Data Structures for academics

Data Structures

Data Structures for academics course at Algorithm Class training institute makes you confident with fundamentals. This Training would be very useful for  academics.  Here we are going to discuss and implement the conceptss. Hence this is one of the Best Data structures And Algorithms Training In Bangalore or Data Structures And Algorithms Training In Hyderabad. This requires prior knowledge on C/JAVA.

Duration: 6 weeks

Fee: Rs 10000 (Class Room, Hyderabad)

Fee: Rs 12000 (Online, India)

Fee:  300 USD (Online,US)

Mode : Online and Class room

Trainer Details: 

Trainer Name          : Mr. Sree

Qualification            : M.Tech(CSE), IIT Roorkee

Experience              : Software professional with 16 yrs experience in Data                                                                      structures/C/C++/JAVA/Python/PERL/UNIX/MPI(parallel programming).

 

Course Content

 

SNO

topic

subtopic

no.of hrs

1

Algorithm Analysis

How to analyse a program


Big O notation

Theta notation

Omega notation

1

2

Stacks

a) Array and linked list implementation of a stack 

create stack()

isempty()  

push()  

pop()

 

b) infix to post fix conversion

 

c) evaluate postfix expression

2

3

Recursion

Recursion analysis using

 

stack frames

Recursion tree

1

4

Queues

a) Array and linked list implementation of a queue

 

create queue() 

isempty()  


insert()  

remove()

 

b) circular queue

c) double ended queue

1

 5

 linked lists

 a) Single linked list

insertFront()

insertAfter()

insertEnd()

DelFirst()

DelEnd()

DeleAfter()

 

b) Circular linked list

insert()

remove()

stack as CLL

queue as CLL

 

c) Doubly linked list

setLeft()

setRight()

remove()

removeLeft()

RemoveRight()

5

 6

Trees    

Binary Trees   Binary Search Trees                                    

a) Tree terminology

b) General tree

a) expression tree

b) Binary Tree

e) Tree traversal

PreTraversal()

postTraversal()

inorderTrav()

 f) Construct original tree from given     pre order and in order traversals. 

g) Construct original tree from given     post order and in order traversals.

a) createtree()

b) setleft()

c) setRight()

d) createTree()

e) disposeTree()

f) FindKey()

g) findMin()

h) findMax()

i) find inorder successor, predecessor  

j) Tree delete operation

5

 7

 AVL trees

AVL TREES      Rotations

a) LR

b) RL

c) LL 

d) RR

1

 8

 Sorting

 Bubble sort

Insertion sort

Quick sort

Merge sort

Heap sort

Priority queue

2

 

 Searching

 Linear Search

  Binary search

 1

10

Arrays

 

 1

11

Hashing

 

1

12

TRIES

node Structure  

getNode()  

insert()  

search()

1

13

Suffix Trees

 

 

14

Ternary Search Tree

Introduction 

insert() 

search()

1

 15

 Tournament Tree

 

 

16

B Tree

Introduction  

insert()  

search()  

delete()

 1

17

Graphs

Adjacency matrix  

Adjacency list  

BFS  

DFS  

 

Floyd Shortest Path

 

4

 18

 Divide and Conquer

Merge Sort  

Quick Sort

 1

19

Greedy Algorithms

Dijkstra Shortest Path

 

Krushka’s Spannig Tree

Primes’s Spannig Tree

2

 20

 Dynamic Programming

Introduction to dynamic programming  

memorization (top down) 

tabulation  (Bottom up)  

optimal sub structure

3