BCA- Lateral Entry

Fee Type	Amount
Programme Fees (per Semester)	₹55000
Examination Fees	₹3000
International Fee (USD)	$3200

Slab	>=60% - 74.99%	>=75% - 89.99%	>=90% & Above
Fee	₹50000	₹45000	₹40000

Course Curriculum

3RD SEMESTER SUBJECTS

This course introduces Python programming fundamentals, covering syntax, data types, operators, control structures, functions, string handling, and an introduction to object-oriented programming, enabling students to design, develop, and debug structured Python programs for problem-solving.

Course Outcome:

CO1: Understand the fundamentals of Python programming, its features, and application areas.
CO2: Apply operators, expressions, and control structures to write logical Python programs.
CO3: Develop and use functions, modules, and string operations for structured programming.
CO4: Implement Python data structures such as lists, tuples, sets, and dictionaries to organize and manipulate data.
CO5: Apply object-oriented programming concepts including classes, objects, and inheritance in Python.
CO6: Handle exceptions and perform file operations to build robust Python applications.

This practical course provides hands-on experience in Python programming, covering basic programs, control structures, functions, string manipulation, lists, tuples, dictionaries, and object-oriented concepts, enabling students to design, test, and implement Python programs for real-world problem-solving.

Course Outcome:

CO1: Write and execute basic Python programs using variables, operators, and control structures.
CO2: Develop modular programs using functions and string-handling techniques.
CO3: Implement and manipulate Python data structures such as lists, tuples, sets, and dictionaries.
CO4: Design programs using object-oriented concepts including classes, objects, and inheritance.
CO5: Handle exceptions and perform file handling operations in Python programs.
CO6: Debug and test Python programs to solve practical computational problems.

This course provides a comprehensive understanding of linear and non-linear data structures, including arrays, stacks, queues, linked lists, trees, and graphs, along with searching and sorting techniques, enabling students to select and implement appropriate data structures for efficient problem-solving.

Course Outcome:

CO1: Understand the concept, classification, and applications of data structures.
CO2: Implement arrays and analyze algorithms using time and space complexity.
CO3: Design and apply stacks and queues to solve computational problems.
CO4: Implement linked lists and perform operations such as insertion, deletion, and traversal.
CO5: Construct and traverse tree structures, including binary and binary search trees.
CO6: Apply graph representations and searching/sorting algorithms for efficient data processing.

This practical course provides hands-on experience in implementing linear and non-linear data structures such as arrays, stacks, queues, linked lists, trees, and graphs, along with searching and sorting algorithms, enabling students to develop efficient programs for data organization and manipulation.

Course Outcome:

CO1: Implement array-based operations and analyze their efficiency.
CO2: Develop programs using stacks and queues for problem-solving.
CO3: Implement singly, doubly, and circular linked lists with various operations.
CO4: Construct and traverse binary trees and binary search trees.
CO5: Implement graph representations and traversal algorithms.
CO6: Apply searching and sorting algorithms to organize and retrieve data efficiently.

This course introduces the principles and practices of software engineering, covering software development life cycle models, requirement analysis, software design, coding standards, testing strategies, and project management, enabling students to apply systematic approaches to develop reliable and maintainable software.

Course Outcome:

CO1: Understand the fundamental concepts, characteristics, and process models of software engineering.
CO2: Perform requirement analysis and prepare software requirement specifications.
CO3: Apply software design principles, including architectural and modular design techniques.
CO4: Apply coding standards and software testing strategies to ensure software quality.
CO5: Understand software project management concepts, including estimation, scheduling, and risk management.
CO6: Apply software maintenance and quality assurance practices to real-world software projects.

This course introduces students to emerging Artificial Intelligence tools and technologies, covering generative AI, prompt engineering, AI-based productivity and content-creation tools, and their applications across domains, enabling students to effectively use AI tools to enhance learning, creativity, and problem-solving.

Course Outcome:

CO1: Understand the fundamental concepts of Artificial Intelligence and emerging AI tools.
CO2: Apply prompt engineering techniques to interact effectively with generative AI tools.
CO3: Use AI-based tools for content creation, documentation, and presentation development.
CO4: Apply AI tools for data analysis, research, and productivity enhancement.
CO5: Evaluate the ethical considerations and limitations of using AI tools.
CO6: Integrate AI tools into academic and real-world problem-solving tasks.

This course develops advanced entrepreneurial thinking, focusing on scaling business ventures, financial planning, marketing strategies, and leadership skills, enabling students to plan, launch, and sustain entrepreneurial ventures in dynamic business environments.

Course Outcome:

CO1: Explain advanced concepts of entrepreneurship related to venture scaling and sustainability.
CO2: Apply financial planning and resource management techniques for entrepreneurial ventures.
CO3: Develop marketing and branding strategies for new business ventures.
CO4: Demonstrate leadership and team-building skills required for managing entrepreneurial ventures.
CO5: Evaluate strategies for scaling and sustaining business ventures in competitive markets.
CO6: Apply entrepreneurial planning techniques to launch a viable business venture.

This course introduces full-stack web development using the MERN stack, covering MongoDB for database management, Express.js for server-side development, React.js for building user interfaces, and Node.js for backend runtime, enabling students to design and develop dynamic, database-driven web applications.

Course Outcome:

CO1: Understand the fundamentals of full-stack web development and the MERN stack architecture.
CO2: Design and implement NoSQL databases using MongoDB.
CO3: Develop server-side applications and RESTful APIs using Node.js and Express.js.
CO4: Build interactive and responsive user interfaces using React.js.
CO5: Integrate front-end and back-end components to build complete web applications.
CO6: Deploy and manage a full-stack web application.

This practical course provides hands-on experience in building full-stack web applications using MongoDB, Express.js, React.js, and Node.js, covering database design, API development, front-end component creation, and application integration, enabling students to develop complete, functional web applications.

Course Outcome:

CO1: Design and implement collections and documents using MongoDB.
CO2: Develop RESTful APIs using Node.js and Express.js.
CO3: Build reusable UI components and manage state using React.js.
CO4: Connect front-end applications to back-end APIs and databases.
CO5: Implement authentication and basic security in a MERN application.
CO6: Develop and deploy a complete full-stack web application project.

This course introduces the fundamentals of data analytics, covering data collection, data cleaning, exploratory data analysis, descriptive statistics, and data visualization techniques, enabling students to analyze and interpret data to support informed decision-making.

Course Outcome:

CO1: Understand the fundamental concepts, types, and process of data analytics.
CO2: Apply data cleaning and preprocessing techniques to prepare data for analysis.
CO3: Perform exploratory data analysis using descriptive statistical measures.
CO4: Apply data visualization techniques to represent and interpret data.
CO5: Understand the basics of predictive analytics and its applications.
CO6: Interpret analytical results to support data-driven decision-making.

This practical course provides hands-on experience in data analytics tools and techniques, covering data import and cleaning, exploratory data analysis, statistical computations, and creation of visualizations and dashboards, enabling students to analyze real-world datasets effectively.

Course Outcome:

CO1: Import, clean, and preprocess datasets using data analytics tools.
CO2: Perform exploratory data analysis on real-world datasets.
CO3: Compute descriptive statistical measures using analytics software.
CO4: Create charts, graphs, and visualizations to represent data insights.
CO5: Build simple dashboards to summarize and present analytical findings.
CO6: Interpret and report insights derived from data analysis.

This course introduces the concepts and techniques of multimedia and animation production, covering text, image, audio, and video elements, principles of animation, and the use of multimedia authoring tools, enabling students to design and produce multimedia content and basic animations.

Course Outcome:

CO1: Understand the fundamental concepts and elements of multimedia systems.
CO2: Apply image and audio editing techniques to create multimedia content.
CO3: Understand video editing concepts and produce basic video content.
CO4: Understand the principles and types of animation.
CO5: Create 2D animations using animation software tools.
CO6: Design and produce an integrated multimedia project.

This practical course provides hands-on experience in multimedia and animation production, covering image and audio editing, video editing, and 2D animation creation using industry-standard software tools, enabling students to design and produce multimedia and animated content.

Course Outcome:

CO1: Edit and enhance images using multimedia editing software.
CO2: Perform basic audio editing and mixing for multimedia projects.
CO3: Edit and produce short video clips using video editing tools.
CO4: Create 2D animations using animation software.
CO5: Combine multimedia elements to create an integrated multimedia presentation.
CO6: Design and produce a complete multimedia or animation project.

4TH SEMESTER SUBJECTS

This course introduces the fundamentals of Artificial Intelligence and Soft Computing, covering problem-solving through search techniques, knowledge representation, expert systems, fuzzy logic, artificial neural networks, and genetic algorithms, enabling students to understand and apply intelligent computing techniques to real-world problems.

Course Outcome:

CO1: Understand the fundamental concepts, history, and applications of Artificial Intelligence.
CO2: Apply search techniques and problem-solving strategies to solve AI-based problems.
CO3: Understand knowledge representation techniques and the working of expert systems.
CO4: Apply fuzzy logic concepts and fuzzy set operations to handle uncertainty in real-world problems.
CO5: Understand the fundamentals of artificial neural networks and their learning mechanisms.
CO6: Apply genetic algorithms and other soft computing techniques to optimize computational problems.

This practical course provides hands-on experience in implementing Artificial Intelligence and Soft Computing techniques, including search algorithms, knowledge-based systems, fuzzy logic operations, neural network models, and genetic algorithms, enabling students to design and evaluate intelligent systems for problem-solving.

Course Outcome:

CO1: Implement basic AI search algorithms to solve computational problems.
CO2: Develop simple knowledge-based and rule-based expert systems.
CO3: Implement fuzzy set operations and fuzzy inference systems.
CO4: Design and simulate artificial neural network models for pattern recognition.
CO5: Implement genetic algorithms to solve optimization problems.
CO6: Evaluate and compare the performance of different soft computing techniques.

This course provides a comprehensive understanding of computer network fundamentals, covering network models, the OSI and TCP/IP reference models, data communication, network devices, addressing, routing, and network security, enabling students to understand the design and functioning of modern computer networks.

Course Outcome:

CO1: Understand the basic concepts, types, and topologies of computer networks.
CO2: Explain the layered architecture of the OSI and TCP/IP reference models.
CO3: Apply data link layer concepts, including error detection, correction, and medium access control.
CO4: Understand network layer concepts, including IP addressing, subnetting, and routing algorithms.
CO5: Apply transport layer protocols and concepts for reliable data communication.
CO6: Understand application layer protocols and fundamentals of network security.

This practical course provides hands-on experience in computer networking concepts, including network cabling, IP addressing, subnetting, configuration of network devices, and use of networking commands and simulation tools, enabling students to design, configure, and troubleshoot basic computer networks.

Course Outcome:

CO1: Identify and work with networking devices, cables, and connectors.
CO2: Configure IP addressing and subnetting for a given network topology.
CO3: Use networking commands and utilities for network diagnosis and troubleshooting.
CO4: Configure basic routing and switching using networking simulation tools.
CO5: Implement and test simple client-server network applications.
CO6: Analyze network traffic and apply basic network security configurations.

This course introduces the fundamental concepts of database management systems, covering data models, relational database design, normalization, SQL, transaction management, and concurrency control, enabling students to design, implement, and manage efficient and reliable database systems.

Course Outcome:

CO1: Understand the fundamental concepts, architecture, and advantages of database management systems.
CO2: Design entity-relationship models and convert them into relational database schemas.
CO3: Apply normalization techniques to eliminate redundancy and ensure data integrity.
CO4: Write and execute SQL queries for data definition, manipulation, and retrieval.
CO5: Understand transaction management concepts, including ACID properties and concurrency control.
CO6: Understand database recovery techniques and basics of database security.

This practical course provides hands-on experience in designing and implementing relational databases, covering ER modeling, table creation, SQL queries, joins, subqueries, views, and transaction control, enabling students to develop and manage functional database applications.

Course Outcome:

CO1: Design ER diagrams and convert them into relational database schemas.
CO2: Create and manage database tables using SQL data definition commands.
CO3: Perform data manipulation operations using SQL insert, update, and delete commands.
CO4: Write complex SQL queries involving joins, subqueries, and aggregate functions.
CO5: Implement views, indexes, and constraints to ensure data integrity.
CO6: Apply transaction control commands to manage database transactions effectively.

This course introduces the fundamentals of Linux operating system administration, covering file system management, user and group administration, process management, shell scripting, and system security, enabling students to install, configure, and manage Linux-based systems.

Course Outcome:

CO1: Understand the architecture, features, and file system of the Linux operating system.
CO2: Manage users, groups, and file permissions in a Linux environment.
CO3: Perform process management and system monitoring tasks in Linux.
CO4: Write shell scripts to automate administrative tasks.
CO5: Configure and manage basic network services in Linux.
CO6: Apply basic system security and backup practices in Linux administration.

This practical course provides hands-on experience in Linux system administration, covering installation, file and user management, shell scripting, process handling, and basic network configuration, enabling students to perform essential administrative tasks on Linux-based systems.

Course Outcome:

CO1: Install and configure a Linux operating system.
CO2: Perform file, directory, and permission management using Linux commands.
CO3: Create and manage users and groups in a Linux environment.
CO4: Write and execute shell scripts to automate routine tasks.
CO5: Monitor and manage system processes in Linux.
CO6: Configure basic network settings and services in Linux.

This course introduces the fundamentals of Java programming, covering syntax, data types, control structures, object-oriented programming concepts, and exception handling, enabling students to design, develop, and debug structured and object-oriented Java applications.

Course Outcome:

CO1: Understand the fundamentals, features, and application areas of Java programming.
CO2: Apply operators, expressions, and control structures to write logical Java programs.
CO3: Implement object-oriented programming concepts including classes, objects, and constructors in Java.
CO4: Apply inheritance, polymorphism, and interfaces to design robust Java applications.
CO5: Handle exceptions to build reliable and fault-tolerant Java programs.
CO6: Understand the basics of multithreading and file handling in Java.

This practical course provides hands-on experience in Java programming, covering basic programs, control structures, object-oriented concepts, exception handling, and file operations, enabling students to design, implement, and test Java applications.

Course Outcome:

CO1: Write and execute basic Java programs using variables, operators, and control structures.
CO2: Implement classes, objects, and constructors to develop object-oriented Java programs.
CO3: Apply inheritance, polymorphism, and interfaces in Java applications.
CO4: Handle exceptions to develop robust Java programs.
CO5: Implement multithreading concepts in Java applications.
CO6: Perform file handling operations to read and write data in Java programs.

This course introduces the concepts of data warehousing and data mining, covering data warehouse architecture, OLAP operations, data preprocessing, and mining techniques such as classification, clustering, and association rule mining, enabling students to extract meaningful patterns and knowledge from large datasets.

Course Outcome:

CO1: Understand the concepts, architecture, and components of data warehousing.
CO2: Apply OLAP operations for multidimensional data analysis.
CO3: Perform data preprocessing techniques, including cleaning, integration, and transformation.
CO4: Apply classification techniques to build predictive data mining models.
CO5: Apply clustering techniques to group and analyze data patterns.
CO6: Apply association rule mining to discover relationships within datasets.

This practical course provides hands-on experience in data warehousing and data mining techniques, covering data preprocessing, OLAP operations, and implementation of classification, clustering, and association rule mining algorithms, enabling students to analyze datasets and extract meaningful patterns using data mining tools.

Course Outcome:

CO1: Perform data preprocessing tasks such as cleaning and transformation on real datasets.
CO2: Implement OLAP operations for multidimensional data analysis.
CO3: Implement classification algorithms using data mining tools.
CO4: Implement clustering algorithms to group similar data patterns.
CO5: Implement association rule mining algorithms to discover data relationships.
CO6: Interpret and present results obtained from data mining experiments.

This course develops logical reasoning and analytical problem-solving skills, covering numerical ability, logical reasoning, data interpretation, and quantitative aptitude, enabling students to enhance their analytical thinking for academic and competitive examinations.

Course Outcome:

CO1: Apply numerical ability concepts to solve quantitative problems.
CO2: Solve logical reasoning problems using systematic approaches.
CO3: Interpret and analyze data presented in various formats.
CO4: Apply problem-solving techniques to competitive examination-style questions.
CO5: Improve speed and accuracy in solving analytical problems.

This course introduces the fundamental concepts of environmental science, covering natural resources, ecosystems, biodiversity, environmental pollution, and sustainable development, enabling students to understand environmental issues and develop responsible practices towards environmental conservation.

Course Outcome:

CO1: Understand the basic concepts and importance of environmental science.
CO2: Explain the structure and function of ecosystems and biodiversity conservation.
CO3: Identify causes, effects, and control measures of environmental pollution.
CO4: Understand the concept and importance of sustainable development.
CO5: Apply environmentally responsible practices in personal and professional life.

This course focuses on advanced entrepreneurial practices, covering business scaling strategies, innovation management, funding and investment options, and sustainable business practices, enabling students to develop and manage growth-oriented entrepreneurial ventures.

Course Outcome:

CO1: Explain advanced strategies for scaling and growing a business venture.
CO2: Apply innovation management techniques to entrepreneurial ventures.
CO3: Understand various funding and investment options available for startups.
CO4: Develop strategies for building sustainable and socially responsible businesses.
CO5: Evaluate risks and challenges associated with entrepreneurial growth.
CO6: Apply entrepreneurial concepts to develop a business growth plan.

5TH SEMESTER SUBJECTS

This course introduces the fundamentals of Cloud Computing, covering cloud service and deployment models, virtualization, cloud architecture, cloud storage, and major cloud platforms, enabling students to understand how cloud technologies are designed, deployed, and utilized for scalable computing solutions.

Course Outcome:

CO1: Understand the fundamental concepts, characteristics, and evolution of Cloud Computing.
CO2: Differentiate between cloud service models (IaaS, PaaS, SaaS) and deployment models.
CO3: Understand virtualization concepts and their role in enabling cloud infrastructure.
CO4: Explain cloud architecture, storage, and networking components.
CO5: Compare and evaluate major cloud service platforms and their offerings.
CO6: Identify the benefits, challenges, and real-world applications of cloud computing.

This practical course provides hands-on experience with cloud platforms, covering account and resource setup, virtual machine creation, cloud storage configuration, and deployment of basic applications, enabling students to gain practical exposure to working with cloud computing environments.

Course Outcome:

CO1: Create and configure accounts and resources on a cloud computing platform.
CO2: Set up and manage virtual machines on a cloud environment.
CO3: Configure and use cloud storage services for data management.
CO4: Deploy basic applications and services using cloud platform tools.
CO5: Monitor and manage cloud resources for optimal utilization.
CO6: Apply basic access control and security settings within a cloud environment.

This course provides a comprehensive understanding of network security principles and cryptographic techniques, covering symmetric and asymmetric encryption, hashing, digital signatures, authentication protocols, and network security mechanisms, enabling students to design and implement secure communication systems.

Course Outcome:

CO1: Understand the fundamental concepts and goals of network security.
CO2: Apply symmetric key cryptographic algorithms for secure data transmission.
CO3: Apply asymmetric key cryptographic algorithms and public key infrastructure concepts.
CO4: Use hashing techniques and digital signatures to ensure data integrity and authentication.
CO5: Understand network security protocols and mechanisms for securing communication.
CO6: Analyze common network attacks and apply appropriate countermeasures.

This practical course provides hands-on experience in implementing cryptographic algorithms and network security techniques, including encryption/decryption, hashing, digital signatures, and basic security tools, enabling students to apply security concepts to protect data and communication.

Course Outcome:

CO1: Implement classical and modern symmetric encryption algorithms.
CO2: Implement asymmetric encryption algorithms for secure key exchange.
CO3: Apply hashing algorithms to verify data integrity.
CO4: Generate and verify digital signatures for authentication purposes.
CO5: Use security tools to analyze and monitor network traffic.
CO6: Apply basic security configurations to protect systems from common attacks.

This course develops technical writing and documentation skills, covering the principles of clear and precise writing, technical reports, manuals, research papers, and professional documentation, enabling students to effectively communicate technical information for academic and workplace purposes.

Course Outcome:

CO1: Understand the principles and characteristics of effective technical writing.
CO2: Write clear, concise, and well-structured technical documents and reports.
CO3: Apply appropriate formatting, style, and referencing standards in technical writing.
CO4: Prepare user manuals, proposals, and process documentation for technical audiences.
CO5: Develop research papers and technical articles following academic writing conventions.
CO6: Edit and proofread technical documents to improve clarity and accuracy.

This course evaluates the practical industry exposure gained by students during their summer training, covering the assessment of technical skills acquired, project work undertaken, and professional experience gained, enabling students to consolidate and present their learning from real-world work environments.

Course Outcome:

CO1: Demonstrate technical skills and knowledge acquired during industrial summer training.
CO2: Document the training experience through a structured training report.
CO3: Present the work undertaken during training in a clear and organized manner.
CO4: Reflect on the practical application of academic concepts in a professional setting.
CO5: Evaluate personal and professional growth achieved through industry exposure.

This course enables students to apply the knowledge and skills gained throughout the programme to design and develop a substantial project, covering problem identification, requirement analysis, system design, implementation, and documentation, fostering independent and applied learning through a real-world capstone project.

Course Outcome:

CO1: Identify a real-world problem and define project objectives and scope.
CO2: Perform requirement analysis and design an appropriate system or solution.
CO3: Apply technical skills and tools to implement the proposed project.
CO4: Test and evaluate the developed project against defined requirements.
CO5: Prepare comprehensive project documentation following standard formats.
CO6: Present and defend the project work through demonstrations and reports.

This course introduces the fundamentals of mobile application development, covering mobile app architecture, user interface design, application components, data storage, and deployment, enabling students to design and develop functional mobile applications for Android or cross-platform environments.

Course Outcome:

CO1: Understand the fundamentals of mobile application development and mobile app architecture.
CO2: Design user interfaces and layouts for mobile applications.
CO3: Implement application components such as activities, fragments, and navigation.
CO4: Apply data storage techniques, including local databases, in mobile applications.
CO5: Integrate APIs and external services into mobile applications.
CO6: Test, debug, and deploy mobile applications.

This practical course provides hands-on experience in developing mobile applications, covering interface design, application component implementation, data storage, API integration, and testing, enabling students to build and deploy complete mobile applications.

Course Outcome:

CO1: Design and implement user interfaces for mobile applications.
CO2: Develop application screens using activities, fragments, and navigation components.
CO3: Implement local data storage in mobile applications.
CO4: Integrate APIs and external services into a mobile application.
CO5: Test and debug mobile applications for functionality and usability.
CO6: Build and deploy a complete mobile application project.

This course introduces the principles and practices of UI/UX design, covering user research, wireframing, prototyping, visual design principles, usability, and design tools, enabling students to design intuitive and user-centered interfaces for digital products.

Course Outcome:

CO1: Understand the fundamental concepts and principles of UI/UX design.
CO2: Conduct user research and define user personas and requirements.
CO3: Create wireframes and prototypes for digital interfaces.
CO4: Apply visual design principles, including layout, color, and typography.
CO5: Evaluate usability and apply user-centered design practices.
CO6: Design a complete UI/UX solution for a digital product.

This practical course provides hands-on experience in UI/UX design tools and techniques, covering wireframing, prototyping, visual design, and usability testing, enabling students to design and evaluate user interfaces for digital applications.

Course Outcome:

CO1: Create wireframes for digital application interfaces using design tools.
CO2: Develop interactive prototypes to represent user flows.
CO3: Apply visual design elements to create polished interface designs.
CO4: Conduct basic usability testing on designed interfaces.
CO5: Refine designs based on feedback and usability findings.
CO6: Design and present a complete UI/UX project.

This course introduces the fundamentals of Search Engine Optimization, covering keyword research, on-page and off-page optimization techniques, technical SEO, content optimization, and performance analysis, enabling students to improve the visibility and ranking of websites on search engines.

Course Outcome:

CO1: Understand the fundamental concepts and importance of Search Engine Optimization.
CO2: Perform keyword research and analysis for SEO planning.
CO3: Apply on-page optimization techniques to improve website content and structure.
CO4: Apply off-page optimization techniques, including link building strategies.
CO5: Understand technical SEO factors affecting website performance and ranking.
CO6: Analyze SEO performance using analytics and reporting tools.

This practical course provides hands-on experience in implementing SEO techniques, covering keyword research, on-page and off-page optimization, technical SEO audits, and performance tracking using SEO tools, enabling students to optimize websites for improved search engine visibility.

Course Outcome:

CO1: Perform keyword research using SEO tools.
CO2: Apply on-page optimization techniques to a website.
CO3: Implement basic off-page optimization and link-building activities.
CO4: Conduct a technical SEO audit of a website.
CO5: Track and analyze website performance using analytics tools.
CO6: Prepare an SEO report summarizing optimization efforts and results.

This course focuses on advanced entrepreneurial execution, covering business plan development, pitching techniques, risk management, and strategies for sustaining and exiting a venture, enabling students to refine and present a comprehensive entrepreneurial plan.

Course Outcome:

CO1: Develop a comprehensive business plan for an entrepreneurial venture.
CO2: Apply effective pitching techniques to present a business idea.
CO3: Identify and manage risks associated with running a business venture.
CO4: Understand strategies for sustaining long-term business growth.
CO5: Explore exit strategies and succession planning for business ventures.
CO6: Present a complete entrepreneurial plan for evaluation.

6TH SEMESTER (OPTION: A) SUBJECTS

This course provides students with structured industry exposure through a period of training in an organizational environment, covering real-world work practices, professional conduct, and application of academic knowledge to practical tasks, enabling students to develop workplace-ready skills and industry insight.

Course Outcome:

CO1: Understand the working environment, culture, and practices of an industrial organization.
CO2: Apply academic knowledge and skills to practical, real-world work assignments.
CO3: Develop professional and workplace communication and interpersonal skills.
CO4: Document the training experience through a structured industrial training report.
CO5: Evaluate personal and professional growth achieved through industrial exposure.

This course is the culmination of the capstone project initiated earlier, focusing on the complete implementation, testing, refinement, and final deployment of the project, along with comprehensive documentation and presentation, enabling students to demonstrate end-to-end application of their academic learning to a real-world solution.

Course Outcome:

CO1: Refine the project design based on feedback from the earlier capstone phase.
CO2: Complete the implementation of the proposed system or solution.
CO3: Perform thorough testing and validation of the developed project.
CO4: Optimize and finalize the project for deployment or practical use.
CO5: Prepare complete project documentation, including reports and user guides.
CO6: Present and defend the completed project before an evaluation panel.

6TH SEMESTER (OPTION: B) SUBJECTS

This course provides a comprehensive understanding of information security principles and cyber law, covering security threats, risk management, security policies, data protection, and the legal and ethical framework governing cyberspace, enabling students to safeguard information systems and understand cyber regulations.

Course Outcome:

CO1: Understand the fundamental concepts and importance of information security.
CO2: Identify information security threats, vulnerabilities, and risk management practices.
CO3: Apply security policies and controls to protect organizational information assets.
CO4: Understand the fundamentals of cyber law and Information Technology Act provisions.
CO5: Analyze cybercrimes, digital evidence, and legal remedies available under cyber law.
CO6: Apply ethical and legal principles while handling information and digital resources.

This course introduces the fundamentals of the Internet of Things, covering IoT architecture, sensors and actuators, communication protocols, IoT platforms, and application domains, enabling students to understand the design and functioning of connected smart devices and systems.

Course Outcome:

CO1: Understand the fundamental concepts, architecture, and applications of IoT.
CO2: Explain the working of sensors, actuators, and IoT hardware components.
CO3: Understand IoT communication protocols and networking technologies.
CO4: Explore IoT platforms and cloud integration for data management.
CO5: Understand data handling and analytics techniques used in IoT systems.
CO6: Identify security challenges and best practices in IoT deployments.

This practical course provides hands-on experience in building IoT applications, covering sensor and actuator interfacing, microcontroller programming, communication protocols, and cloud connectivity, enabling students to design and implement simple IoT-based projects.

Course Outcome:

CO1: Interface sensors and actuators with microcontroller/IoT development boards.
CO2: Write and upload programs to control IoT hardware components.
CO3: Implement communication between IoT devices using standard protocols.
CO4: Connect IoT devices to cloud platforms for data transmission and monitoring.
CO5: Collect and visualize sensor data using IoT dashboards.
CO6: Design and demonstrate a simple end-to-end IoT application.

This course introduces the fundamentals of Big Data, covering the characteristics of big data, distributed storage and processing frameworks, the Hadoop ecosystem, and data analytics techniques, enabling students to understand how large-scale data is stored, processed, and analyzed.

Course Outcome:

CO1: Understand the characteristics, sources, and challenges of Big Data.
CO2: Explain the architecture and components of the Hadoop ecosystem.
CO3: Understand distributed storage concepts using the Hadoop Distributed File System.
CO4: Apply the MapReduce programming model for distributed data processing.
CO5: Explore Big Data processing tools and frameworks for analytics.
CO6: Understand the applications of Big Data across various domains.

This practical course provides hands-on experience in Big Data tools and frameworks, covering Hadoop installation and configuration, HDFS operations, MapReduce programming, and basic data processing tasks, enabling students to gain practical exposure to handling large-scale datasets.

Course Outcome:

CO1: Set up and configure a basic Hadoop environment.
CO2: Perform file and directory operations using HDFS commands.
CO3: Write and execute simple MapReduce programs for data processing.
CO4: Import and process datasets using Big Data tools.
CO5: Perform basic data analysis tasks on large datasets.
CO6: Demonstrate the working of a simple Big Data processing pipeline.

This practical course provides hands-on experience with version control systems, covering repository creation, branching, merging, conflict resolution, and collaborative workflows using tools such as Git and GitHub, enabling students to manage source code effectively in team-based software development.

Course Outcome:

CO1: Understand the concept and importance of version control systems.
CO2: Create and manage repositories using Git.
CO3: Perform branching, merging, and conflict resolution in a Git repository.
CO4: Collaborate on projects using remote repositories and platforms such as GitHub.
CO5: Apply best practices for commit history and version tracking.
CO6: Manage a collaborative software project using a version control workflow.

This course introduces the fundamental concepts and practices of DevOps, covering continuous integration and continuous deployment, version control, containerization, infrastructure automation, and monitoring, enabling students to understand the tools and processes used to streamline software development and operations.

Course Outcome:

CO1: Understand the fundamental concepts, principles, and benefits of DevOps.
CO2: Apply version control practices to support collaborative software development.
CO3: Understand continuous integration and continuous deployment (CI/CD) pipelines.
CO4: Understand containerization concepts and their role in application deployment.
CO5: Apply infrastructure automation concepts to manage IT resources.
CO6: Understand monitoring and logging practices used in DevOps environments.

This practical course provides hands-on experience with DevOps tools and practices, covering version control, CI/CD pipeline setup, containerization, and basic infrastructure automation, enabling students to implement essential DevOps workflows.

Course Outcome:

CO1: Use version control tools to manage source code collaboratively.
CO2: Set up a basic continuous integration pipeline for a software project.
CO3: Configure a continuous deployment workflow for an application.
CO4: Create and run containerized applications using containerization tools.
CO5: Apply basic infrastructure automation scripts to configure environments.
CO6: Monitor application deployment using basic DevOps monitoring tools.

This course introduces the fundamentals of wireless communication technologies, covering wireless network architecture, transmission techniques, mobile communication standards, wireless networking protocols, and emerging wireless technologies, enabling students to understand the design and functioning of wireless communication systems.

Course Outcome:

CO1: Understand the fundamental concepts and principles of wireless communication.
CO2: Explain wireless network architecture and transmission techniques.
CO3: Understand the evolution and standards of mobile communication technologies.
CO4: Explain wireless networking protocols used in local and wide area networks.
CO5: Understand the fundamentals of emerging wireless technologies such as 5G and IoT connectivity.
CO6: Identify security challenges and solutions in wireless communication systems.

This practical course provides hands-on experience in configuring and analyzing wireless networks, covering wireless device setup, network configuration, signal analysis, and basic wireless security implementation, enabling students to apply wireless technology concepts in practical scenarios.

Course Outcome:

CO1: Configure basic wireless network devices and access points.
CO2: Analyze wireless signal strength and coverage in a given environment.
CO3: Configure wireless network settings for connectivity and performance.
CO4: Implement basic wireless security configurations.
CO5: Use tools to monitor and troubleshoot wireless network issues.
CO6: Demonstrate the setup of a simple wireless communication scenario.

This course focuses on the complete execution of a capstone project, covering final implementation, integration, testing, deployment, and comprehensive documentation, enabling students to demonstrate the end-to-end application of their academic learning through a fully realized project.

Course Outcome:

CO1: Finalize the design and scope of the capstone project.
CO2: Complete the implementation and integration of all project components.
CO3: Conduct comprehensive testing and validation of the project.
CO4: Deploy the completed project in a real or simulated environment.
CO5: Prepare complete project documentation, including reports and manuals.
CO6: Present and defend the completed project before an evaluation panel.

Admissions Open 2026-27

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Bachelor of Computer Application (Lateral Entry)

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Merit Based Scholarship Scheme

Course Curriculum

3RD SEMESTER SUBJECTS

Python Programming

Python Programming Lab

Data Structure

Data Structure Lab

Software Engineering

Emerging AI Tools

Entrepreneurship Mindset-III

MERN Stack Development

MERN Stack Development Lab

Basic of Data Analytics

Basic of Data Analytics Lab

Multimedia and Animation Production

Multimedia and Animation Production Lab

4TH SEMESTER SUBJECTS

Artificial Intelligence and Soft Computing

Artificial Intelligence and Soft Computing Lab

Computer Networks

Computer Networks Lab

Database Management System

Database Management System Lab

Linux Administration

Linux Administration Lab

Java Programming

Java Programming Lab

Data Mining and warehouse

Data Mining and Warehouse Lab

Analytical Skills I

Environmental Science

Entrepreneurship Mindset -IV

5TH SEMESTER SUBJECTS

Cloud Computing

Cloud Computing Lab

Network Security and Cryptography

Network Security and Cryptography Lab

Technical Writing

Summer Training Evaluation

Capstone Project -I

Mobile Application Development

Mobile Application Development Lab

UI/UX Design

UI/UX Design Lab

Search Engine Optimization

Search Engine Optimization lab

Entrepreneurship Mindset- V

6TH SEMESTER (OPTION: A) SUBJECTS

Admissions
Open 2026-27

Industry-oriented
learning

Modern campus
facilities

Academic excellence &
mentorship

Global opportunities &
placements