Data Structures & Algorithms using C and C++ Training

• To provide students with a solid understanding of the basic concepts and principles of data structures and algorithms.
• To introduce students to the most popular data structures, such as arrays, linked lists, stacks, queues, trees, and graphs, and to teach them how to work with these structures in C and C++.
• To familiarize students with various algorithmic techniques, including sorting, searching, and recursion, and to help them understand when and how to apply these techniques to solve programming problems.
• To teach students how to design and implement efficient algorithms for real-world applications.
• To help students develop problem-solving skills and enhance their ability to analyze and optimize algorithms.
• To prepare students for advanced courses in computer science and for careers in software development, data analysis, and other related fields.

• Recorded Videos After Training
• Digital Learning Material
• Course Completion Certificate
• 24x7 After Training Support

• Computer science students who want to deepen their understanding of data structures and algorithms and prepare for advanced coursework in computer science. Software developers who want to improve their problem-solving skills and learn new techniques for designing efficient algorithms.
• Programmers who want to work with popular data structures, such as arrays, linked lists, stacks, queues, trees, and graphs, and apply them to real-world programming problems. Anyone who wants to learn how to analyze and optimize algorithms to improve their performance and efficiency.
• Overall, the course is suitable for individuals who have a solid foundation in programming concepts and are looking to expand their knowledge and skills in data structures and algorithms using C and C++.

• Basic knowledge of programming concepts such as variables, data types, loops, and conditional statements
• Familiarity with C and C++ programming languages
• Understanding of object-oriented programming (OOP) concepts Experience in problem-solving and analytical thinking

• Multisoft Systems provides a training certification after successful completion of Data Structure & Algorithms using C and C++ course.

1.Essential C and C++ Concepts

• Arrays Basics
• Structures
• Pointers
• Reference in C++
• Pointer to Structure
• Functions
• Parameter Passing Methods
• Structures and Functions
• Converting a C program to a C++ class

2.Required Setup for Programming

• Online C and C++ compiler
• Setup CodeBlocks and Settings
• Setup Dev-C++ and Settings
• Debugging using Dev-C++ and CodeBlocks
• Setup and Debugging using Visual Studio

3.Introduction

• Stack vs Heap Memory
• Physical vs Logical Data Structures
• Abstract Datatypes
• Time and Space Complexity

4.Recursion

• Generalizing Recursion
• Static and Global Variables in Recursion
• Head, Tail, and Tree Recursion
• Indirect Recursion
• Nested Recursion
• Fibonacci Series using Recursion

5.Array Representation

• Array Declaration
• Static vs Dynamic Arrays
• Increasing Array Size
• 2D Arrays
• Row and Column Major Formula for 2D Arrays
• Formulas for 3D & nD Arrays

6.Array ADT

• Array ADT
• Inserting in an Array
• Deleting from Array
• Linear Search
• Binary Search
• Get( ) Set( ) Avg( ) Max( ) functions on Array
• Merging and Sorting Arrays

7.Strings

• Finding Length of a String
• Validating a String
• Reversing a String

8.Matrices

• C++ class for Diagonal Matrix
• Lower Triangular Matrix Row and Column Major Mapping
• Lower Triangular Matrix in C and C++
• Triangular Matrices
• Symmetric Matrix

9.Sparse Matrix and Polynomial Representation

• Sparse Matrix Representation
• Create Sparse Matrix
• Sparse Matrix using C++
• Polynomial Representation
• Polynomial Evaluation
• Polynomial Addition
• Coding Polynomial

10.Linked List

• Dynamic Data Structure Linked List
• Display Linked List
• Recursive Display of Linked List
• Sum of All Elements in a Linked List
• Searching in a Linked List
• Deleting from Linked List
• Reversing a Linked List
• Concatenating 2 Linked Lists
• Merging 2 Linked Lists
• 11.Sparse Matrix and Polynomial Representation using Linked List
• Sparse Matrix using Linked List
• Polynomial Representation using Linked List

12.Stacks

• Stack using Array
• Implementation of Stack using Array
• Stack using Linked List
• Stack Operations using Linked List
• Parenthesis Matching
• Infix to Postfix Conversion
• Associativity and Unary Operators

13.Queues

• Queue ADT
• Queue using Single Pointer
• Queue using Two Pointers
• Implementing Queue using Array
• Drawback of Queue using Array
• Circular Queue
• Double Ended Queue DEQUEUE

14.Trees

• Terminology
• Number of Binary Trees using N Nodes
• Height vs Nodes in Binary Tree
• Internal Nodes vs External Nodes in Binary Tree
• Strict Binary Tree
• Height vs Node of Strict Binary Tree
• Internal vs External Nodes of Strict Binary Trees
• n-ary Trees
• Analysis of n-Ary Trees
• Full vs Complete Binary Tree

15.Binary Search Trees

• Searching in a Binary Search Trees
• Inserting in a Binary Search Tre
• Creating a Binary Search Tree
• Deleting from Binary Search Tree
• Program for Generating BST from Preorder

16.AVL Trees

• Inserting in AVL with Rotations
• General form of AVL Rotations
• Generating AVL Tree
• Deletion from AVL Tree with Rotations
• Height Analysis of AVL Trees

17.Search Trees

• 2-3 Trees
• 2-3-4 Trees
• Red-Black Trees
• Red-Black Trees vs 2-3-4 Trees
• Creating Red-Black Tree similar to Creating 2-3-4 Tree

18.Heap

• Inserting in a Heap
• Creating a Heap
• Deleting from Heap and Heap Sort
• Heap as Priority Queue

19.Sorting Technique

• Criteria used for Analysing Sorts
• Bubble Sort
• Insertion Sort
• Selection Sort
• Quick Sort
• Merging
• Recursive Merge Sort
• Count Sort
• Bin / Bucket Sort
• Radix Sort
• Shell Sort

20.Hashing Technique

• Chaining
• Linear Probing
• Quadratic Probing
• Double Hashing
• Hash Function Ideas

21.Graphs

• Directed and Undirected Graphs
• Breadth First Search
• Depth First Search
• Spanning Trees
• Prim's Minimum Cost Spanning Tree
• Kruskal's Minimum Cost Spanning Tree
• Disjoint Subsets

22.Asymptotic Notations

• Big Oh
• Omega
• Theta