Data Structures & Algorithms
| Training Mode | Regular | Fasttrack | Crash |
|---|---|---|---|
| Classroom | Online | 2 Months | 1 Month | 15 Days |
The Data Structures & Algorithms (DSA) Course is a practical, career-oriented program designed for BCA, B.Tech, MCA, Diploma, Engineering students and aspiring software developers who want to strengthen their programming and problem-solving abilities.
Data Structures and Algorithms are the foundation of software engineering and are essential for coding interviews at leading technology companies. This course teaches students how to write optimized code, analyze time complexity, and solve real-world programming problems using C++.
Through live coding sessions, assignments, coding challenges, and practical projects, students develop the analytical thinking required for competitive programming and technical interviews.
Why Learn Data Structures & Algorithms?
A strong understanding of DSA helps programmers write efficient software, optimize application performance, and solve complex computational problems. It is one of the most important skills for software development, product-based companies, and competitive coding.
Who Should Join?
This course is ideal for:
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BCA Students
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B.Tech & Engineering Students
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MCA Students
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Diploma Students
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Competitive Programmers
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Software Development Aspirants
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Students Preparing for Coding Interviews
Learning Outcomes
After completing the Data Structures & Algorithms Course, students will be able to analyze algorithm efficiency, implement core data structures, solve complex coding problems, optimize programs using appropriate algorithms, and confidently prepare for technical interviews and software development careers.
Data Structures & Algorithms Course Syllabus
Module 1 – DSA Fundamentals
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Introduction to Data Structures & Algorithms
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Time Complexity (Big O Notation)
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Space Complexity
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Best, Average & Worst Case Analysis
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Algorithm Design Basics
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Recursion Fundamentals
Module 2 – Arrays & Strings
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One & Two-Dimensional Arrays
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String Manipulation
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Searching Techniques
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Sliding Window
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Prefix Sum
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Two Pointer Technique
Module 3 – Searching & Sorting
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Linear Search
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Binary Search
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Bubble Sort
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Selection Sort
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Insertion Sort
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Merge Sort
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Quick Sort
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Counting Sort
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Complexity Analysis
Module 4 – Linked Lists
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Singly Linked List
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Doubly Linked List
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Circular Linked List
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Insertion & Deletion
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Reversing Linked Lists
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Practical Problems
Module 5 – Stack & Queue
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Stack Implementation
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Queue Implementation
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Circular Queue
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Priority Queue
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Deque
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Expression Evaluation
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Balanced Parentheses
Module 6 – Trees
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Binary Tree
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Binary Search Tree (BST)
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Tree Traversals
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AVL Tree Basics
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Heap Fundamentals
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Priority Queue using Heap
Module 7 – Graphs
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Graph Representation
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BFS (Breadth First Search)
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DFS (Depth First Search)
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Shortest Path Basics
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Topological Sorting
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Connected Components
Module 8 – Hashing & Dynamic Programming
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Hash Tables
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HashMap
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HashSet
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Memoization
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Dynamic Programming Basics
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Common DP Problems
Module 9 – Coding Interview Preparation
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Problem Solving Strategies
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LeetCode Style Questions
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Pattern-Based Questions
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Recursion Problems
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Array & Tree Challenges
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Mock Coding Interviews
Practical Projects
Students will solve real coding problems and develop applications including:
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Student Record Management
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Library Management System
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Maze Solver
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Binary Search Visualizer
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Task Scheduler using Queue
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Contact Management using HashMap
