## Data Structure Training

Data Structure Training NITDP Data Structure Training instituteAbout Data Structure Training Data Structures is a concept a means of storing a collection of data. Computer Science is a concern with study of methods for effectively using a computer to solve problems. These can be solve by algorithms and data structures. Data Structures tells you what way the data as to store in computer memory and how to access the data efficiently. Many Applications are designed by data structures stack applications like page visited history in a web-browser, chain of method calls in the Java virtual machine or C++ Run-time environment etc Queue Application Like Waiting Lines, Multi-programming etc For many applications the choice of proper data structure is the only major decision involving the implementation. Majorly the database designing and internal implementation is done only by using Data Structures techniques. Data Structure Training Course ObjectiveThis Course main objective for the student to understand Analysis and Designing of the Algorithms and how the different data structures are used for efficient accessing of the data and Manipulation of the data at the end of the session we can able to Know different Kinds of data structures and we can able to provide different algorithms for time and space complexity. Data Structure Training Course Duration 60 Working days, daily two hours Data Structure Training Course Content OverviewIntroduction to Data Structure AlgorithmsPerformance Analysis Time complexity Space complexity Asymptotic Notations- Big O Omega Theta notations Arrays Structures PointersDynamic Memory allocation Malloc() calloc() realloc() free() Stacks Stack Operations push() pop() peex() distzay() isEmpty() isFull() Stack implementation using arrays Applications Decimal to Binary String reverse Number reverse Recursion – Towers of Hanoi Balanced Parentheses Expressions Stack Implementation using pointer (dynamic) ExpressionIntroduction to Notations Importance of Notations in expression evaluation Conversion Algorithm Infix to prefix Infix to postfix Prefix to infix Prefix to postfix Postfix to infix Postfix to prefix Implementation of all the conversions QueuesOperations on Queue – enqueue(), dequeue() Queue implementation using static arrays Applications Queues Implementations using pointer (dynamic) Circular queues Double Ended queue (Deques) Single linked list Introduction Construction Length Insertion Deletion Sort Reverse list Swap node data Swap nodes Applications Stack implementation using linked listQueue implementation using linked listDoubly linked listCircular linked listCircular Doubly Linked ListBinary TreeTerminology Differences between Tree and Binary Tree Binary Tree Representations Expression Trees Traversals In-order pre-order post-order Binary Search Tree Introduction to BST Insertion Deletion Search Implementation Graph Introduction & Terminology Graph Representations Traversal BFS (Breadth First Search) DFS (Depth First Search) Searching AlgorithmsLinear search Binary search Sorting Algorithms Bubble sort Selection sort Insertion sor t Heap sort Merge sort Quick sort AVL Trees Introduction BST v/s AVL Rotations L-L-Rotation R-R-Rotation L-R-Rotation R-L-Rotation Insertion Deletion Traversal Red Black TreesIntroduction BST v/s AVL v/s RBT Rotations L-L-Rotation R-R-Rotation L-R-Rotation R-L-Rotation Insertion Deletion B trees M-way Search Tree Search Insertion Deletion Hashing Hash Table representation Hash function-Division Method Collision Collision Resolution Techniques Separate Chaining open addressing linear probing quadratic probing double hashing Rehashing Priority Queue-DefinitionOperations-Insertion, Deletion, Heap Definition Max Heap Min Heap Insertion and deletion Pattern matching algorithmsBrute force Boyer –Moore algorithm Knuth-Morris-Pratt algorithm Tries Standard TriesCompressed Tries Suffix tries Dynamic ProgrammingGreedy Method Divide and conquer methodCategories: Classroom Training Tags: Data Structure Training Job Alert:- Click Here Similar Post:- Click Here |

** Data Structure Training** NITDP Data Structure Training institute

**About Data Structure Training**

Data Structures is a concept a means of storing a collection of data. Computer Science is a concern with study of methods for effectively using a computer to solve problems. These can be solve by algorithms and data structures. Data Structures tells you what way the data as to store in computer memory and how to access the data efficiently. Many Applications are designed by data structures stack applications like page visited history in a web-browser, chain of method calls in the Java virtual machine or C++ Run-time environment etc Queue Application Like Waiting Lines, Multi-programming etc For many applications the choice of proper data structure is the only major decision involving the implementation. Majorly the database designing and internal implementation is done only by using Data Structures techniques.

**Data Structure Training Course Objective**

This Course main objective for the student to understand Analysis and Designing of the Algorithms and how the different data structures are used for efficient accessing of the data and Manipulation of the data at the end of the session we can able to Know different Kinds of data structures and we can able to provide different algorithms for time and space complexity.**Data Structure Training Course Duration**

60 Working days, daily two hours**Data Structure Training Course Content Overview****Introduction to Data Structure****Algorithms****Performance Analysis**

Time complexity

Space complexity**Asymptotic Notations-**

Big O

Omega

Theta notations**Arrays****Structures**** ****Pointers****Dynamic Memory allocation**** **

Malloc()

calloc()

realloc()

free()**Stacks **

Stack Operations

push()

pop()

peex()

distzay()

isEmpty()

isFull()

Stack implementation using arrays

Applications

Decimal to Binary

String reverse

Number reverse

Recursion – Towers of Hanoi

Balanced Parentheses

Expressions**Stack Implementation using pointer (dynamic)****Expression**

Introduction to Notations

Importance of Notations in expression evaluation

Conversion Algorithm

Infix to prefix

Infix to postfix

Prefix to infix

Prefix to postfix

Postfix to infix

Postfix to prefix

Implementation of all the conversions**Queues**

Operations on Queue – enqueue(), dequeue()

Queue implementation using static arrays

Applications

Queues Implementations using pointer (dynamic)**Circular queues****Double Ended queue (Deques)****Single linked list**

Introduction

Construction

Length

Insertion

Deletion

Sort

Reverse list

Swap node data

Swap nodes

Applications**Stack implementation using linked list****Queue implementation using linked list****Doubly linked list****Circular linked list****Circular Doubly Linked List****Binary Tree**

Terminology

Differences between Tree and Binary Tree

Binary Tree Representations

Expression Trees

Traversals

In-order

pre-order

post-order**Binary Search Tree**

Introduction to BST

Insertion

Deletion

Search

Implementation**Graph**

Introduction & Terminology

Graph Representations

Traversal

BFS (Breadth First Search)

DFS (Depth First Search)**Searching Algorithms**

Linear search

Binary search**Sorting Algorithms**

Bubble sort

Selection sort

Insertion sor

t Heap sort

Merge sort

Quick sort**AVL Trees**

Introduction

BST v/s AVL

Rotations

L-L-Rotation

R-R-Rotation

L-R-Rotation

R-L-Rotation

Insertion

Deletion

Traversal**Red Black Trees**

Introduction

BST v/s AVL v/s RBT

Rotations

L-L-Rotation

R-R-Rotation

L-R-Rotation

R-L-Rotation

Insertion

Deletion**B trees**

M-way Search Tree

Search

Insertion

Deletion**Hashing**

Hash Table representation

Hash function-Division Method

Collision

Collision Resolution Techniques

Separate Chaining

open addressing

linear probing

quadratic probing

double hashing

Rehashing**Priority Queue-Definition**

Operations-Insertion, Deletion,**Heap**

Definition

Max Heap

Min Heap

Insertion and deletion**Pattern matching algorithms**

Brute force

Boyer –Moore algorithm

Knuth-Morris-Pratt algorithm**Tries** Standard Tries

Compressed Tries

Suffix tries

**Dynamic Programming**

**Greedy Method**

**Divide and conquer method**

Categories: Classroom Training

Tags: Data Structure Training

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