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Fees
₹12,00,000
Placement
92.0%
Avg Package
₹4,50,000
Highest Package
₹8,00,000
Fees
₹12,00,000
Placement
92.0%
Avg Package
₹4,50,000
Highest Package
₹8,00,000
Seats
600
Students
1,200
Seats
600
Students
1,200
The Computer Applications curriculum at M V N University Palwal is designed to provide students with a solid foundation in core computer science concepts while offering flexibility through specialized electives. The program spans eight semesters, each containing a carefully selected mix of theoretical and practical courses.
| Semester | Course Code | Course Title | Credit Structure (L-T-P-C) | Prerequisites |
|---|---|---|---|---|
| 1 | CS101 | Introduction to Programming using C/C++ | 3-0-0-3 | - |
| 1 | CS102 | Data Structures and Algorithms | 3-0-0-3 | CS101 |
| 1 | MA101 | Mathematics for Computer Science | 3-0-0-3 | - |
| 1 | PH101 | Physics for Computer Science | 3-0-0-3 | - |
| 1 | EC101 | Electronics for Computer Applications | 3-0-0-3 | - |
| 1 | HS101 | Communication Skills | 2-0-0-2 | - |
| 2 | CS201 | Object-Oriented Programming with Java | 3-0-0-3 | CS101 |
| 2 | CS202 | Database Management Systems | 3-0-0-3 | CS102 |
| 2 | MA201 | Probability and Statistics | 3-0-0-3 | MA101 |
| 2 | PH201 | Modern Physics | 3-0-0-3 | PH101 |
| 2 | EC201 | Digital Logic Design | 3-0-0-3 | EC101 |
| 2 | HS201 | Professional Ethics and Values | 2-0-0-2 | - |
| 3 | CS301 | Operating Systems | 3-0-0-3 | CS201 |
| 3 | CS302 | Computer Networks | 3-0-0-3 | EC201 |
| 3 | CS303 | Software Engineering | 3-0-0-3 | CS201 |
| 3 | MA301 | Linear Algebra and Numerical Methods | 3-0-0-3 | MA201 |
| 3 | PH301 | Quantum Mechanics | 3-0-0-3 | PH201 |
| 3 | CS304 | Computer Organization and Architecture | 3-0-0-3 | EC201 |
| 4 | CS401 | Artificial Intelligence and Machine Learning | 3-0-0-3 | CS303 |
| 4 | CS402 | Cybersecurity and Network Security | 3-0-0-3 | CS302 |
| 4 | CS403 | Data Science and Analytics | 3-0-0-3 | MA301 |
| 4 | CS404 | Software Testing and Quality Assurance | 3-0-0-3 | CS303 |
| 4 | CS405 | Internet of Things (IoT) | 3-0-0-3 | CS302 |
| 4 | CS406 | Human-Computer Interaction | 3-0-0-3 | CS303 |
| 5 | CS501 | Advanced Machine Learning | 3-0-0-3 | CS401 |
| 5 | CS502 | Cloud Computing and DevOps | 3-0-0-3 | CS301 |
| 5 | CS503 | Big Data Analytics | 3-0-0-3 | CS403 |
| 5 | CS504 | Blockchain Technologies | 3-0-0-3 | CS402 |
| 5 | CS505 | Quantum Computing | 3-0-0-3 | PH301 |
| 5 | CS506 | Mobile Application Development | 3-0-0-3 | CS406 |
| 6 | CS601 | Research Methodology and Project Planning | 3-0-0-3 | - |
| 6 | CS602 | Capstone Project I | 0-0-6-3 | CS501 |
| 6 | CS603 | Internship | 0-0-0-3 | - |
| 7 | CS701 | Advanced Capstone Project II | 0-0-6-3 | CS602 |
| 7 | CS702 | Research Project | 0-0-6-3 | - |
| 8 | CS801 | Final Year Project | 0-0-6-3 | CS702 |
Advanced departmental electives provide students with opportunities to specialize in emerging areas of computer science. These courses are designed to challenge students and deepen their understanding of specialized domains.
This course introduces students to the fundamental concepts of artificial intelligence, including search algorithms, knowledge representation, planning, and learning techniques. Students learn to implement machine learning models using libraries like TensorFlow and PyTorch, gaining hands-on experience with neural networks, deep learning architectures, and natural language processing.
This course covers the principles of information security, including cryptography, network security protocols, intrusion detection systems, and risk management. Students gain practical skills in secure coding practices, penetration testing, and vulnerability assessment through laboratory sessions and real-world case studies.
Students learn to extract meaningful insights from large datasets using statistical methods and machine learning algorithms. The course includes hands-on experience with tools like Python, R, SQL, and big data platforms such as Hadoop and Spark. Projects involve analyzing real-world datasets to solve business problems.
This course focuses on ensuring software quality through systematic testing techniques, test planning, automation frameworks, and defect management. Students learn industry-standard tools like Selenium, JUnit, and TestNG, preparing them for roles in QA teams and software development lifecycle processes.
Students explore the integration of sensors, devices, and networks to create smart systems that can collect and exchange data. The course covers embedded system programming, wireless communication protocols, IoT platform development, and real-world applications in smart cities, agriculture, and healthcare.
This course examines how users interact with digital systems and how interfaces can be designed to enhance usability and accessibility. Topics include user experience (UX) design, interaction design principles, prototyping tools, and accessibility standards. Students develop skills in conducting user research and creating inclusive digital experiences.
This course provides an overview of cloud computing models, virtualization technologies, and containerization platforms like Docker and Kubernetes. Students learn to implement continuous integration/continuous deployment (CI/CD) pipelines, manage infrastructure as code using tools like Terraform, and deploy scalable applications on public clouds.
Students gain expertise in processing and analyzing large volumes of data using distributed computing frameworks. The course includes hands-on experience with Hadoop ecosystem components such as MapReduce, Hive, Pig, and Spark. Projects involve building scalable data pipelines and implementing advanced analytics solutions.
This course explores the underlying principles of blockchain technology, including consensus mechanisms, smart contracts, and decentralized applications. Students learn to develop blockchain-based solutions using platforms like Ethereum and Hyperledger Fabric, gaining practical experience in cryptographic protocols and distributed ledger technologies.
Students study the fundamentals of quantum mechanics and how they apply to computing. The course covers quantum algorithms, error correction techniques, and quantum programming languages like Qiskit. Labs involve simulating quantum circuits and exploring potential applications in cryptography and optimization.
This course teaches students to develop cross-platform mobile apps using modern frameworks such as React Native and Flutter. Students learn about UI/UX design, app architecture, integration with APIs, and deployment processes for iOS and Android platforms.
The Computer Applications program emphasizes project-based learning to foster innovation, teamwork, and practical skills. The curriculum includes mandatory mini-projects in the third year, followed by a comprehensive capstone project in the final year.
Mini projects are designed to allow students to apply theoretical knowledge to real-world problems. Each student selects a project topic related to their area of interest under the guidance of a faculty mentor. The projects typically span two months and require students to develop a working prototype or solution.
The capstone project is a significant undertaking that allows students to demonstrate mastery in their chosen domain. Students work on an original research or development project, often collaborating with industry partners or academic institutions. The project involves extensive literature review, experimental design, implementation, testing, and documentation.
Students are encouraged to propose project ideas aligned with their interests and career goals. Faculty mentors guide students through the project lifecycle, ensuring they meet academic standards and industry expectations. Regular progress reviews and milestone evaluations help maintain quality and timely completion.
