PO1: Scientific Knowledge & Foundation: Apply core knowledge of mathematics, statistics, and computer science fundamentals to solve structural and logical problems
PO2: Problem Analysis: Identify, formulate, and analyze complex scientific or data-driven challenges using basic computation principles
PO3: Design & Development: Create software, algorithm scripts, or workflow solutions that meet technical, environmental, and societal needs
PO4: Modern Tool Usage: Select, learn, and apply modern software tools, platforms, and programming languages efficiently.
PO5: Professional Ethics: Understand and apply ethical standards, transparency, and data privacy frameworks in technological deployment
PSO1: Core AI & ML Mastery: Design, develop, and test intelligent computing models using machine learning algorithms, deep learning architectures, and statistical models.
PSO2: Domain Application Frameworks: Apply sub-fields of artificial intelligence—specifically Natural Language Processing (NLP) and Data Analytics—to real-world domains like finance, healthcare, or business.
PSO3: Responsible AI Implementation: Build, scale, and evaluate automated pipelines while identifying and minimizing dataset bias, ensuring ethical AI governance, and enforcing data security compliance
Course Outcomes (CO)
Computer Fundamentals and Office Automation
Sem I2025-2026
CO1: At the End of the Course, The Students will be able to explain different number systems, the historical evolution of computers, and identify key components in a block diagram.
CO2: Learners will demonstrate basic blocks of a computer and fundamental networking
knowledge.
CO3: Learners will create professional-level documents and design visually appealing presentations using word processing software and presentation software.
CO4: Learners will manipulate data within spreadsheets, apply formulas, and generate accurate summaries and visualizations.
CO5: Learners will apply data modelling techniques to analyze, organize, and represent data effectively in various scenarios.
ARTIFICIAL & COMPUTATIONAL INTELLIGENCE
Sem II2025-2026
CO1: Students completing this course will be able to: Explain basic AI terminology, agent models, and the PEAS framework.
CO2: Students completing this course will be able to: Formulate AI problems using search strategies and implement basic algorithms conceptually.
CO3: Understand core machine learning categories and their applications.
CO4: Describe computational intelligence approaches and their role in AI.
CO5: Students completing this course will be able to: Write and execute simple Prolog programs demonstrating logic programming fundamentals.
PYTHON PROGRAMMING AND DATA STRUCTURES
Sem II2025-2026
CO1: After successful completion of the course, students will be able to:
1. Explain the basic features, syntax, data types, and operators of Python programming.
CO2: students will be able to: Apply control flow constructs, functions, and modules to develop structured Python programs.
CO3: students will be able to: Demonstrate the use of sequences, sets, and dictionaries for effective data handling and manipulation.
CO4: students will be able to: Implement file handling techniques and apply exception handling mechanisms for robust applications.
CO5: students will be able to: Develop object-oriented and GUI-based applications using Python.
Course Outcomes (CO)
Introduction to OOP using JAVA
Sem III2025-2026
CO1: Overview of java programming, history and its features
CO2: Understand fundamentals of programming such as variables, conditional and iterative execution, statements, etc
CO3: Understand the principles of arrays, inheritance, packages and multi-threading.
CO4: Understand the Fundamental features of Managing Errors, Exceptions and Applet
Programming.
CO5: Understand the Files concept in java.
OPERATING SYSTEMS
Sem III2025-2026
CO1: Analyse the services and functions of operating systems
CO2: Analyse the concepts of processes in operating system and illustration of the scheduling of processor for a given problem instance
CO3: Analyse memory management techniques, concepts of virtual memory
CO4: To understand Introduction to Unix:- Architecture of Unix, Features of Unix , Unix Commands
CO5: To understand Shell programming and Simple shell program examples
DATA WAREHOUSING AND DATA MINING
Sem IV2025-2026
CO1: To understand the principles of Data warehousing and Data Mining.
CO2: To be familiar with the Data warehouse architecture and its Implementation.
CO3: To know the Architecture of a Data Mining system.
CO4: To understand the various Data preprocessing Methods.
CO5: To perform classification and prediction of data.
INTRODUCTION TO AI
Sem IV2025-2026
CO1: Understand the need of AI and Intelligent Agents.
CO2: Gain knowledge about practical applications of NLP
CO3: Understand knowledge based agents and prepositional logic.
CO4: Gain knowledge about learning agents and decision trees.
CO5: Understand parts, tasks and architecture of Robotics.
Machine Learning using Python
Sem IV2025-2026
CO1: Explain the basic concepts of machine learning.
CO2: Construct supervised learning models.
CO3: Construct unsupervised learning algorithms.
CO4: Evaluate and compare different models
Course Outcomes (CO)
PROBLEM SOLVING USING C
CO1: Understand basic computing concepts, programming paradigms and write structured C programs.
CO2: Apply control flow statements to solve logical and repetitive tasks in C.
CO3: Implement arrays and string operations to manage and manipulate data efficiently.
CO4: Design modular code using functions, recursion, and appropriate parameter passing.
CO5: Utilize pointers and memory operations for effective data handling. Demonstrate competence in dynamic memory allocation and text file processing.
COMPUTER FUNDAMENTALS AND OFFICE AUTOMATION
Sem I2025-2026
CO1: At the End of the Course, The Students will be able to explain different number systems, the historical evolution of computers, and identify key components in a block diagram.
CO2: Learners will demonstrate basic blocks of a computer and fundamental networking knowledge.
CO3: Learners will create professional-level documents and design visually appealing presentations using word processing software and presentation software.
CO4: Learners will manipulate data within spreadsheets, apply formulas, and generate accurate summaries and visualizations.
CO5: Learners will apply data modelling techniques to analyze, organize, and represent data effectively in various scenarios.
DATA STRUCTURES USING C
Sem II2025-2026
CO1: Learners will be able to: Explain algorithm characteristics, time and space complexity, and asymptotic notations with clarity.
CO2: Implement and analyze different types of linked lists, including insertion, deletion, and traversal operations.
CO3: Develop stack and queue data structures using arrays and linked lists, and apply them in expression evaluation.
CO4: Apply efficient searching and sorting algorithms to solve computational problems and evaluate performance trade-offs.
CO5: Construct and traverse tree and graph structures, using them to solve problems like shortest path and spanning trees.
DIGITAL LOGIC DESIGN
Sem II2025-2026
CO1: At the end of the course, students will be able to: Apply concepts of number systems to perform radix conversions and binary arithmetic using signed and unsigned formats.
CO2: Simplify logic functions using Boolean algebra, Karnaugh maps, and universal gates.
CO3: Design and analyze combinational circuits such as half adders, full adders, and subtractors.
CO4: Construct advanced combinational logic modules, including multiplexers, demultiplexers, encoders, decoders, and their hierarchical versions. Realize complex Boolean functions using combinations of logic modules.
CO5: Develop and evaluate sequential circuits such as flip-flops, latches, counters, and shift registers.