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Data Structure and Algorithm

Data Structures and Algorithms introduces both foundational and advanced concepts critical to computer science and information technology. Key topics include fundamental data structures like arrays, linked lists, stacks, queues, trees, graphs, and hash tables, as well as algorithms for sorting, searching, recursion, and complexity analysis using Big O notation. Students engage in lectures and hands-on programming labs to apply these concepts, focusing on developing strong problem-solving and coding skills. Activities involve implementing various data structures, designing and optimizing algorithms, analyzing algorithm efficiency, and collaborating on projects that address real-world ICT challenges. The course emphasizes best practices and explores current trends in algorithm development and data management within the ICT industry.

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Introduction to Data Structures & Algorithms

Data types, Data structure and Abstract date type, Dynamic memory allocation in C, Introduction to Algorithms, Asymptotic notations and common functions.

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Stacks

Definition, Stack as an ADT, Stack operation, Stack application: Conversion from infix to postfix/prefix expression, Evaluation of postfix/ prefix expressions.

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Queues

Definition, Queue as an ADT, Primitive operations in queue: Enqueue and Dequeue, Linear Queue, Circular Queue, Priority Queue.

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Lists

List and ADT, Array Implementation of Lists, Linked List, Types of Linked List: Singly Linked List, Doubly Linked List, Circular Linked List. Basic operations in Linked List: creation, node insertion and deletion from beginning, end and specified position, Stack and Queue as a Linked List.

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Recursion

Principle of recursion, Comparison between recursion and iteration, Factorial, Fibonacci sequence, GCD, Tower of Hanoi(TOH), Applications and Efficiency of recursion.

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Trees

Concept and definitions, Basic operations in binary tree, Tree height, level and depth, Binary Search Tree, Insertion, Deletion, Traversals (pre-order, post-order and in-order ), Search in BST, AVL tree and Balancing algorithm, Applications of tree.

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Sorting

Introduction and Types of sorting: Internal and External sort, Comparison Sorting Algorithms: Bubble, Selection and Insertion Sort, Divide and Conquer Sorting: Merge, Quick and Heap Sort, Efficiency of Sorting Algorithms.

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Searching

Introduction to searching, Search Algorithms: Sequential search, Binary search, Efficiency of search algorithms, Hashing : Hash function and hash tables, Collision resolution technique,

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Graphs

Definition and Representation, Graph Traversal: BFS and DFS, Minimum Spanning Trees: Kruskal and Prims Algorithm, Shortest Path Algorithms: Dijksrtra Algorithm.

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