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
Credit:4 Lecturre per week:3 Practicalper week:2 Total:Hour:5 Course Summary This course provides a comprehensive overview of computing, covering historical milestones, hardware components, software systems, and computational thinking principles. Students will explore the evolution of computing systems, from early pioneers to modern processors and quantum units. The curriculum delves into hardware intricacies, software distinctions, and essential concepts in computer science, emphasizing problem-solving skills and algorithmic thinking. Practical aspects include hands-on experiences with hardware assembling, operating system installation, algorithm and flowchart visualization. Course Outcomes (CO) CO1 Develop a foundational knowledge of computing systems, encompassing their historical development, evolutionar milestones, and the notable contributions key figures in the field. CO2 Acquire familiarity with diverse hardware components constituting a computer system. CO3 Gain practical expertise by engaging in hands- on activities focused on the installation and configuration of diverse hardware components within a computer system. CO4 Explore the spectrum of software types, and actively participate in the partitioning, installation, and configuration of operating systems to cultivate a comprehensive understanding of software systems. CO5 Develop a foundational understanding of computer science as a discipline, examining problems through the lens of computational thinking and cultivating analytical skills to address challenges in the field. CO6 Represent complex problems using algorithmic approaches and enhance problem- solving skills by visualizing solutions through the utilization of various software tools.
Programme : BCA Course Code:BCA1CJ103 /BCA1MN 102 Course Title: Discrete structures for computer application Course Credit: 4 Course Summary : This course provides a foundational understating of essential concepts that are fundamental to computer science and various branches of mathematics. The course explores topic related to propositional logic, sets and relations , Graphs and Trees. Course outcomes : CO1:Aquire a comprehensive understanding of propositional logic and its applications CO2: Able to proficiently define and manipulate sets, analyse relations and functions. CO3: Acquire basic understanding of graph theory including representations and types of graphs, their properties such as connectivity ,cycles, paths and degrees. CO4:Able to understand advanced concepts of graph theory , focusing Euler's graph, Hamiltonian graph, Isomorphism and Homeomorphism.
MODULES MATRICES. VECTORS. DIFFERENTIATION. INTEGRATION. OPEN-ENDED.
Course Code :MAT1MN104 Minor Course Course Summary: This course explores mathematical logic, set theory ,and combinatorics ,covering fundamental ideas of like propositions ,logical equivalences and quantifiers .It introduce set theory concepts such as sets, operations with sets and cardinality .Additionally ,it delves in to functions and matrices along with permutations, combinations and discrete probability in combinatorics . Course Outcomes : CO1: Analyse propositional logic and equivalences CO2: Apply set theory and operations. CO3: Implement functions ,matrices, and combinatorics. SYLLUBUS
Course Details Credit : 4 Lecture per week : 4 Total Hours : 60 Course Summary This course provides a comprehensive overview of computing, covering historical milestones, hardware components, software systems, and computational thinking principles. Students will explore the evolution of computing systems, from early pioneers to modern processors and quantum units. The curriculum delves into hardware intricacies, software distinctions, and essential concepts in computer science, emphasizing problem-solving skills and algorithmic thinking. Practical aspects include hands-on experiences with hardware assembling, operating system installation, algorithm and flowchart visualization. Course Outcomes (CO) CO1: Develop foundational knowledge of computing systems, including their history, evolution, and key contributors. CO2: Acquire familiarity with diverse hardware components of a computer system. CO3: Gain practical expertise in installing and configuring various hardware components. CO4: Understand software systems through partitioning, installation, and configuration of operating systems. CO5: Develop a foundational understanding of computer science, focusing on computational thinking and problem-solving. CO6: Represent and solve complex problems using algorithmic approaches and various software tools.
Contact Hours per Week: 6 (3L + 3P)Number of Credits: 3Number of Contact Hours: 96 Hrs.Course Evaluation: Internal: 15 Marks + External: 60 Marks Objectives To review on concept of OOP. To learn Java Programming Environments. To practice programming in Java. To learn GUI Application development in JAVA. Course Outcomes CO1. Knowledge of the structure and model of the Java programming language,CO2.Use the Java programming language for various programming technologiesCO3.Develop software in the Java programming language,CO4.Evaluate user requirements for software functionality required to decide whetherthe Java programming language can meet user requirements
