Data Structure Training
| 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 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
ArraysStructures
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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