B.Sc. (Hons.) Computer Applications

The Bachelor of Science in Computer Applications (BSc CA) is a four -year undergraduate program that focuses on providing students with a strong foundation in computer science and its applications. The program is designed to equip students with the skills and knowledge, both academic knowledge and practical skills required to succeed in the rapidly evolving field of computer science. The program spans eight semesters, covering a wide range of topics from fundamental programming to advanced technologies like Artificial Intelligence and Big Data Analytics.

Graduates of the BSc CA program have excellent career prospects in both industry and academia. With the growing demand for professionals across multiple sectors, students can explore opportunities in:

  • Software Industry: AI Engineer, Machine Learning Engineer, Data Scientist, AI Research Scientist, and Software Developer.
  • Finance & Banking: AI-driven risk assessment, fraud detection, and predictive analytics.
  • Healthcare: Medical image analysis, AI-powered diagnostics, and healthcare automation.
  • Cybersecurity and Networking: Graduates can pursue careers in cybersecurity and networking.
  • IT Consulting and Management: Roles are available in IT consulting and management.
  • Database Administration: Opportunities exist as database administrators.
  • Network Administration: Graduates can work in network administration
  • Government & Defense: Cybersecurity, surveillance, and AI policy.

Discipline Specific Core courses are the mandatory, foundational, and advanced subject-specific credit courses that form the main focus of your chosen Major or Minor area of study, ensuring in-depth competency in that specific discipline.

This course introduces the fundamentals of computer programming using the C language. Students learn problem-solving techniques, algorithms, flowcharts, and structured programming concepts while developing basic coding skills through practical sessions.

This course focuses on object-oriented programming concepts such as classes, objects, inheritance, polymorphism, and encapsulation using C++. It helps students build modular and reusable programs while strengthening programming logic.

This course introduces data organization techniques such as arrays, linked lists, stacks, queues, trees, and graphs using C++. Students learn efficient storage and retrieval of data and apply problem-solving techniques through programming.

This course covers the fundamentals of database systems, including data models, relational databases, SQL, normalization, and database design. It enables students to manage and retrieve data effectively for real-world applications.

This course introduces basic digital electronics concepts such as logic gates, Boolean algebra, combinational circuits, and sequential circuits. Students gain an understanding of digital systems and computer hardware foundations.

This course introduces Java programming concepts including classes, objects, exception handling, inheritance, and GUI-based application development. It helps students create platform-independent applications using Java.

This course focuses on modern web development techniques including front-end and back-end technologies, dynamic web pages, and web application development. Students gain practical skills in designing interactive websites.

This course explains the functions of operating systems including process management, memory management, file systems, and scheduling. It helps students understand how computer resources are managed efficiently.

This course introduces Python programming and essential libraries for data analysis and visualization. Students learn to work with datasets, perform analysis, and generate insights using tools like NumPy and Pandas.

This course covers networking fundamentals, network topologies, communication models, protocols, and data transmission techniques. Students understand how computer networks operate and communicate securely.

This course introduces software development principles, system analysis, design methods, and software life cycle models. It helps students understand how software projects are planned, developed, and maintained.

This course introduces machine learning techniques used to build predictive and intelligent systems. Students learn concepts such as supervised and unsupervised learning with practical implementation.

This course focuses on software design, coding practices, testing, and implementation. Students gain practical exposure to developing applications using standard development methodologies.

This course introduces techniques for discovering patterns and extracting useful information from large datasets. Students learn classification, clustering, and data analysis methods for decision-making.

This course explains testing techniques used to ensure software quality and reliability. Students learn test planning, debugging, and validation methods.

This course introduces research methods, data collection, analysis techniques, and report writing. It prepares students to carry out academic and technical research systematically.

This course focuses on algorithm design techniques, complexity analysis, and optimization methods. Students learn to solve computational problems efficiently.

This course introduces intelligent systems, search strategies, knowledge representation, and AI applications. Students gain understanding of how machines simulate human intelligence.

This course covers IoT architecture, smart devices, sensors, and communication technologies. Students explore connected systems and real-world IoT applications.

This course introduces methods and tools used to process and analyze large-scale data. Students learn data analytics techniques for modern computing environments.

This course familiarizes students with ethical practices in research, publication standards, plagiarism awareness, and intellectual property rights. It promotes responsible academic and professional conduct.

This course introduces neural networks and deep learning models used in advanced artificial intelligence. Students explore practical applications in image recognition, language processing, and predictive systems.

Discipline Specific Elective courses are specialized courses that allow students to dive deeper into their chosen major or minor fields, providing tailored knowledge in specific areas of their discipline.

This course introduces the fundamentals of cloud computing and the technologies used to deliver computing services over the internet. Students learn about cloud architecture, service models such as IaaS, PaaS, and SaaS, virtualization, storage systems, and deployment models. The course also explores cloud platforms and their applications in business and modern computing environments.

This course provides an introduction to Android application development and mobile computing concepts. Students learn the basics of Android Studio, user interface design, activities, layouts, intents, and data handling in Android applications. The course enables learners to build simple mobile applications while understanding the core components of the Android platform.

This course introduces the principles and techniques used for processing and analyzing digital images. Students study image enhancement, filtering, transformation, segmentation, and feature extraction. Practical exposure to image processing tools helps learners understand how images are manipulated and applied in areas such as medical imaging, computer vision, and pattern recognition.

This course provides a foundation in R programming for data analysis and statistical computing. Students learn data structures, operators, functions, visualization techniques, and statistical methods using R. The course develops skills for handling datasets, performing analysis, and creating graphical representations useful in research and decision-making.

This course focuses on the design and functioning of system software and its relationship with computer architecture. It covers assemblers, macro processors, loaders, linkers, and compilers, helping students understand how programs are translated and executed by the system. The course builds strong theoretical knowledge of system-level software and its role in efficient program execution.

This course focuses on the concepts and techniques used to protect computer networks and information systems. Students study network threats, cryptography, firewalls, authentication, access control, and secure communication protocols. The course helps learners understand security risks and methods to ensure confidentiality, integrity, and availability in network environments.

This course introduces the techniques used to process and analyze human language with computers. Students explore text processing, language models, machine learning and deep learning approaches in NLP, and applications such as chatbots, translation, sentiment analysis, and question answering systems. The course also addresses challenges like ambiguity, fairness, and emerging trends in language technologies.

This course introduces the concepts and applications of Generative Artificial Intelligence. Students learn how AI models generate text, images, and other content using machine learning and deep learning techniques. The course explores generative models, prompt engineering, ethical concerns, and real-world applications of Generative AI across various domains.

MDC, AEC, SEC, and VAC are the four core categories of "General Foundation Courses" introduced under the National Education Policy (NEP). They provide foundational knowledge beyond your core major.

Broaden your intellectual foundation by studying academic fields outside your core discipline.
  • Computer Hardware and Assembling
  • Cyber Laws and Online Safety
  • Basic IT Tools
  • Web Designing

Equip you with practical, hands-on training to directly improve your employability.
  • Advanced Excel
  • AI Tools
  • Technical Writing using LATEX

Instill ethics, constitutional values, and cultural awareness for holistic personal development.
  • IT, Environment, and Holistic Living
  • White Hat Hacking
  • Green Computing
  • Information and Cyber Ethics
  • Cyber Forensics and Data Security
  • Cyber Security and Ethical Hacking
  • Health and Wellness