The Data Structures course provides a comprehensive understanding of the fundamental concepts required to efficiently organize, manage, and store data in computer programs. Students will learn about various data structures such as arrays, linked lists, stacks, queues, trees, graphs, and hash tables, along with their real-world applications. The course emphasizes both theoretical concepts and practical implementations, enabling learners to analyze the efficiency of different data structures in terms of time and space complexity. By the end of the program, participants will be proficient in designing optimized algorithms, solving complex computational problems, and applying data structures effectively in software development, competitive programming, and system design.
Module 1: Introduction to Data Structures Basics of Data Structures Importance and Applications Complexity Analysis (Time and Space).
Module 2: Arrays and Strings One-dimensional and Multi-dimensional Arrays Operations: Insertion, Deletion, Traversal String Handling and Manipulation.
Module 3: Linked Lists Singly Linked List nDoubly Linked List Circular Linked List Operations and Applications.
Module 4: Stacks and Queues Stack Implementation (Array & Linked List) Queue Implementation (Simple, Circular, Priority) Applications in Real-world Problems.
Module 5: Trees Binary Trees and Binary Search Trees Tree Traversals (Inorder, Preorder, Postorder) Balanced Trees (AVL, Red-Black Tree) Applications of Trees.
Module 6: Graphs Graph Representation (Adjacency Matrix & List) Graph Traversal (BFS & DFS) Shortest Path Algorithms (Dijkstra, Floyd-Warshall) Minimum Spanning Tree (Prim & Kruskal).
Module 7: Hashing Hash Functions and Collision Resolution Open Addressing and Chaining Applications of Hashing.
Module 8: Advanced Data Structures Heaps and Priority Queues Tries Disjoint Set (Union-Find).
Module 9: Algorithms & Problem Solving Searching Algorithms (Linear, Binary) Sorting Algorithms (Bubble, Merge, Quick, Heap) Algorithm Optimization Techniques
Module 10: Projects & Applications Real-world Case Studies Implementing Data Structures in Projects Competitive Programming Challenges
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