C Programming, C++ & Data Structures and Algorithms Course

The C Programming, C++ Foundation and Data Structures & Algorithms Using C++ course is designed for first-year undergraduate students to build a strong foundation in programming and DSA. Students learn C programming fundamentals, C++ and OOP concepts, STL, and core Data Structures & Algorithms including arrays, strings, recursion, searching, sorting, linked lists, stacks and queues. The course follows a progressive learning path from programming fundamentals to beginner-to-intermediate DSA problem solving using C++.

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C++ & DSA Career Opportunities, Salary & Hiring Companies

Explore career opportunities after learning C Programming, C++, Object-Oriented Programming (OOP), STL and Data Structures & Algorithms. Build the skills required for roles such as C++ Developer, Software Engineer, Embedded C/C++ Developer, System Software Engineer and Algorithm Developer.

With strong programming and DSA skills, learners can pursue opportunities across IT services, product companies, engineering organizations and technology startups. Salary growth depends on skills, experience, location and company.

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C++ & DSA Career Opportunities, Salary & Hiring Companies

Explore career opportunities after learning C Programming, C++, Object-Oriented Programming (OOP), STL and Data Structures & Algorithms. Build the skills required for roles such as C++ Developer, Software Engineer, Embedded C/C++ Developer, System Software Engineer and Algorithm Developer.

With strong programming and DSA skills, learners can pursue opportunities across IT services, product companies, engineering organizations and technology startups. Salary growth depends on skills, experience, location and company.

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Embedded C/C++ Developer career opportunities, salary ranges and hiring companies in India

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Embedded C/C++ Developer career opportunities, salary ranges and hiring companies in India

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System Software Engineer career opportunities, salary ranges and hiring companies in India.

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Course Overview

Comprehensive programming training designed for first-year undergraduate students to build a strong foundation in C Programming, C++, Object-Oriented Programming (OOP), STL, and Data Structures & Algorithms through structured learning and practical problem-solving.

This 4-month course follows a progressive learning path, helping students advance from programming fundamentals to beginner-to-intermediate DSA problem solving using C++.

Course Structure

  • Duration: 4 Months
  • Mode: Online & Offline Instructor-Led Training
  • Learning Approach: Structured curriculum with programming exercises and practical problem-solving
  • Academic Level: First-Year Undergraduate
  • Course Level: Beginner to Intermediate
  • Core Areas: C Programming | C++ | OOP | STL | Data Structures & Algorithms
  • Certification: ISO Certified Course

Who Should Enroll

  • First-year undergraduate students starting their programming journey.
  • Beginners interested in learning C and C++ programming.
  • Students preparing for Data Structures & Algorithms and technical interviews.
  • Aspiring software developers building programming and problem-solving skills.
  • Learners interested in Object-Oriented Programming and STL.
  • Students preparing for advanced programming and software development.

Course Outcomes & Skills You Master

C Programming Fundamentals: Learn variables, operators, control flow, arrays, strings, functions, recursion and structured programming.

Memory Management & Advanced C: Develop skills in pointers, structures, unions, dynamic memory allocation and file handling.

C++ & Object-Oriented Programming: Understand classes, objects, constructors, inheritance, polymorphism, encapsulation and abstraction.

STL & Generic Programming: Work with templates, containers, iterators, algorithms, pairs, comparators and lambda expressions.

Data Structures & Algorithms: Learn arrays, strings, searching, sorting, recursion, singly linked lists, stacks and queues.

Problem-Solving Techniques: Understand time and space complexity, brute force, prefix sum, two pointers, basic sliding window and STL-based problem solving.

Programming Foundation: Build a strong foundation for software development, advanced DSA learning and technical programming challenges.

Certification

Earn an ISO Certified Course Certificate upon successful completion of the program, demonstrating your learning and foundational knowledge in C Programming, C++, and Data Structures & Algorithms.

Certification eligibility and issuing details should be mentioned according to GRRAS’s official certification policy.

C Programming, C++ and Data Structures & Algorithms Course Curriculum

The course curriculum is designed to provide a progressive learning journey from programming fundamentals to beginner-to-intermediate Data Structures & Algorithms using C++. Students begin with C Programming, covering variables, operators, control flow, arrays, strings, functions, recursion, pointers, structures, dynamic memory allocation, and file handling.

The second part focuses on C++ Programming and Object-Oriented Programming (OOP), including classes, objects, constructors, inheritance, polymorphism, encapsulation, abstraction, templates, and the Standard Template Library (STL).

The final part introduces Data Structures & Algorithms using C++, covering algorithm analysis, arrays, strings, searching, sorting, recursion, singly linked lists, stacks, queues, and essential problem-solving techniques such as prefix sum, two pointers, and basic sliding window.

This comprehensive curriculum helps learners develop programming logic, write efficient code, understand core data structures, and build a strong foundation for software development and advanced DSA learning.

Topic 1 – Programming Fundamentals and Introduction to C

  • Introduction to Programming 
  • Problem-Solving Approach 
  • Algorithms 
  • Flowcharts 
  • Pseudocode 
  • Introduction to C Language 
  • Features and Applications of C 
  • Structure of a C Program 
  • Compilation and Execution Process 
  • Header Files 
  • main() Function 
  • Comments in C 
  • C Character Set 
  • C Tokens 
  • Keywords 
  • Identifiers 
  • Constants 
  • Operators 
  • Special Symbols 

Topic 2 – Variables, Constants and Data Types

  • Variables 
  • Variable Declaration and Initialization 
  • Rules for Naming Variables 
  • Constants 
  • Literals 
  • Basic Data Types 
  • int 
  • char 
  • float 
  • double 
  • void 
  • Type Modifiers 
  • short 
  • long 
  • signed 
  • unsigned 
  • Size and Range of Data Types 
  • sizeof Operator 
  • Type Conversion 
  • Implicit Type Conversion 
  • Explicit Type Conversion 
  • Type Casting 
  • const Keyword 
  • Symbolic Constants using #define 

Topic 3 – Input and Output Operations

  • Standard Input and Output 
  • printf() 
  • scanf() 
  • Format Specifiers 
  • Escape Sequences 
  • Character Input and Output 
  • getchar() 
  • putchar() 
  • String Input and Output 
  • fgets() 
  • puts() 
  • Formatted Input and Output 

Topic 4 – Operators and Expressions

  • Arithmetic Operators 
  • Relational Operators 
  • Logical Operators 
  • Assignment Operators 
  • Increment and Decrement Operators 
  • Bitwise Operators 
  • Bitwise AND 
  • Bitwise OR 
  • Bitwise XOR 
  • Bitwise NOT 
  • Left Shift 
  • Right Shift 
  • Conditional/Ternary Operator 
  • sizeof Operator 
  • Comma Operator 
  • Expressions 
  • Operator Precedence 
  • Operator Associativity 
  • Type Conversion in Expressions 

Topic 5 – Decision-Making Statements

  • Introduction to Control Flow 
  • if Statement 
  • if-else Statement 
  • Nested if-else 
  • else-if Ladder 
  • Multiple Conditions 
  • switch Statement 
  • break Statement 
  • Nested switch 
  • Conditional/Ternary Operator 
  • Comparison of if-else and switch 

Topic 6 – Looping and Control Statements

  • Introduction to Iteration 
  • while Loop 
  • do-while Loop 
  • for Loop 
  • Nested Loops 
  • break 
  • continue 
  • goto 
  • Loop Control and Execution Flow 
Projects

Programming Practice 

  • Number-Based Problems 
  • Digit-Based Problems 
  • Mathematical Series 
  • Prime Number 
  • Factorial 
  • Fibonacci Series 
  • Palindrome Number 
  • Armstrong Number 
  • Pattern-Based Problems 

Topic 7 – Arrays

One-Dimensional Arrays 

  • Introduction to Arrays 
  • Array Declaration 
  • Array Initialization 
  • Array Input and Output 
  • Array Traversal 
  • Accessing and Updating Elements 
  • Passing Arrays to Functions 
  • Basic Array Operations 
  • Sum and Average 
  • Maximum and Minimum 
  • Reversing an Array 
  • Copying Arrays 
  • Element Frequency 
  • Insertion 
  • Deletion 

Two-Dimensional Arrays 

  • Introduction to Two-Dimensional Arrays 
  • Declaration and Initialization 
  • Matrix Representation 
  • Matrix Input and Output 
  • Row and Column Traversal 
  • Matrix Addition 
  • Matrix Subtraction 
  • Matrix Multiplication 
  • Matrix Transpose 
  • Diagonal Operations 

Multidimensional Arrays 

  • Introduction to Multidimensional Arrays 
  • Basic Memory Representation 

Topic 8 – Strings and Character Arrays

  • Introduction to Strings 
  • Character Arrays 
  • Null Character (‘\0’) 
  • String Declaration and Initialization 
  • String Input and Output 
  • String Traversal 
  • Standard String Library (string.h) 

String Functions 

  • strlen() 
  • strcpy() 
  • strcat() 
  • strcmp() 

String Programming 

  • Finding String Length 
  • Copying a String 
  • Comparing Strings 
  • Concatenating Strings 
  • Reversing a String 
  • Palindrome Checking 
  • Counting Characters 
  • Counting Vowels and Consonants 
  • Word Counting 
  • Character Frequency 
  • Uppercase and Lowercase Conversion

Topic 9 – Functions

  • Introduction to Functions 
  • Advantages of Functions 
  • Function Declaration 
  • Function Definition 
  • Function Call 
  • Function Prototype 
  • Return Type 
  • Parameters and Arguments 
  • Formal Parameters 
  • Actual Parameters 
  • Return Statement 

Types of Functions 

  • No Arguments and No Return Value 
  • Arguments and No Return Value 
  • No Arguments and Return Value 
  • Arguments and Return Value 

Parameter Passing 

  • Call by Value 
  • Passing Addresses to Functions 
  • Passing Arrays to Functions 
  • Passing Strings to Functions 

Additional Concepts 

  • Nested Function Calls 
  • Scope of Variables 
  • Local Variables 
  • Global Variables 

Topic 10 – Recursion

  • Introduction to Recursion 
  • Recursive Functions 
  • Base Condition 
  • Recursive Call 
  • Function Call Stack 
  • Direct Recursion 
  • Recursion vs Iteration 

Recursive Programming 

  • Factorial 
  • Fibonacci Series 
  • Sum of Natural Numbers 
  • Power Calculation 
  • Sum of Digits 
  • GCD 
  • Basic Recursive Problems 

Topic 11 – Storage Classes

  • Scope and Lifetime of Variables 
  • Storage Classes in C 
  • auto 
  • register 
  • static 
  • extern 
  • Local and Global Scope 
  • Static Variables 
  • External Variables 

Topic 12 – Pointers

  • Introduction to Memory Addresses 
  • Introduction to Pointers 
  • Pointer Declaration 
  • Pointer Initialization 
  • Address Operator (&) 
  • Dereference Operator (*) 
  • Accessing Values Through Pointers 
  • NULL Pointer 
  • Pointer Arithmetic 
  • Increment and Decrement of Pointers 
  • Pointer Comparison 
  • Pointer to Pointer 

Pointers and Arrays 

  • Relationship Between Arrays and Pointers 
  • Array Traversal Using Pointers 
  • Pointer Arithmetic with Arrays 

Pointers and Strings 

  • Character Pointers 
  • String Traversal Using Pointers 

Pointers and Functions 

  • Passing Pointers to Functions 
  • Modifying Variables Through Pointers 
  • Passing Arrays Through Pointers 

Topic 13 – Structures

  • Introduction to Structures 
  • Structure Declaration 
  • Structure Variables 
  • Structure Initialization 
  • Accessing Structure Members 
  • Array of Structures 
  • Nested Structures 
  • Passing Structures to Functions 
  • Returning Structures from Functions 
  • Pointer to Structure 
  • Arrow Operator (->) 
  • typedef 

Topic 14 – Unions and Enumeration

Unions 

  • Introduction to Unions 
  • Union Declaration 
  • Union Variables 
  • Accessing Union Members 
  • Memory Allocation in Union 
  • Structure vs Union 

Enumerations 

  • Introduction to enum 
  • Declaring Enumerated Data Types 
  • Using Enumeration Constants 

Topic 15 – Dynamic Memory Allocation

  • Introduction to Memory Management 
  • Static Memory Allocation 
  • Dynamic Memory Allocation 
  • Stack and Heap Memory 
  • Dynamic Memory Allocation using <stdlib.h> 

Memory Management Functions 

  • malloc() 
  • calloc() 
  • realloc() 
  • free() 

Concepts 

  • Dynamic Arrays 
  • Memory Deallocation 
  • Memory Leaks 
  • Dangling Pointers 
  • NULL Pointer Handling

Topic 16 – Preprocessor Directives

  • Introduction to C Preprocessor 
  • Preprocessor Directives 
  • #include 
  • #define 
  • Symbolic Constants 
  • Macros 
  • Function-Like Macros 

Conditional Compilation 

  • #if 
  • #ifdef 
  • #ifndef 
  • #else 
  • #endif 

Header Files 

  • Standard Header Files 
  • User-Defined Header Files 
  • Header Guards 

Topic 17 – File Handling

  • Introduction to File Handling 
  • File Pointer 
  • FILE Data Type 
  • Opening Files 
  • Closing Files 

File Opening Modes 

  • Read Mode 
  • Write Mode 
  • Append Mode 
  • Read/Write Modes 
  • Binary Modes 

File Handling Functions 

  • fopen() 
  • fclose() 
  • fgetc() 
  • fputc() 
  • fgets() 
  • fputs() 
  • fprintf() 
  • fscanf() 
  • fread() 
  • fwrite() 

Additional Concepts 

  • End of File (EOF) 
  • Text Files 
  • Binary Files 
  • Sequential File Access 
  • Reading and Writing Structures to Files 

Topic 18 – Command-Line Arguments and Modular Programming

Command-Line Arguments 

  • Introduction to Command-Line Arguments 
  • argc 
  • argv 
  • Passing Values from Command Line 

Modular Programming 

  • Introduction to Modular Programming 
  • Creating Multiple Source Files 
  • User-Defined Header Files 
  • Function Declarations in Header Files 
  • Separate Function Implementations 
  • External Variables 
  • extern Keyword 
  • Compiling and Linking Multiple Files 
Projects

Practical Programming Coverage 

Students will practice programs based on: 

  • Basic Input and Output 
  • Operators and Expressions 
  • Conditional Statements 
  • Loops 
  • Number-Based Problems 
  • Pattern Problems 
  • Arrays 
  • Matrices 
  • Strings 
  • Functions 
  • Recursion 
  • Pointers 
  • Structures 
  • Unions 
  • Dynamic Memory Allocation 
  • File Handling 
  • Modular Programming 

PART II - Topic 1 – Introduction to C++

  • Introduction to C++ 
  • History and Evolution of C++ 
  • Features of C++ 
  • Applications of C++ 
  • Structure of a C++ Program 
  • Compilation and Execution 
  • Header Files 
  • iostream 
  • namespace 
  • std Namespace 
  • main() Function 
  • cin 
  • cout 
  • endl 
  • Scope Resolution Operator 
  • Reference Variables 
  • bool Data Type 
  • string Data Type 
  • auto Keyword 
  • Type Casting 
  • Default Arguments 
  • Inline Functions 
  • Introduction to Function Overloading 

Topic 2 – C and C++ Comparison

  • Procedural Programming vs Object-Oriented Programming 
  • Program Structure 
  • Functions vs Classes and Objects 
  • Data Hiding 
  • Input and Output 
  • Dynamic Memory Management 
  • Function Overloading 
  • Operator Overloading 
  • References 
  • Structures in C and C++ 
  • Exception Handling 
  • Generic Programming 
  • Standard Library 
  • Templates 
  • STL 
  • Namespaces

Topic 3 – Dynamic Memory Allocation in C++

  • Stack Memory 
  • Heap Memory 
  • Static Memory Allocation 
  • Dynamic Memory Allocation 
  • new 
  • delete 
  • new[] 
  • delete[] 
  • Dynamic Variables 
  • Dynamic Arrays 
  • Dynamic 2D Arrays 
  • Dynamic Objects 
  • Dynamic Arrays of Objects 
  • NULL 
  • nullptr 
  • Memory Leaks 
  • Dangling Pointers 
  • Memory Deallocation 
  • C vs C++ Dynamic Memory Management 

Topic 4 – Introduction to Object-Oriented Programming

  • Introduction to OOP 
  • Procedural Programming vs OOP 
  • Need for OOP 
  • Classes 
  • Objects 
  • Encapsulation 
  • Abstraction 
  • Inheritance 
  • Polymorphism 
  • Advantages of OOP 

Topic 5 – Classes and Objects

  • Class Declaration 
  • Object Creation 
  • Data Members 
  • Member Functions 
  • Access Specifiers 
  • public 
  • private 
  • protected 
  • Member Functions Inside Class 
  • Member Functions Outside Class 
  • Scope Resolution Operator 
  • Multiple Objects 
  • Array of Objects 
  • Objects as Function Arguments 
  • Returning Objects from Functions 

Topic 6 – Constructors and Destructors

Constructors 

  • Default Constructor 
  • Parameterized Constructor 
  • Copy Constructor 
  • Constructor Overloading 
  • Constructor with Default Arguments 
  • Dynamic Constructor 
  • Initialization List 

Destructors 

  • Destructor Syntax 
  • Destructor Execution 
  • Memory Cleanup 
  • Constructor and Destructor Calling Order 

Topic 7 – Encapsulation and Abstraction

Encapsulation 

  • Data Binding 
  • Data Hiding 
  • Access Control 
  • Getter Functions 
  • Setter Functions 

Abstraction 

  • Implementation Hiding 
  • Interface-Based Design 
  • Encapsulation vs Abstraction 

Topic 8 – Inheritance

  • Base Class 
  • Derived Class 
  • Single Inheritance 
  • Multilevel Inheritance 
  • Multiple Inheritance 
  • Hierarchical Inheritance 
  • Hybrid Inheritance 
  • Public Inheritance 
  • Private Inheritance 
  • Protected Inheritance 
  • Constructor in Inheritance 
  • Destructor in Inheritance 
  • Function Overriding 
  • Ambiguity in Multiple Inheritance 
  • Scope Resolution in Inheritance 

Topic 9 – Polymorphism

Compile-Time Polymorphism 

  • Function Overloading 
  • Constructor Overloading 
  • Operator Overloading 

Runtime Polymorphism 

  • Function Overriding 
  • Base Class Pointer 
  • Derived Class Object 
  • Virtual Functions 
  • Pure Virtual Functions 
  • Abstract Classes 
  • Late Binding 
  • Dynamic Binding 

Topic 10 – Additional OOP Concepts

  • this Pointer 
  • Static Data Members 
  • Static Member Functions 
  • Friend Functions 
  • Friend Classes 
  • Constant Objects 
  • Constant Member Functions 
  • Object Pointers 
  • Dynamic Objects 
  • Shallow Copy 
  • Deep Copy 
  • Copy Constructor 
  • Introduction to Exception Handling 
  • try 
  • catch 
  • throw 

Topic 11 – Templates in C++

Function Templates 

  • Function Template Syntax 
  • Generic Functions 
  • Template Function Calls 
  • Multiple Template Parameters 
  • Function Template Overloading 

Class Templates 

  • Class Template Syntax 
  • Template Objects 
  • Multiple Template Parameters 
  • Template Member Functions 
  • Generic Classes 

Topic 12 – Introduction to STL

  • Introduction to STL 
  • Need for STL 
  • Components of STL 
  • Containers 
  • Iterators 
  • Algorithms 
  • Function Objects 
  • Utility Components 

Topic 13 – Sequence Containers

Vector 

  • Declaration and Initialization 
  • push_back() 
  • pop_back() 
  • size() 
  • capacity() 
  • empty() 
  • at() 
  • front() 
  • back() 
  • insert() 
  • erase() 
  • clear() 
  • Traversal 

Array 

  • std::array 
  • Initialization 
  • Element Access 
  • Traversal 

List 

  • std::list 
  • push_front() 
  • push_back() 
  • pop_front() 
  • pop_back() 
  • insert() 
  • erase() 
  • Traversal 

Forward List 

  • std::forward_list 
  • Basic Operations 

Deque 

  • std::deque 
  • Front Operations 
  • Back Operations 
  • Insertion 
  • Deletion 

Topic 14 – Container Adaptors

Stack 

  • LIFO 
  • push() 
  • pop() 
  • top() 
  • empty() 
  • size() 

Queue 

  • FIFO 
  • push() 
  • pop() 
  • front() 
  • back() 
  • empty() 
  • size() 

Priority Queue 

  • Max Heap 
  • Min Heap 
  • push() 
  • pop() 
  • top() 
  • Comparator

Topic 15 – Associative Containers

Set 

  • Ordered Storage 
  • Unique Elements 
  • Insertion 
  • Deletion 
  • find() 
  • count() 

Multiset 

  • Ordered Storage 
  • Duplicate Elements 

Map 

  • Key-Value Pairs 
  • Ordered Keys 
  • Insertion 
  • Updating 
  • Searching 
  • Traversal 

Multimap 

  • Duplicate Keys 
  • Key-Value Storage 

Topic 16 – Unordered Containers

Unordered Set 

  • Hash-Based Storage 
  • Insertion 
  • Deletion 
  • Searching 

Unordered Map 

  • Key-Value Storage 
  • Hashing 
  • Insertion 
  • Updating 
  • Searching 
  • Traversal 

Comparison 

  • set vs unordered_set 
  • map vs unordered_map 

Topic 17 – Iterators

  • Introduction to Iterators 
  • begin() 
  • end() 
  • rbegin() 
  • rend() 
  • Input Iterator 
  • Output Iterator 
  • Forward Iterator 
  • Bidirectional Iterator 
  • Random Access Iterator 
  • Iterator Traversal 
  • Iterator Dereferencing 

Topic 18 – STL Algorithms

  • sort() 
  • reverse() 
  • find() 
  • count() 
  • min() 
  • max() 
  • min_element() 
  • max_element() 
  • binary_search() 
  • lower_bound() 
  • upper_bound() 
  • swap() 
  • next_permutation() 
  • prev_permutation() 
  • accumulate() 
  • fill() 
  • copy() 
  • unique() 

Topic 19 – Pair, Comparator and Lambda

Pair 

  • pair 
  • first 
  • second 
  • Nested Pair 
  • Pair with Containers 

Comparator 

  • Default Comparator 
  • Custom Comparator 
  • Ascending Order 
  • Descending Order 
  • Comparator with Objects 
  • Comparator with Priority Queue 

Lambda 

  • Lambda Syntax 
  • Lambda Expressions 
  • Lambda with STL Algorithms 
  • Custom Sorting using Lambda 
Projects

C++ Foundation Course Outcomes

After completing the C++ Foundation module, students will be able to: 

  1. Understand the fundamental features of C++ and distinguish C++ programming from C programming.
  2. Apply dynamic memory allocation using new, delete, new[] and delete[] safely and effectively.
  3. Design programs using classes, objects, constructors, destructors, encapsulation and abstraction.
  4. Implement inheritance and polymorphism for reusable and extensible program design.
  5. Use function templates and class templates to develop generic and reusable code.
  6. Use Standard Template Library containers, iterators and algorithms for efficient programming.
  7. Apply pairs, comparators and lambda expressions in basic problem-solving scenarios.
  8. Build the C++ programming foundation required for Data Structures & Algorithms.

PART III - Topic 20 – Introduction to Data Structures & Algorithms

  • Introduction to Data Structures 
  • Introduction to Algorithms 
  • Need for Data Structures 
  • Need for Algorithms 
  • Types of Data Structures 
  • Linear Data Structures 
  • Non-Linear Data Structures 
  • Primitive and Non-Primitive Data Structures 
  • Static and Dynamic Data Structures 
  • Abstract Data Types 
  • Problem-Solving Approach 
  • Choosing an Appropriate Data Structure 

Topic 21 – Algorithm Analysis and Complexity

  • Introduction to Algorithm Analysis 
  • Time Complexity 
  • Space Complexity 
  • Best Case 
  • Average Case 
  • Worst Case 
  • Asymptotic Notations 
  • Big O Notation 
  • Omega Notation 
  • Theta Notation 
  • Common Time Complexities 
  • O(1) 
  • O(log n) 
  • O(n) 
  • O(n log n) 
  • O(n²) 
  • Complexity of Loops 
  • Complexity of Nested Loops 
  • Basic Complexity of Recursive Functions 
  • Comparison of Algorithms Based on Complexity 

Topic 22 – Arrays

  • Array Representation 
  • Array Traversal 
  • Accessing Elements 
  • Updating Elements 
  • Insertion 
  • Deletion 
  • Reversing an Array 
  • Finding Maximum and Minimum 
  • Finding Second Largest Element 
  • Frequency of Elements 
  • Duplicate Elements 
  • Removing Duplicates 
  • Rotating an Array 
  • Merging Arrays 
  • Basic Array Problem Solving 

Topic 23 – Two-Dimensional Arrays

  • 2D Array Representation 
  • Row-Wise Traversal 
  • Column-Wise Traversal 
  • Matrix Traversal 
  • Diagonal Traversal 
  • Matrix Transpose 
  • Matrix Rotation Basics 
  • Searching in a Matrix 
  • Basic Matrix Problems 

Topic 24 – Strings

  • String Representation in C++ 
  • String Traversal 
  • Character Frequency 
  • String Reverse 
  • Palindrome String 
  • Anagram Basics 
  • Removing Duplicate Characters 
  • Counting Characters 
  • Counting Words 
  • String Comparison 
  • Substrings 
  • Basic String Manipulation 
  • Basic String Problems 

Topic 25 – Searching Algorithms

Linear Search 

  • Introduction to Linear Search 
  • Linear Search Algorithm 
  • Linear Search Implementation 
  • Time Complexity 
  • Space Complexity 

Binary Search 

  • Introduction to Binary Search 
  • Prerequisites for Binary Search 
  • Iterative Binary Search 
  • Recursive Binary Search 
  • First Occurrence 
  • Last Occurrence 
  • Count of Occurrences 
  • Lower Bound 
  • Upper Bound 
  • Time Complexity 
  • Space Complexity 

Topic 26 – Sorting Algorithms

Bubble Sort 

  • Bubble Sort Algorithm 
  • Working of Bubble Sort 
  • Optimized Bubble Sort 
  • Time Complexity 
  • Space Complexity 

Selection Sort 

  • Selection Sort Algorithm 
  • Working of Selection Sort 
  • Time Complexity 
  • Space Complexity 

Insertion Sort 

  • Insertion Sort Algorithm 
  • Working of Insertion Sort 
  • Time Complexity 
  • Space Complexity 

Merge Sort 

  • Divide and Conquer 
  • Merge Operation 
  • Merge Sort Algorithm 
  • Recursive Implementation 
  • Time Complexity 
  • Space Complexity 

Quick Sort 

  • Divide and Conquer 
  • Pivot Element 
  • Partitioning 
  • Quick Sort Algorithm 
  • Recursive Implementation 
  • Time Complexity 
  • Space Complexity 

Sorting Comparison 

  • Comparison of Sorting Algorithms 
  • Stable and Unstable Sorting 
  • In-Place and Out-of-Place Sorting 

Topic 27 – Recursion in DSA

  • Recursion Review 
  • Base Case 
  • Recursive Case 
  • Recursive Call Stack 
  • Recursive Tree Basics 
  • Factorial Using Recursion 
  • Fibonacci Using Recursion 
  • Sum of Natural Numbers 
  • Sum of Array Elements 
  • Reverse an Array 
  • Reverse a String 
  • Palindrome Using Recursion 
  • Binary Search Using Recursion 
  • Basic Recursive Problem Solving

Topic 28 – Singly Linked List

  • Introduction to Linked List 
  • Need for Linked List 
  • Array vs Linked List 
  • Node Structure 
  • Dynamic Node Creation 
  • Head Pointer 
  • Tail Pointer 
  • Linked List Traversal 
  • Displaying Linked List 
  • Counting Nodes 
  • Searching an Element 
  • Updating Node Data 

Insertion 

  • Insertion at Head 
  • Insertion at Tail 
  • Insertion at a Given Position 

Deletion 

  • Deletion from Head 
  • Deletion from Tail 
  • Deletion from a Given Position 
  • Deletion by Value 

Linked List Operations 

  • Reversing a Linked List 
  • Finding Middle Element 
  • Basic Linked List Problems 

Topic 29 – Stack

  • Introduction to Stack 
  • LIFO Principle 
  • Stack Operations 
  • Push 
  • Pop 
  • Peek / Top 
  • isEmpty 
  • Size 
  • Stack Implementation Using Array 
  • Stack Implementation Using Singly Linked List 
  • Stack Using STL 
  • Stack Overflow 
  • Stack Underflow 

Applications of Stack 

  • Reverse a String 
  • Balanced Parentheses 
  • Expression Basics 
  • Infix Expression 
  • Prefix Expression 
  • Postfix Expression 
  • Infix to Postfix Conversion 
  • Infix to Prefix Conversion 
  • Postfix Evaluation 
  • Basic Stack Problems 

Topic 30 – Queue

  • Introduction to Queue 
  • FIFO Principle 
  • Queue Operations 
  • Enqueue 
  • Dequeue 
  • Front 
  • Rear 
  • isEmpty 
  • Size 
  • Queue Implementation Using Array 
  • Queue Implementation Using Singly Linked List 
  • Queue Using STL 
  • Queue Overflow 
  • Queue Underflow 

Circular Queue 

  • Introduction to Circular Queue 
  • Need for Circular Queue 
  • Circular Queue Representation 
  • Enqueue Operation 
  • Dequeue Operation 
  • Front and Rear Management 

Deque 

  • Introduction to Double-Ended Queue 
  • Insertion from Front 
  • Insertion from Rear 
  • Deletion from Front 
  • Deletion from Rear 
  • Deque Using STL 

Topic 31 – Basic Problem-Solving Techniques

  • Brute Force Approach 
  • Optimized Approach 
  • Array Traversal Techniques 
  • Frequency Counting 
  • Prefix Sum Basics 
  • Two Pointer Technique 
  • Basic Sliding Window 
  • Sorting-Based Problem Solving 
  • Binary Search-Based Problem Solving 
  • Recursion-Based Problem Solving 
  • Linked List-Based Problem Solving 
  • Stack-Based Problem Solving 
  • Queue-Based Problem Solving 

Topic 32 – STL for DSA Problem Solving

  • vector 
  • pair 
  • stack 
  • queue 
  • deque 
  • sort() 
  • reverse() 
  • find() 
  • binary_search() 
  • lower_bound() 
  • upper_bound() 
  • min_element() 
  • max_element() 
  • Basic Custom Comparator 
  • Selecting Appropriate STL Containers 
Projects

 

DSA Course Outcomes

After completing the Data Structures & Algorithms module, students will be able to: 

  1. Understand fundamental data structures and evaluate basic time and space complexity.
  2. Apply arrays, two-dimensional arrays and strings to solve beginner-to-intermediate programming problems.
  3. Implement and compare linear search, binary search and fundamental sorting algorithms.
  4. Use recursion to solve basic algorithmic problems and understand recursive execution flow.
  5. Implement and perform core operations on a Singly Linked List.
  6. Implement Stack and Queue data structures using arrays, linked lists and STL.
  7. Apply basic problem-solving techniques such as brute force, prefix sum, two pointers and sliding window.
  8. Use appropriate C++ STL utilities to write clear and efficient DSA solutions.

Real-World Programming Projects

Apply your programming knowledge through practical projects designed to strengthen your C, C++, OOP, STL, and Data Structures & Algorithms skills. Build real-world applications while developing problem-solving and programming expertise.https://grras.com/wp-admin/post.php?post=34421&action=edit

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Learn directly from certified professionals with years of hands-on experience who guide you through every module, project, and career milestone personally.

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Gain practical exposure by working on live, industry-grade projects that mirror real business challenges, strengthening your technical execution and problem-solving abilities.

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Real-world projects to implement learned concepts.

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Weekly tests to assess progress

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Expert Sessions

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Skill Refinement Tasks

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Enhances students' problem-solving, analytical thinking, and numerical ability-preparing them for competitive exams and placement tests.

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Help students structure professional, impactful resumes

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Placement coordination

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* Organize hiring events and recruitment drives

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Prepare students for various interview formats, including case studies, coding rounds, and group discussions

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Frequently Asked Questions

This course teaches C Programming, C++, Object-Oriented Programming (OOP), STL, and Data Structures & Algorithms using C++. It helps students build programming fundamentals and practical problem-solving skills through a structured 4-month curriculum.

This course is suitable for first-year undergraduate students, beginners learning C and C++, and learners preparing for programming, DSA, technical interviews, and software development.

No, prior programming experience is not mandatory. The course starts with C programming fundamentals and gradually introduces C++, OOP, STL, and Data Structures & Algorithms

You will learn programming fundamentals, pointers, memory management, OOP, STL, arrays, strings, searching, sorting, recursion, linked lists, stacks, queues, and essential problem-solving techniques

Yes, this course is designed for beginners and first-year undergraduate students. It provides a progressive learning path from basic programming concepts to intermediate-level DSA problem-solving.

You will work on practical projects such as a Student Management System, Banking Management System, Library Management System, and DSA-Based Contact Management System.

Yes, you will apply C++ concepts such as classes, objects, encapsulation, inheritance, polymorphism, and file handling to develop practical applications.

These projects help you apply programming concepts to real-world problems while improving logical thinking, coding skills, data management, and problem-solving abilities.

Yes, selected projects incorporate arrays, linked lists, searching, sorting, stacks, queues, and STL containers to help you understand and apply DSA concepts.

Yes, you can use your completed projects as portfolio examples to demonstrate your programming knowledge, C++ skills, and practical experience during internships and entry-level job applications.

This course helps build a foundation for entry-level roles such as Junior Software Developer, C++ Developer, and Software Engineer. Career opportunities depend on your skills, projects, and interview preparation.

The course covers algorithms, complexity analysis, recursion, searching, sorting, and core data structures that help students develop competitive programming and problem-solving skills.

Yes, the course covers fundamental C and C++ concepts, OOP, pointers, arrays, functions, and DSA topics that support academic programming preparation.

Yes, the course builds a foundation for exploring advanced DSA, competitive programming, software development, system programming, and other programming specialisations.

You should focus on writing clean code, solving programming problems, understanding algorithms, using data structures, and building practical projects with C++.

Yes, the course is available through online and offline instructor-led training, depending on the selected learning mode and batch availability.

The curriculum follows a progressive approach, beginning with C programming fundamentals and advancing to C++, OOP, STL, and Data Structures & Algorithms.

Instructor-led training is designed to support concept understanding, programming practice, and problem-solving. Students can clarify their doubts during available learning sessions.

Regular practice is important. Students should revise concepts, solve coding problems, and work on projects consistently to improve their programming skills.

You can continue practising DSA, develop advanced projects, prepare for technical interviews, explore competitive programming, or learn specialised programming technologies.

This course teaches C Programming, C++, Object-Oriented Programming (OOP), STL, and Data Structures & Algorithms using C++. It helps students build programming fundamentals and practical problem-solving skills through a structured 4-month curriculum.

This course is suitable for first-year undergraduate students, beginners learning C and C++, and learners preparing for programming, DSA, technical interviews, and software development.

No, prior programming experience is not mandatory. The course starts with C programming fundamentals and gradually introduces C++, OOP, STL, and Data Structures & Algorithms

You will learn programming fundamentals, pointers, memory management, OOP, STL, arrays, strings, searching, sorting, recursion, linked lists, stacks, queues, and essential problem-solving techniques

Yes, this course is designed for beginners and first-year undergraduate students. It provides a progressive learning path from basic programming concepts to intermediate-level DSA problem-solving.

You will work on practical projects such as a Student Management System, Banking Management System, Library Management System, and DSA-Based Contact Management System.

Yes, you will apply C++ concepts such as classes, objects, encapsulation, inheritance, polymorphism, and file handling to develop practical applications.

These projects help you apply programming concepts to real-world problems while improving logical thinking, coding skills, data management, and problem-solving abilities.

Yes, selected projects incorporate arrays, linked lists, searching, sorting, stacks, queues, and STL containers to help you understand and apply DSA concepts.

Yes, you can use your completed projects as portfolio examples to demonstrate your programming knowledge, C++ skills, and practical experience during internships and entry-level job applications.

This course helps build a foundation for entry-level roles such as Junior Software Developer, C++ Developer, and Software Engineer. Career opportunities depend on your skills, projects, and interview preparation.

The course covers algorithms, complexity analysis, recursion, searching, sorting, and core data structures that help students develop competitive programming and problem-solving skills.

Yes, the course covers fundamental C and C++ concepts, OOP, pointers, arrays, functions, and DSA topics that support academic programming preparation.

Yes, the course builds a foundation for exploring advanced DSA, competitive programming, software development, system programming, and other programming specialisations.

You should focus on writing clean code, solving programming problems, understanding algorithms, using data structures, and building practical projects with C++.

Yes, the course is available through online and offline instructor-led training, depending on the selected learning mode and batch availability.

The curriculum follows a progressive approach, beginning with C programming fundamentals and advancing to C++, OOP, STL, and Data Structures & Algorithms.

Instructor-led training is designed to support concept understanding, programming practice, and problem-solving. Students can clarify their doubts during available learning sessions.

Regular practice is important. Students should revise concepts, solve coding problems, and work on projects consistently to improve their programming skills.

You can continue practising DSA, develop advanced projects, prepare for technical interviews, explore competitive programming, or learn specialised programming technologies.

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