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Data Structure And Algorithm Course

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Data Structure Course – Learn Algorithms and Problem Solving

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About Data Structure Course

The Data Structures Course is designed to strengthen your programming and problem-solving skills by teaching you how to organize, manage, and store data efficiently. You will learn about arrays, linked lists, stacks, queues, trees, graphs, hash tables, and advanced searching and sorting techniques.

Data Structures are the backbone of efficient coding and competitive programming. They form the basis of how real-world applications like databases, operating systems, and search engines work. Mastering them helps you write faster, memory-optimized programs and crack coding interviews with confidence.

By the end of this course, you’ll be able to apply the right data structure for solving complex problems, optimize your code performance, and build a solid foundation for advanced topics like algorithms and system design.

Data Structure Course Modules

  • ✔ Understanding Data Structures and Algorithms
  • ✔ Types of Data Structures: Linear and Non-linear
  • ✔ Complexity Analysis: Big O, Big Theta, Big Omega
  • ✔ Applications of Data Structures

  • ✔ Introduction to Arrays
  • ✔ Array Operations: Traversal, Insertion, Deletion, Searching, Sorting
  • ✔ Multi-dimensional Arrays
  • ✔ Applications of Arrays

  • ✔ Singly Linked List: Insertion, Deletion, Traversal
  • ✔ Doubly Linked List
  • ✔ Circular Linked List
  • ✔ Applications of Linked Lists

  • ✔ Concept of Stack
  • ✔ Implementation using Arrays and Linked List
  • ✔ Applications: Expression Evaluation, Balanced Parentheses
  • ✔ Infix to Postfix Conversion

  • ✔ Concept of Queue
  • ✔ Implementation using Arrays and Linked List
  • ✔ Circular Queue
  • ✔ Priority Queue and Deque
  • ✔ Applications of Queues

  • ✔ Introduction to Trees
  • ✔ Binary Trees: Traversals (Inorder, Preorder, Postorder)
  • ✔ Binary Search Trees: Insertion, Deletion, Searching
  • ✔ AVL Trees and Rotations
  • ✔ Applications of Trees

  • ✔ Introduction to Graphs
  • ✔ Graph Representations: Adjacency Matrix, Adjacency List
  • ✔ Graph Traversals: BFS, DFS
  • ✔ Applications of Graphs

  • ✔ Hash Tables and Hash Functions
  • ✔ Collision Handling: Chaining, Open Addressing
  • ✔ Heap: Min Heap, Max Heap
  • ✔ Heap Operations and Applications

  • ✔ Linear Search
  • ✔ Binary Search (Iterative & Recursive)
  • ✔ Jump Search
  • ✔ Interpolation Search

  • ✔ Bubble Sort
  • ✔ Selection Sort
  • ✔ Insertion Sort
  • ✔ Merge Sort
  • ✔ Quick Sort
  • ✔ Heap Sort
  • ✔ Counting, Radix, and Bucket Sort

  • ✔ Activity Selection Problem
  • ✔ Fractional Knapsack Problem
  • ✔ Huffman Coding
  • ✔ Minimum Spanning Tree using Kruskal’s Algorithm
  • ✔ Minimum Spanning Tree using Prim’s Algorithm

  • ✔ Fibonacci using Memoization & Tabulation
  • ✔ Longest Common Subsequence (LCS)
  • ✔ Matrix Chain Multiplication
  • ✔ 0/1 Knapsack Problem
  • ✔ Coin Change Problem
  • ✔ Longest Increasing Subsequence (LIS)

  • ✔ Dijkstra’s Algorithm for Shortest Path
  • ✔ Bellman-Ford Algorithm
  • ✔ Floyd-Warshall Algorithm
  • ✔ Topological Sort (DFS/Kahn’s Algorithm)
  • ✔ Cycle Detection in Directed Graph

  • ✔ N-Queens Problem
  • ✔ Rat in a Maze
  • ✔ Sudoku Solver
  • ✔ Graph Coloring Problem
  • ✔ Traveling Salesman Problem (TSP)

FAQ

Data Structures are ways to organize and store data efficiently so it can be accessed and modified effectively.

They form the backbone of efficient programming and problem-solving, especially in competitive coding and interviews.

Yes, a basic understanding of C/C++ or Python programming is recommended.

It covers arrays, linked lists, stacks, queues, trees, graphs, hashing, and algorithms like searching and sorting.

They are used in databases, file systems, networking, operating systems, and search engines.

Yes, most interview questions in top companies like Google, Amazon, and Microsoft are based on Data Structures and Algorithms.

Yes, projects like mini-database systems, pathfinding algorithms, and scheduling systems are included.

Typically 2–3 months with consistent practice.

You can move on to Algorithms, Competitive Programming, and System Design.

Yes, mastery of Data Structures greatly improves your chances in technical job interviews.
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