensing that you agree to by using Dot Net Tricks LMS. We track this stuff, any abuse of copyright is taken seriously. Thanks for your understanding on this one.

Q5. What If I miss my online training class?

All online training classes are recorded. You will get the recorded sessions so that you can watch the online classes when you want. Also, you can join other class to do your missing classes.

Q6. Who are your mentors?

All our mentors are highly qualified and experience professionals. All have at least 8-10 yrs of development experience in various technologies and are trained by Dot Net Tricks to deliver interactive training to the participants.

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