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Fees
N/A
Placement
92.0%
Avg Package
₹5,20,000
Highest Package
₹9,50,000
Fees
N/A
Placement
92.0%
Avg Package
₹5,20,000
Highest Package
₹9,50,000
Seats
150
Students
300
Seats
150
Students
300
| Semester | Course Code | Course Title | Credit Structure (L-T-P-C) | Prerequisites |
|---|---|---|---|---|
| 1 | CS101 | Engineering Mathematics I | 3-0-0-3 | - |
| 1 | CS102 | Physics for Engineers | 3-0-0-3 | - |
| 1 | CS103 | Introduction to Programming | 2-0-2-2 | - |
| 1 | CS104 | Computer Organization and Architecture | 3-0-0-3 | - |
| 1 | CS105 | English for Engineers | 2-0-0-2 | - |
| 1 | CS106 | Lab: Introduction to Programming | 0-0-3-1 | - |
| 2 | CS201 | Engineering Mathematics II | 3-0-0-3 | CS101 |
| 2 | CS202 | Data Structures and Algorithms | 3-0-0-3 | CS103 |
| 2 | CS203 | Object-Oriented Programming | 3-0-0-3 | CS103 |
| 2 | CS204 | Digital Logic Design | 3-0-0-3 | - |
| 2 | CS205 | Electrical Circuits and Networks | 3-0-0-3 | - |
| 2 | CS206 | Lab: Data Structures and Algorithms | 0-0-3-1 | CS202 |
| 3 | CS301 | Database Management Systems | 3-0-0-3 | CS202 |
| 3 | CS302 | Software Engineering | 3-0-0-3 | CS203 |
| 3 | CS303 | Computer Networks | 3-0-0-3 | CS204 |
| 3 | CS304 | Operating Systems | 3-0-0-3 | CS203 |
| 3 | CS305 | Probability and Statistics | 3-0-0-3 | CS101 |
| 3 | CS306 | Lab: Database Management Systems | 0-0-3-1 | CS301 |
| 4 | CS401 | Design and Analysis of Algorithms | 3-0-0-3 | CS202 |
| 4 | CS402 | Web Technologies | 3-0-0-3 | CS203 |
| 4 | CS403 | Computer Graphics and Multimedia | 3-0-0-3 | CS203 |
| 4 | CS404 | Human Computer Interaction | 3-0-0-3 | - |
| 4 | CS405 | Mobile Computing | 3-0-0-3 | CS203 |
| 4 | CS406 | Lab: Web Technologies | 0-0-3-1 | CS402 |
| 5 | CS501 | Artificial Intelligence | 3-0-0-3 | CS202, CS301 |
| 5 | CS502 | Cybersecurity Fundamentals | 3-0-0-3 | CS204 |
| 5 | CS503 | Data Mining and Warehousing | 3-0-0-3 | CS301 |
| 5 | CS504 | Cloud Computing | 3-0-0-3 | CS204 |
| 5 | CS505 | Software Testing | 3-0-0-3 | CS302 |
| 5 | CS506 | Lab: AI and Machine Learning | 0-0-3-1 | CS501 |
| 6 | CS601 | Advanced Web Development | 3-0-0-3 | CS402 |
| 6 | CS602 | DevOps and CI/CD | 3-0-0-3 | CS203 |
| 6 | CS603 | Internet of Things (IoT) | 3-0-0-3 | CS204 |
| 6 | CS604 | Mobile App Development | 3-0-0-3 | CS405 |
| 6 | CS605 | Game Development | 3-0-0-3 | - |
| 6 | CS606 | Lab: Mobile App Development | 0-0-3-1 | CS604 |
| 7 | CS701 | Research Methodology | 2-0-0-2 | - |
| 7 | CS702 | Capstone Project - I | 3-0-0-3 | CS501, CS601 |
| 7 | CS703 | Internship Preparation | 2-0-0-2 | - |
| 7 | CS704 | Special Topics in Computer Applications | 3-0-0-3 | - |
| 8 | CS801 | Capstone Project - II | 6-0-0-6 | CS702 |
| 8 | CS802 | Professional Practices | 2-0-0-2 | - |
| 8 | CS803 | Elective I: AI & ML | 3-0-0-3 | CS501 |
| 8 | CS804 | Elective II: Cybersecurity | 3-0-0-3 | CS502 |
| 8 | CS805 | Elective III: Data Science | 3-0-0-3 | CS301 |
| 8 | CS806 | Lab: Specialized Electives | 0-0-3-1 | - |
Artificial Intelligence and Machine Learning: This course introduces students to fundamental concepts in AI, including search algorithms, knowledge representation, reasoning, planning, and machine learning techniques. Students learn how to build intelligent systems using neural networks, decision trees, clustering, classification, and regression models. The course emphasizes practical implementation through Python-based labs and projects.
Cybersecurity Fundamentals: This elective covers the principles of network security, cryptographic protocols, secure coding practices, risk management, and incident response strategies. Students gain hands-on experience with firewalls, intrusion detection systems, penetration testing tools, and compliance frameworks like ISO 27001 and NIST.
Data Mining and Warehousing: Students explore techniques for extracting patterns from large datasets, including association rule mining, clustering, classification, and prediction. The course includes practical sessions on SQL, Python libraries like Pandas and Scikit-Learn, and data visualization tools such as Tableau.
Cloud Computing: This course delves into cloud service models (IaaS, PaaS, SaaS), deployment architectures, virtualization technologies, and major platforms like AWS, Azure, and GCP. Practical labs involve deploying applications on these platforms and managing resources efficiently.
Advanced Web Development: Building upon basic web technologies, this course explores modern frameworks like React, Angular, Node.js, and RESTful APIs. Students learn to develop scalable web applications with user authentication, database integration, and performance optimization techniques.
DevOps and CI/CD: This elective focuses on automating software delivery processes through continuous integration and deployment practices. Topics include version control (Git), containerization (Docker), orchestration (Kubernetes), monitoring (Prometheus), and infrastructure as code (Terraform).
Internet of Things (IoT): Students study sensor networks, embedded systems programming, communication protocols (WiFi, Bluetooth, Zigbee), and edge computing. Practical labs involve building IoT devices using Raspberry Pi, Arduino, and microcontrollers.
Mobile App Development: This course covers both native and cross-platform mobile app development using technologies like Flutter, React Native, Swift, Kotlin, and Android Studio. Students learn to design user interfaces, integrate APIs, manage data persistence, and publish apps on app stores.
Game Development: Using Unity 3D engine, students learn game architecture, scripting, animation, sound design, UI/UX principles, and multiplayer networking. Projects include building interactive games with physics engines, AI behaviors, and immersive environments.
Human-Computer Interaction (HCI): This elective explores how users interact with computer systems and how to design interfaces that are intuitive, efficient, and accessible. Topics include usability testing, user research, prototyping, accessibility standards (WCAG), and cognitive load theory.
Our department strongly believes in project-based learning as a core component of the educational experience. The structure encourages students to engage with real-world challenges and develop practical solutions using their academic knowledge.
The mandatory mini-projects span two semesters, starting from the third year. Each project team consists of 4-6 students, guided by faculty mentors. Projects are evaluated based on technical merit, creativity, presentation quality, and peer feedback. Students must submit progress reports, deliverables, and final presentations.
The final-year thesis/capstone project is an individual or group endeavor that spans the entire eighth semester. It requires students to identify a relevant problem, propose a solution, implement it, and document the process in a comprehensive report. Faculty mentors guide teams throughout the research and development phases, ensuring alignment with industry standards.
Project selection involves multiple rounds of proposal submission, faculty review, and stakeholder consultation. Students can choose from proposed projects by faculty members or submit their own ideas for approval. This approach fosters innovation, encourages collaboration, and ensures relevance to current technological trends.
