Comprehensive Course Structure Overview
| Semester | Course Code | Course Title | Credit Structure (L-T-P-C) | Prerequisites |
|---|---|---|---|---|
| 1 | CS101 | Introduction to Programming with C | 3-0-2-4 | - |
| 1 | CS102 | Mathematics for Computer Applications I | 3-0-2-4 | - |
| 1 | CS103 | Physics for Computer Science | 3-0-2-4 | - |
| 1 | CS104 | English for Technical Communication | 2-0-2-3 | - |
| 1 | CS105 | Computer Organization and Architecture | 3-0-2-4 | - |
| 1 | CS106 | Programming Lab with C | 0-0-4-2 | - |
| 2 | CS201 | Data Structures and Algorithms | 3-0-2-4 | CS101 |
| 2 | CS202 | Mathematics for Computer Applications II | 3-0-2-4 | CS102 |
| 2 | CS203 | Object Oriented Programming with Java | 3-0-2-4 | CS101 |
| 2 | CS204 | Electronics and Communication Fundamentals | 3-0-2-4 | - |
| 2 | CS205 | Database Management Systems | 3-0-2-4 | - |
| 2 | CS206 | Java Programming Lab | 0-0-4-2 | CS101 |
| 3 | CS301 | Operating Systems | 3-0-2-4 | CS201, CS205 |
| 3 | CS302 | Computer Networks | 3-0-2-4 | CS201 |
| 3 | CS303 | Software Engineering | 3-0-2-4 | CS201, CS205 |
| 3 | CS304 | Discrete Mathematics | 3-0-2-4 | CS102 |
| 3 | CS305 | Web Technologies | 3-0-2-4 | CS203 |
| 3 | CS306 | Web Development Lab | 0-0-4-2 | CS203, CS205 |
| 4 | CS401 | Artificial Intelligence and Machine Learning | 3-0-2-4 | CS201, CS304 |
| 4 | CS402 | Cybersecurity Fundamentals | 3-0-2-4 | CS301, CS302 |
| 4 | CS403 | Cloud Computing | 3-0-2-4 | CS301, CS302 |
| 4 | CS404 | Data Science and Analytics | 3-0-2-4 | CS201, CS202 |
| 4 | CS405 | Mobile Application Development | 3-0-2-4 | CS203, CS305 |
| 4 | CS406 | Mobile App Development Lab | 0-0-4-2 | CS203, CS305 |
| 5 | CS501 | Advanced Algorithms | 3-0-2-4 | CS201 |
| 5 | CS502 | Human Computer Interaction | 3-0-2-4 | CS201, CS303 |
| 5 | CS503 | Internet of Things | 3-0-2-4 | CS301, CS302 |
| 5 | CS504 | Research Methodology | 3-0-2-4 | - |
| 5 | CS505 | Project Management | 3-0-2-4 | - |
| 5 | CS506 | Mini Project I | 0-0-8-4 | - |
| 6 | CS601 | Advanced Machine Learning | 3-0-2-4 | CS401 |
| 6 | CS602 | Network Security | 3-0-2-4 | CS402 |
| 6 | CS603 | DevOps and Containerization | 3-0-2-4 | CS301, CS303 |
| 6 | CS604 | Big Data Analytics | 3-0-2-4 | CS404 |
| 6 | CS605 | Mobile Application Development II | 3-0-2-4 | CS405 |
| 6 | CS606 | Mini Project II | 0-0-8-4 | CS506 |
| 7 | CS701 | Capstone Project I | 0-0-12-8 | CS606 |
| 7 | CS702 | Advanced Topics in Computer Applications | 3-0-2-4 | - |
| 7 | CS703 | Entrepreneurship in Tech | 3-0-2-4 | - |
| 7 | CS704 | Internship Program | 0-0-12-8 | - |
| 8 | CS801 | Capstone Project II | 0-0-12-8 | CS701 |
| 8 | CS802 | Industry Exposure Seminar | 3-0-2-4 | - |
| 8 | CS803 | Research Paper Writing and Presentation | 3-0-2-4 | - |
Detailed Departmental Elective Courses
The department offers a wide range of advanced elective courses designed to deepen students' understanding and provide specialized skills in emerging areas:
- Advanced Machine Learning: This course explores deep learning architectures, neural networks, and reinforcement learning techniques. Students will work on real-world datasets and build predictive models for various domains including healthcare, finance, and autonomous systems.
- Network Security: Focuses on protecting network infrastructures against cyber threats. Topics include firewalls, intrusion detection systems, secure protocols, and cryptography. Practical labs involve setting up virtual networks and conducting penetration testing exercises.
- DevOps and Containerization: Covers continuous integration/continuous deployment (CI/CD) pipelines using tools like Jenkins, Docker, and Kubernetes. Students learn to automate software delivery processes and manage cloud-based applications at scale.
- Big Data Analytics: Introduces students to big data processing frameworks such as Apache Hadoop and Spark. The course emphasizes data warehousing, real-time streaming analytics, and visualization techniques for handling large datasets efficiently.
- Mobile Application Development II: Builds upon the foundational knowledge gained in earlier semesters. Students develop advanced mobile apps with features like offline functionality, location services, and integration with backend APIs using modern frameworks.
- Internet of Things (IoT) Systems: Explores IoT architecture, sensor networks, embedded systems programming, and connectivity protocols. Students design and implement smart home or industrial automation solutions using Raspberry Pi, Arduino, and other platforms.
- Human-Computer Interaction: Emphasizes user-centered design principles and usability studies. Students conduct research on human behavior in digital environments, prototype interfaces, and evaluate user experiences through experiments and surveys.
- Cloud Computing Technologies: Provides an in-depth look at cloud service models (IaaS, PaaS, SaaS), virtualization technologies, and cloud security measures. Practical sessions involve deploying applications on AWS, Azure, and Google Cloud platforms.
- Data Science and Analytics: Combines statistics, programming, and domain expertise to extract insights from complex datasets. Students use Python, R, SQL, and machine learning libraries to perform exploratory data analysis, build predictive models, and communicate findings effectively.
- Artificial Intelligence in Robotics: Integrates AI concepts with robotics engineering. Students design intelligent robots that can perceive environments, make decisions, and interact with humans using sensors, actuators, and control systems.
Project-Based Learning Philosophy
The department's philosophy on project-based learning is centered around experiential education, where students learn by doing. Projects are structured to mirror real-world challenges and provide opportunities for innovation and creativity.
The mandatory mini-projects in the fifth semester allow students to apply theoretical knowledge to practical problems. These projects typically span 8 weeks and involve working in teams of 3-5 members under faculty supervision. Students must document their process, present findings, and receive feedback from both peers and mentors.
The final-year capstone project provides a comprehensive learning experience where students undertake an extended research or development endeavor. This project spans two semesters (7th and 8th) and requires significant independent work, including literature review, problem definition, methodology design, implementation, testing, and documentation.
Students select their projects based on their interests and career goals, often aligning with ongoing faculty research initiatives or industry partnerships. Faculty mentors guide students through each phase of the project, ensuring academic rigor while encouraging innovation and entrepreneurship.