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DATA STRUCTURE AND ALGORITHM USING JAVA

If you look around, many of the software are running really slow and inefficient and many freshers dont have proper skill sets. So, how you are going to differentiate yourself from rest of the others? In today’ time, when you know Data Structure and Algorithms using any of the programming language then you can say that you have more knowledge then others which makes you stand out of crowd. And that’s where DSA course from LogicRays Academy comes into the picture!

Our certification course in DSA will help you equip with an extraordinary knowledge finding creating the perfect applications. The training course from LogicRays entails the basics of Theory and practicals. Moreover, this course will help individuals to master in advanced tools and techniques, which enables you to become a perfect coder within a short time span.

What is Data Structure and Algorithm?

ADSA, or Data Structures and Algorithms, is a fundamental area in computer science that focuses on designing and analyzing efficient ways to store, organize, and manipulate data. It involves studying various data structures, such as arrays, linked lists, and trees, and algorithms for tasks like sorting, searching, and optimization. Mastery of DSA is crucial for solving complex computational problems, improving program efficiency, and ensuring that software applications run smoothly and effectively.

WHY YOU NEED TO LEARN DATA STRUCTURE AND ALGORITHM USING java

Learning DSA provides essential skills that are beneficial for efficient software development, problem-solving, and advancing in a technology career. It enhances your ability to design robust, high-performance systems and adapt to complex challenges in the field.

Enhanced Problem
Solving Skills
Efficiency and
Performance
Technical Interviews
and Job Preparation
Foundation for
Advanced Topics
Code Optimization
and Maintenance
Scalability
Algorithmic Thinking
WHY YOU SHOULD REGISTER AT LOGICRAYS FOR LEARNING DATA STRUCTURE AND ALGORITHM USING JAVA COURSE IN AHMEDABAD?
  • Helps individuals sharpen their high-level thinking skills.
  • Leverage from the trainers having experience of more than 5 years.
  • Proven and well-tested teaching methods for the newbie and advance learners.
  • Get mentored by the industry best Ethical Hackers.
  • Get benefit of job placement assistance.

If you are planning to learn Data Structure and Algorithms using JAVA from the professionals, get in touch with us now!

For any questions, you can contact us or visit LogicRays Academy center.

DATA STRUCTURE AND ALGORITHM
  • What is Data Structure
  • What is an algorithm?
  • Why are Data Structures and Algorithms important?
  • Types of Data Structures
  • Types of Algorithms
  • Big O Notations - (Big O, Big Omega, Big Theta)
  • Drop Constants
  • Drop Non Dominant Terms
  • Space Complexity
  • How to Measure the Code using Big O?
  • Types of Arrays
  • Array Traversal
  • Search for Array Element
  • Delete Array Element
  • Time and Space Complexity of 1D Arrays
  • Time and Space Complexity of 2D Arrays
  • When to Use/Avoid Arrays
  • What is ArrayList?
  • CRUD Array List
  • Traversal of ArrayList
  • Time and Space Complexity of ArrayList
  • What is a Linked List?
  • Linked List vs Array
  • Types of Linked List
  • Creation of Singly Linked List
  • Insertion in Singly Linked List in Memory
  • Insertion Algorithm and methods 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
  • Circular Singly Linked List
  • Doubly Linked List
  • Circular Doubly Linked List
  • What and Why of Stack?
  • 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 methods - Push, Pop, Peek, Delete, and isEmpty using Linked List
  • Time and Space Complexity of Stack using Linked List
  • When to Use/Avoid Stack
  • What is a Queue?
  • 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?
  • Time and Space Complexity of Circular Queue using Array
  • Queue Operations using Linked List
  • Time and Space Complexity of Queue using Linked List
  • Array vs Linked List Implementation
  • When to Use/Avoid Queue?
  • What is Recursion?
  • Why do we need Recursion?
  • Recursive vs Iterative Solution
  • When to Use/Avoid Recursion?
  • How to Write Recursion in 3 Steps?
  • How to Measure Recursive Algorithm?
  • How to Measure Recursive Algorithm with Multiple Calls?
  • Why / What is a Tree?
  • Creating a Basic Tree in Java
  • What is A Binary Tree and its types
  • 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, Insert Method in Binary Tree (Linked List)
  • Delete a Node in Binary Tree (Linked List)
  • Create Binary Tree (Array)
  • Insert Method Binary Tree (Array)
  • PreOrder, InOrder, PostOrder, LevelOrder Traversal Binary Tree (Array)
  • Search Method Binary Tree (Array)
  • Delete a Node Binary Tree (Array)
  • Array vs Linked List in Binary Tree Implementation
  • What is a Binary Search Tree? Why do we need it?
  • Create Binary Search Tree
  • Insert a Node to Binary Search Tree
  • PreOrder, InOrder, PostOrder, Level Order Traversal Binary Search Tree
  • Search in Binary Search Tree
  • Delete a Node in Binary Search Tree
  • 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 (LL, LR, RR, RL)
  • Delete a Node from AVL (LL, LR, RR, RL)
  • Delete a Node from AVL (All Together)
  • 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, Search, Delete a String in Trie
  • What is Hashing? Why we need it?
  • Hashing Terminology and Function
  • Types of Collision Resolution Techniques - Direct Chaining (Insert, Search, Delete)
  • Hash Table is Full
  • Collision Resolution Technique - Linear Probing (Insert, Search, Delete)
  • Collision Resolution Technique - Open Addressing: Quadratic Probing
  • Collision Resolution Technique - Open Addressing: Double Hashing
  • Pros and Cons of Resolution Techniques
  • Practical Use of Hashing
  • Hashing vs Other DS
  • What is Sorting?
  • Types of Sorting
  • Sorting Terminology
  • Bubble, Selection, Insertion, Bucket, Merge, Quick, Heap Sort
  • Comparison of Sorting Algorithms
  • Introduction To Search Algorithms
  • Linear, Binary Search
  • Time Complexity of Binary Search
  • What is a Graph? Why do we need Graph?
  • Graph Terminology
  • Types of Graph and Representation
  • Graph in Java using Adjacency Matrix and List
  • Breadth First Search Algorithm (BFS) - Adjacency Matrix and Adjacency List
  • Time Complexity of Breadth First Search (BFS) Algorithm
  • Depth First Search (DFS) Algorithm - Adjacency Matrix and Adjacency List
  • 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 and 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 and 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 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
    • BFS vs Dijkstra vs Bellman Ford
    • 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
    • Kruskal Algorithm
    • Prim's Algorithm
    • Kruskal vs Prim's Algorithms
    • What is Greedy Algorithm?
    • Known Greedy Algorithms
    • Activity Selection Problem
    • Activity Selection Problem in Java
    • Coin Change Problem
    • Fractional Knapsack Problem
    • What is a Divide and Conquer Algorithm?
    • Number Factor
    • House Robber
    • Convert One String to Another
    • Zero One Knapsack Problem
    • Longest Common Subsequence Problem
    • Longest Palindromic Subsequence Problem
    • Minimum Cost to Reach Last Cell
    • Number of Paths To Reach The Last Cell with Given Cost
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