DSA for Academics

 

Demo Video

Demo video1:   Delete a node in BST

Demo video2:   Delete first node in CLL

Data Structures and Algorithms

Data Structures for  academics course at Algorithm Training training institute requires prior knowledge on programming languages like C or Java orPython. This course is designed for students who are studying their Data structures and Algorithms course in their academics. Even any non computer science student can join the course to master their programming skills. Here we are going to discuss and implement the topics and problems. This course would hep you to write efficient programs. Hence this is one of the Best Data structures And Algorithms Training In Bangalore or Data Structures and Algorithms Training In Hyderabad

Course Details:

Duration: 30hrs

time : 7.30 pm

Mode :  class room or online

Course Fee: 400usd

Demo:

Demo video1:   Delete a node in BST
Demo video2:   Delete first node in CLL

Trainer Details:

Trainer Details:

Trainer Details:

Trainer Name          : Mr. Srihari
Qualification            : M.Tech(CSE), IIT Roorkee
Experience              : Software professional with 20 yrs experience in Data structures/C/C++/JAVA/Python/PERL/UNIX/MPI(parallel programming).
Hacker Rank profile: click here

DSA Alumni

Mr Srihari trained nearly 30 students on Data Structures and Algorithms….. He trained ppl from B.tech student to 20 years of real time experienced ppl and students  from various cities in India and Countries like USA, Australia, UK   …etc. click here for Data Structures and Algorithms old batches details

Course Content

Counload course content here: Data Structures and Algorithms for Interviews (1741 downloads )

SNO Topic Sub topic No. of hrs
1 Algorithm Analysis How to analyse a program

Big O notation

Theta notation

Omega notation

1
2 Stacks a)Array implementation

b) Linked list implementation

create stack()

isempty()

push()

pop()

Check for balanced parentheses in an expression

Infix to post fix conversion

Evaluate postfix expression

 

2
3 Recursion Recursion analysis using stack frames

Recursion analysis using recursion tree

 

Analysis of factorial problem

Analysis of fib series

1
4 queues a)Array and linked list implementation of a queue

create queue()

isempty()

insert()

remove()

b) circular queue

c) double ended queue

2
5 Linked Lists Why linked list

linked list implementation

node structure

Implement following routines

getnode()

insertFront()

insertAfter()

insertEnd()

DelFirst()

DelEnd()

DeleAfter()

Implementation of the following problems
 1.Insert new node at front end of linked list
      2. Delete the first node at the front of the LL
      3.Implement Stack using LL
 4. Insert at end of the linked list
5. Insert an element into sorted LL
      6.Insert new node after the given node
      7. Delete the node with data x in LL
 5
 7 Doubly linked list setLeft()

setRight()

remove()

removeLeft()

RemoveRight()

DLL NODE structure

1.Implement insert front DLL

2.Implement delete front node

3.Delete Given Node

4.Insert After the given node

5.Insert before the given node

1
8 Binary Tree   and 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
k)Level Order traversal
5
 9 AVL tree
Rotations
a) LR
b) RL
c) LL
d) RR
1
 10  Sorting  Bubble sort

Insertion sort

Quick sort

Merge sort

Heap sort

Priority queue

3
12 searching Linear Search

Binary search

1
13 Hashing open hashing

closed hashing

implementation of hash table

1
14 Tries introduction

node structure

insert

search

1
15 Suffix Trees 1
16 Ternary Search Tree introduction

node structure

insert

search

1
17  B tree introduction

node structure

insert (algorithm)

search (algorithm)

1
18 Tournament Tree 1
19 Divide and conquer
Merge Sort
Quick Sort
Binary Search
1
20 Graphs
Adjacency matrix
Adjacency list
BFS
DFS
Spanning tree
Topological sorting
5
21 Greedy Method
Kruskals spanning tre
Primes spanning tree
Disjaskra shortest path
Knapsack problem
Huffman Coding
4
22 Backtracking
print permutations of a String
1
21 Dynamic Programming
Introduction to dynamic programming
memorization (top down)
tabulation (Bottom up)
optimal sub structure
factorial of a numer
fibanacci series
2