Comprehensive Course Structure
| Semester | Course Code | Course Title | Credit Structure (L-T-P-C) | Prerequisites |
|---|---|---|---|---|
| 1 | CS101 | Programming Fundamentals | 3-0-0-3 | None |
| 1 | CS102 | Mathematics for Computer Applications | 3-0-0-3 | None |
| 1 | CS103 | Computer Organization | 3-0-0-3 | None |
| 1 | CS104 | Engineering Graphics | 2-0-0-2 | None |
| 1 | CS105 | English for Technical Communication | 2-0-0-2 | None |
| 1 | CS106 | Introduction to Computing | 2-0-0-2 | None |
| 2 | CS201 | Data Structures and Algorithms | 3-0-0-3 | CS101 |
| 2 | CS202 | Database Management Systems | 3-0-0-3 | CS101 |
| 2 | CS203 | Object-Oriented Programming | 3-0-0-3 | CS101 |
| 2 | CS204 | Discrete Mathematics | 3-0-0-3 | CS102 |
| 2 | CS205 | Computer Networks | 3-0-0-3 | CS103 |
| 2 | CS206 | Software Engineering | 3-0-0-3 | CS201 |
| 3 | CS301 | Artificial Intelligence | 3-0-0-3 | CS201 |
| 3 | CS302 | Cybersecurity | 3-0-0-3 | CS201 |
| 3 | CS303 | Data Science | 3-0-0-3 | CS201 |
| 3 | CS304 | Web Technologies | 3-0-0-3 | CS201 |
| 3 | CS305 | Mobile Application Development | 3-0-0-3 | CS201 |
| 3 | CS306 | Cloud Computing | 3-0-0-3 | CS201 |
| 4 | CS401 | Advanced Algorithms | 3-0-0-3 | CS201 |
| 4 | CS402 | Machine Learning | 3-0-0-3 | CS301 |
| 4 | CS403 | Human-Computer Interaction | 3-0-0-3 | CS201 |
| 4 | CS404 | Internet of Things | 3-0-0-3 | CS201 |
| 4 | CS405 | Blockchain Technology | 3-0-0-3 | CS201 |
| 4 | CS406 | Capstone Project | 4-0-0-4 | CS201 |
| 5 | CS501 | Research Methodology | 2-0-0-2 | CS406 |
| 5 | CS502 | Special Topics in AI | 3-0-0-3 | CS301 |
| 5 | CS503 | Advanced Cybersecurity | 3-0-0-3 | CS302 |
| 5 | CS504 | Big Data Analytics | 3-0-0-3 | CS303 |
| 5 | CS505 | Game Development | 3-0-0-3 | CS201 |
| 5 | CS506 | DevOps and CI/CD | 3-0-0-3 | CS306 |
| 6 | CS601 | Internship | 6-0-0-6 | CS406 |
| 6 | CS602 | Thesis Research | 6-0-0-6 | CS501 |
| 6 | CS603 | Capstone Project | 4-0-0-4 | CS406 |
| 6 | CS604 | Project Management | 3-0-0-3 | CS201 |
| 6 | CS605 | Professional Ethics | 2-0-0-2 | None |
| 6 | CS606 | Entrepreneurship | 2-0-0-2 | None |
Advanced Departmental Elective Courses
The Computer Applications program offers a range of advanced departmental elective courses designed to deepen students' expertise in specialized areas. These courses are taught by faculty members who are leaders in their respective fields, ensuring that students receive the most current and relevant instruction.
One such course is Artificial Intelligence, which explores advanced topics in neural networks, deep learning, and natural language processing. Students learn to design and implement AI systems that can solve complex problems in domains such as computer vision, robotics, and intelligent agents. The course emphasizes both theoretical understanding and practical application through hands-on projects.
Cybersecurity is another advanced elective that delves into the latest threats and defense mechanisms in the digital landscape. Students study cryptographic protocols, network security, and ethical hacking techniques. The course includes simulations of real-world security incidents, allowing students to apply their knowledge in practical scenarios.
Data Science is a course that focuses on extracting insights from large datasets using statistical methods and machine learning algorithms. Students learn to use tools such as Python, R, and SQL to analyze data and build predictive models. The course emphasizes the importance of data quality and ethical considerations in data science.
Web Technologies covers the development of modern web applications using frameworks such as React, Node.js, and Angular. Students learn to build scalable and secure web applications that can handle large volumes of traffic. The course includes both front-end and back-end development, providing students with a comprehensive understanding of web development.
Mobile Application Development focuses on creating applications for iOS and Android platforms. Students learn to design user interfaces, implement core functionality, and deploy applications to app stores. The course emphasizes the importance of user experience and cross-platform compatibility.
Cloud Computing explores the architecture and implementation of cloud-based systems. Students study virtualization, containerization, and microservices. The course includes hands-on experience with cloud platforms such as AWS, Azure, and Google Cloud.
Advanced Algorithms is a course that focuses on the design and analysis of complex algorithms. Students learn to solve problems using techniques such as dynamic programming, greedy algorithms, and graph algorithms. The course emphasizes the importance of algorithmic complexity and optimization.
Human-Computer Interaction explores the design and evaluation of user interfaces. Students learn to conduct usability testing, design prototypes, and implement user-centered design principles. The course emphasizes the importance of accessibility and inclusive design.
Internet of Things (IoT) covers the development of smart systems that connect physical devices to the internet. Students learn to program microcontrollers, design sensor networks, and implement real-time data processing. The course emphasizes the integration of hardware and software in IoT applications.
Blockchain Technology introduces students to the fundamentals of blockchain and distributed ledger technology. Students learn to develop smart contracts, design decentralized applications, and understand the security implications of blockchain systems. The course includes hands-on experience with blockchain platforms such as Ethereum and Hyperledger.
Project-Based Learning Philosophy
The department's philosophy on project-based learning is rooted in the belief that students learn best when they are actively engaged in solving real-world problems. Projects are designed to integrate knowledge from multiple disciplines and provide students with practical experience in their chosen fields.
Mini-projects are assigned in the second and third years, allowing students to apply foundational concepts in practical settings. These projects are typically completed in groups and are evaluated based on technical execution, innovation, and presentation. Faculty members serve as mentors, providing guidance and feedback throughout the project lifecycle.
The final-year thesis/capstone project is a comprehensive endeavor that requires students to conduct independent research or develop a significant software solution. Students select projects in consultation with faculty mentors, ensuring that their work aligns with their interests and career goals. The project is evaluated based on originality, technical depth, and the ability to communicate findings effectively.
Students are encouraged to collaborate with industry partners on capstone projects, providing them with exposure to real-world challenges and industry best practices. This collaboration not only enhances the quality of the projects but also provides students with networking opportunities and potential career prospects.