Data Structures And Algorithms

MCP Technologies offers best data structures and algorithms training programmings in Mohali and Chandigarh.

At MCP Technologies, we provide an excellent and high quality Data Structures algorithm Training institute in Chandigarh and Mohali. We have a team of highly skilled professionals having experience more than 10 years to equip you and build a strong foundation. These programming languages are the base foundation languages and they are the part of each of the university board curriculum so most of companies ask directly from these languages and paced accordingly . In small size of batches , we provide practical knowledge without any projector  The curriculum can be customized as per individual’s need. Weekly test conducted to improve the skills of student

We help out students  for  interview preparation training for IT Companies  and E-commerce companies and top level  MNCs,  like Amazon, Accenture, Infosys, Cisco, Microsoft, Nvidia, Google , IBM, Wipro and many more. Our best and advanced training program provides a best practical training program helps in better understanding of data structures and algorithms programs  & Design Pattern  concepts .

Our course content is designed according to requirements of computer based IT companies , to match with the real-world requirements for both new and advanced level. Should have basic knowledge programmings.

We Delivered professionals who prepared for interviews for top ranked MNCs IT company

B.Tech(CSE/IT)/MCA/BCA/MSc IT trades Students looking for data structures coaching

Job seekers who are preparing for interview in Product MNC/IT Companies and Ecommerce companies

Syllabus Content:Data Structures  Algorithms

Basic Concept in Data Structures.

1: Searching and Sorting.

• Linear Search and Binary Search
• Sorting Techniques :- Bubble Sort, Selection Sorting
• Insertion Sort, Merge Sort, Heap Sort (Algorithms and Programs)
• Quick Sort  , Radix Sort (Algorithms and Programs)
• Divide and Conquer Rule
• Complexity Theory :-  Big O Notation

2:  Greedy Algorithms:

• Dijkstra’s Shortest Path Algorithm :  Dynamic Programming
• Min Cost Path
• Longest Increasing Sub-sequence
• Longest Common Sub-sequence
• Weighted Job Scheduling : – Operating System

4:  Backtracking Algorithms

• The Eight Queens Problem
• Fibonacci Numbers , Recursion
• Tower Of Hanoi

5:  Trees And Balanced Trees Algorithms

• Tree Terms
• Binary Search Tree Properties and Algorithms
• Traversals – Preorder Traversing
• Traversals – Postorder Traversing
• Traversals – Inorder Traversing Balanced Trees
• What is Balanced Trees?
• B-Trees – B-Tree Basics
• B-Trees – Adding Items
• B-Trees – Removing Items

6: Graphs

• Network Algorithms
• Network Terminology
• Spanning Trees
• Shortest Paths
• Breadth First Traversal for a Graph
• Depth First Traversal for a Graph
• Application of Depth First Search
• Application of Breadth First Traversal
• Detect Cycle in a Directed Graph
• Detect Cycle in a an Undirected Graph
• Detect cycle in an undirected graph
• Longest Path in a Directed Acyclic Graph
• Check whether a given graph is Bipartite or not

7: Stack Applications

• Stack :- Algorithms and program Using Array
• Stack :- Algorithm and program Using Queue

8 Queue Applications

• Queue :- By Using Array
• Queue :- By Using Stacks

9: Linked list

• Linked list :- Using singly Linked List
• Linked list :- Using doubly Linked List
• Linked list :- Using Circular Linked List

10: Trees (BST, AVL, 2-4 , Red Black)

• Trees – BST
• Trees – AVL
• Trees – 2-4
• Trees – Red Black

11: Hash Table

• Chaining
• Open Addressing – Basics
• Open Addressing – Linear Probing
• Open Addressing – Quadratic Probing

 12: Graphs

• Graph Theory and its representations
• Adjacency Matrix
• Adjacency List
• Directed Graph
• Undirected Graph