Course Description
The Data Structures and Algorithms (DSA) course is designed to help students develop strong programming and problem-solving skills. This course covers fundamental and advanced data structures, algorithm design techniques, searching, sorting, recursion, and time complexity analysis.
Students will learn how to organize, store, process, and manage data efficiently. The course also focuses on coding interview preparation, logical thinking, competitive programming, and real-world software development applications.
Detailed Course Syllabus
Module 1: Introduction to Data Structures
Introduction to Data Structures and Algorithms
Types of Data Structures
Linear and Non-Linear Data Structures
Abstract Data Types (ADT)
Time and Space Complexity
Big O, Big Omega, and Big Theta Notations
Module 2: Arrays and Strings
Introduction to Arrays
One-Dimensional and Two-Dimensional Arrays
Array Traversal and Insertion
Array Deletion and Searching
String Operations
Multidimensional Arrays
Matrix Operations
Two-Pointer Technique
Sliding Window Technique
Array Data Structure, String Algorithms, Array Operations, Matrix Programming, Two Pointer Algorithm
Module 3: Linked Lists
Introduction to Linked Lists
Singly Linked List
Doubly Linked List
Circular Linked List
Insertion and Deletion
Traversing Linked Lists
Reversing a Linked List
Detecting Loops and Cycles
Module 4: Stacks and Queues
Stack Data Structure
Stack Operations: Push, Pop, Peek
Stack Implementation Using Arrays
Stack Implementation Using Linked Lists
Queue Data Structure
Circular Queue
Deque (Double-Ended Queue)
Priority Queue
Applications of Stacks and Queues
Stack Data Structure, Queue Data Structure, Circular Queue, Priority Queue, LIFO, FIFO
Module 5: Searching and Sorting Algorithms
Linear Search
Binary Search
Bubble Sort
Selection Sort
Insertion Sort
Merge Sort
Quick Sort
Heap Sort
Counting Sort
Sorting Algorithm Complexity
Module 6: Trees and Binary Trees
Introduction to Trees
Tree Terminology
Binary Trees
Binary Search Trees (BST)
Tree Traversal Techniques
Inorder, Preorder, and Postorder
Level Order Traversal
AVL Trees
Balanced Binary Trees
Tree Data Structure, Binary Tree, Binary Search Tree, AVL Tree, Tree Traversal Algorithms
Module 7: Graphs
Introduction to Graphs
Directed and Undirected Graphs
Weighted and Unweighted Graphs
Graph Representation
Adjacency Matrix and Adjacency List
Breadth-First Search (BFS)
Depth-First Search (DFS)
Dijkstra’s Algorithm
Minimum Spanning Tree
Kruskal’s and Prim’s Algorithms
Graph Data Structure, Graph Algorithms, BFS, DFS, Dijkstra Algorithm, Graph Traversal
Module 8: Hashing
Introduction to Hashing
Hash Functions
Hash Tables
Collision Handling
Separate Chaining
Open Addressing
Linear Probing
Quadratic Probing
Hash Maps and Hash Sets
Hashing Data Structure, Hash Table, Hash Map, Hash Function, Collision Resolution
Module 9: Advanced Algorithms
Recursion and Backtracking
Divide and Conquer
Greedy Algorithms
Dynamic Programming
Memoization and Tabulation
Knapsack Problem
Longest Common Subsequence
Fibonacci Optimization
Bit Manipulation
Trie Data Structure
Module 10: Coding Interview Preparation
Problem-Solving Techniques
Logical Reasoning
Coding Challenges
LeetCode Problem Solving
HackerRank Practice
Interview-Based DSA Questions
Competitive Programming Basics
Mock Coding Interviews
Practical Projects
Project Name | Concepts Covered |
|---|---|
Student Management System | Arrays, Linked Lists |
Browser History Simulator | Stack |
Ticket Booking Queue System | Queue |
Contact Management System | Hashing, Linked Lists |
File Directory Search | Trees |
Social Network Graph | Graphs, BFS, DFS |
Route Finding Application | Graphs, Dijkstra’s Algorithm |
Search Engine Autocomplete | Trie, Strings |
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Course Page SEO Description
Short Course Content for Website
Data Structures & Algorithms (DSA) Training
Learn the fundamentals of data structures and algorithms with practical programming experience. Our comprehensive DSA course covers arrays, linked lists, stacks, queues, trees, graphs, hashing, searching, sorting, recursion, and dynamic programming.
Course Highlights:
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