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Course Details

Data Structures and Algorithms using C Language

Unlock your programming potential with “Data Structures and Algorithms using C” — a beginner-friendly course to strengthen your logic, problem-solving, and coding skills. Learn arrays, linked lists, stacks, queues, trees, graphs, and key algorithms like sorting, searching, and recursion through clear C implementations and real-world challenges. Perfect for placements or becoming a confident programmer. Enroll now and start your DSA journey!

Students must have in-depth knowledge of C language, as all programs during this course will be implemented in C. It is recommended to revise key topics such as functions, arrays, pointers, structures, and dynamic memory allocation before starting. Additionally, a laptop with a stable internet connection is required, along with curiosity, consistency, and willingness to practice coding regularly. Students should also download Google Meet and Telegram, as these platforms will be used for live classes, updates, and doubt-solving support.

This course is extremely important for building a strong foundation in programming and problem-solving. Data Structures and Algorithms form the backbone of high-level software development, competitive programming, and technical interviews. Learning DSA using C helps students understand how memory works, how to write optimized code, and how to solve real-world problems effectively. Whether you are preparing for placements or improving your logical thinking, this course will give you the knowledge and confidence needed to excel in your tech journey.

The duration of this course is 4.5 months

The course is scheduled to start on – – –. Classes will be held twice a week, every ..day and ..day, from 7:00 PM to 8:45 PM. Sessions will be conducted live on Google Meet, and all updates and notifications will be shared through WhatsApp.

Course fee is only ₹1531

Instractor

Mr. Tamal Mandal

course student (3) (2)

Syllabus

Introduction to Data Structures

  • What are Data Structures and Algorithms

  • Importance and Applications in software, competitive programming, and placements

Arrays

Topics Covered:

  1. Introduction to Arrays (Static Array)

  2. Dynamic Arrays (Using malloc in C)

  3. Array Operations

    • Traversal, Insertion, Deletion, Updating, Searching

  4. Common Array Problems

    • Rotation

    • Element Frequency

    • Maximum/Minimum elements

Linked Lists

Types Covered:

  1. Singly Linked List

  2. Doubly Linked List

  3. Circular Linked List

  4. Circular Doubly Linked List

Topics Covered:

  • Creation, Insertion, Deletion, Traversal

  • Searching and Updating elements

  • Reverse a Linked List

Stacks

Implementation Methods:

  1. Using Array

  2. Using Linked List

Topics Covered:

  • Push, Pop, Peek, IsEmpty operations

  • Applications: Expression evaluation, Undo-Redo

Queues

Implementation Methods:

  1. Using Array

  2. Using Linked List

Other Types:

  • Deque (Double-Ended Queue)

  • pripriority queue

Applications:

  • Job scheduling, process management

Recursion

Topics Covered:

  • Understanding recursive function calls and memory (call stack)

  • Base case and recursive case

  • Practical Examples:

    • Factorial

    • Fibonacci Series

  • How recursion is used in algorithms and data structures

Trees

Types Covered:

  • Binary Search Tree (BST) – Insertion, Deletion, Traversals

  • AVL Tree – Self-balancing BST with rotations

  • Heap Tree – Min-Heap, Max-Heap

  • Huffman Coding Tree – Data Compression

Topics Covered:

  • Traversals: Inorder, Preorder, Postorder

Graphs

Topics Covered:

  1. Representation: Adjacency Matrix, Adjacency List

  2. Graph Traversals: BFS, DFS

Sorting Algorithms:

  • Bubble Sort, Selection Sort, Insertion Sort

  • Quick Sort, Merge Sort, Heap Sort

Heap

Heaps are specialized tree-based data structures used for priority-based operations.

Types Covered:

  • Min-Heap

  • Max-Heap

Topics Covered:

  • Heap Operations: Insertion, Deletion, Heapify

  • Heap Sort

Searching Algorithms:

Linear Search, Binary Search

Hashing:

Hash tables, Collision Handling

Time Complexity & Space Complexity

1. Introduction to Complexity Analysis

  • Importance of analyzing algorithm performance

  • Measuring efficiency in terms of time and space

  • Real-world examples showing optimized vs. unoptimized code


2. Time Complexity (Big O, Big Ω, Big Θ)

  • Big O Notation: Worst-case scenario analysis

  • Big Ω Notation: Best-case scenario analysis

  • Big Θ Notation: Average-case analysis

  • Understanding how input size affects performance

Application to Data Structures & Algorithms:

  • Arrays: Searching, Insertion, Deletion

  • Linked List: Traversal, Insertion, Deletion

  • Stack/Queue: Push, Pop, Enqueue, Dequeue

  • Trees (BST, AVL): Insertion, Deletion, Search

  • Heap: Insert, Delete, Heapify

  • Sorting Algorithms: Bubble, Selection, Insertion, Quick, Merge, Heap Sort

  • Searching Algorithms: Linear, Binary

  • Graph Algorithms: BFS, DFS, Dijkstra’s


3. Space Complexity

  • Memory usage by variables, arrays, linked lists, and recursion

  • Extra memory used by dynamic allocation (malloc in C)

Types of Algorithms:

  • Brute Force
  • Divide and Conquer
  • Greedy Algorithm
  • Dynamic Programming
  • Backtracking

Key Highlights of the Course

  • 130+ DSA Questions Covered – Comprehensive practice from arrays, linked lists, stacks, queues, trees, graphs, recursion, and more.

  • Hands-on Coding – All concepts implemented practically in C language for real-world understanding.

  • Step-by-Step Problem Solving – Learn to approach, analyze, and solve problems efficiently.

  • Placement & Interview Preparation – All questions designed to prepare students for coding interviews and competitive exams.

  • Interactive Live Classes – Doubt-solving support during and after classes.

  • Practical Assignments & Projects – Reinforce learning through real-world problems.

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