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Foundation for business decisions

FREE
Updated 24 Sep 2024
Lessons 5
Enrolled 44
Language English ‎(en)‎
Skill Level Beginner

Course Overview

Total Credit - 4

Lecture per week- 4

The "foundation for business decisions course provides a comprehensive understanding of decision making in business. it covers the basic of decision making, decision making models, management functions and ethical considerations. The course aim to equip students with the knowledge and skills required to meet effective business decisions and address real -world challenges.

Course Content

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Enrolment options

Total Credit - 4

Lecture per week- 4

The "foundation for business decisions course provides a comprehensive understanding of decision making in business. it covers the basic of decision making, decision making models, management functions and ethical considerations. The course aim to equip students with the knowledge and skills required to meet effective business decisions and address real -world challenges.

Skill Level: Beginner
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Credit:4 Lectureper week:3 Practicalper week:2 Course Outcomes (CO): CO1         Differentiate basic data structures (arrays, linked lists, stacks, queues) based on their                                 characteristics,operations, and real-world applications. CO2        Perform basic operations (e.g., )insertion, deletion, search) on fundamental data structures                         using a chosen programming language. CO3       Identify the properties and applications of advanced data structures (trees,graphs). CO4       investigate the properties of various searching and sorting Techniques CO5       Demonstrate critical thinking and problem-solving skills by applying data structures and                              algorithms to address complex computational challenges. CO6      Implement and analyse different data structure algorithms(to solve practical problems Detailed Syllabus:ModuleUnit Content Hrs(45+30)Marks(70)I Introduction to Data Structures and Basic Algorithms  1    Overview of Data Structures: Data type Vs. Data structure, ADT,Definition of Data structure, Data                structure Classification – Linear, Non- Linear (Array, Linked List, Stack, Queue, Tree, Graph)          Introduction to Arrays: Definition, Types (1 Dimensional, 2Dimensional, Multi-Dimensional, Sparse              matrix), Different Array Operations with Algorithm (insertion, deletion, traversal        Structures and Self-referential structures Introduction to Linked list: Definition, Types (Single linked             list,Doublelinked list, Circular linked list- concept only). Singly Linked List Operations with Algorithm           (insertion, deletion,traversal) 2    Introduction to Stack: Definition, stack operations with Algorithm, Applications: recursion, infix to                  postfix - example and Algorithm    Implementation of Stack: using array (overflow & underflow) and     Linkedlist (with algorithm)       Introduction to Queue: Definition, queue operations with Algorithm, Types: Double ended queue (Input        Restricted and Output restricted), Circular queue, Applications       Implementation of Queue: using array and Linked list (withalgorithm)I 3     Non- Linear Data Structures  Introduction to Trees: Basic terminology, Types(Binary tree-        complete,full, skewed etc., Expression Tree)        Properties of Binary tree, Applications. Binary tree representations- using array and linked list 2       Operations on Binary tree- Insertion, Deletion, Traversal- inorder, preorder, postorder - (concepts with        examples)       Algorithm of non-recursive Binary tree traversal         Introduction to Graph: Definition, Basic terminology, Types (Directed,Undirected, Weighted).   Graph         representation –Adjacency list and Adjacency Matrix, Applications. 4      Sorting and Searching : Introduction to Sorting: Definition, Classification (Internal, External)       Internal Sorting Algorithms: Selection sort- Selection sort algorithm,       Exchange sort- Bubble sort algorithm        External Sorting Algorithms: Merge sort- Demonstrate with example.(NoAlgorithm needed)        Advanced sorting Algorithm-: Quick sort- Demonstrate with example.        Introduction to Searching: Linear search and Binary search(Algorithm needed) with example.                      Hashing: Hash Tables, Hash Functions, Different Hash Functions –Division method, Multiplication             method, Mid square method, Folding Method, Collision and Collision resolution Techniques: Open      hashing- Chaining, Closed hashing- Probing5 5    Hands-on Programming in Data Structures: Practical        Implement the following:       1. Basic Operations in a single linked list (Menu driven)       2. Sort the elements in given singly linked list       3. Stack using array.       4. Stack using Linked list       5. Queue using Array       6. Queue using Linked list       7. Sorting algorithms- Selection, Bubble Sort       8. Searching Algorithms- Linear and Binary search

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