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
- 30 Working days, daily one and half 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 Algorithms
- 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 sort
- 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
