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Fees
₹7,50,000
Placement
92.0%
Avg Package
₹5,50,000
Highest Package
₹9,00,000
Fees
₹7,50,000
Placement
92.0%
Avg Package
₹5,50,000
Highest Package
₹9,00,000
Seats
100
Students
300
Seats
100
Students
300
| Semester | Course Code | Course Title | Credit Structure (L-T-P-C) | Pre-requisites |
|---|---|---|---|---|
| 1 | CS101 | Mathematics I | 3-0-0-3 | - |
| 1 | CS102 | Physics for Computer Science | 3-0-0-3 | - |
| 1 | CS103 | Introduction to Programming (C/C++) | 3-0-0-3 | - |
| 1 | CS104 | Digital Logic Design | 3-0-0-3 | - |
| 1 | CS105 | English for Technical Communication | 2-0-0-2 | - |
| 1 | CS106 | Computer Workshop | 0-0-3-1 | - |
| 2 | CS201 | Mathematics II | 3-0-0-3 | CS101 |
| 2 | CS202 | Electrical & Electronics Fundamentals | 3-0-0-3 | - |
| 2 | CS203 | Data Structures and Algorithms | 3-0-0-3 | CS103 |
| 2 | CS204 | Object-Oriented Programming (Java) | 3-0-0-3 | CS103 |
| 2 | CS205 | Computer Organization and Architecture | 3-0-0-3 | CS104 |
| 2 | CS206 | Lab (Data Structures & Algorithms) | 0-0-3-1 | - |
| 3 | CS301 | Probability and Statistics | 3-0-0-3 | CS201 |
| 3 | CS302 | Database Management Systems | 3-0-0-3 | CS203 |
| 3 | CS303 | Operating Systems | 3-0-0-3 | CS205 |
| 3 | CS304 | Computer Networks | 3-0-0-3 | CS205 |
| 3 | CS305 | Software Engineering | 3-0-0-3 | CS204 |
| 3 | CS306 | Lab (Database Management Systems) | 0-0-3-1 | - |
| 4 | CS401 | Microprocessor and Embedded Systems | 3-0-0-3 | CS205 |
| 4 | CS402 | Design and Analysis of Algorithms | 3-0-0-3 | CS301 |
| 4 | CS403 | Compiler Design | 3-0-0-3 | CS303 |
| 4 | CS404 | Artificial Intelligence and Machine Learning | 3-0-0-3 | CS301 |
| 4 | CS405 | Human Computer Interaction | 3-0-0-3 | CS305 |
| 4 | CS406 | Lab (Compiler Design) | 0-0-3-1 | - |
| 5 | CS501 | Cryptography and Network Security | 3-0-0-3 | CS404 |
| 5 | CS502 | Data Mining and Warehousing | 3-0-0-3 | CS302 |
| 5 | CS503 | Cloud Computing | 3-0-0-3 | CS404 |
| 5 | CS504 | Software Architecture and Design Patterns | 3-0-0-3 | CS305 |
| 5 | CS505 | Web Technologies | 3-0-0-3 | CS404 |
| 5 | CS506 | Lab (Cloud Computing) | 0-0-3-1 | - |
| 6 | CS601 | Advanced Machine Learning | 3-0-0-3 | CS404 |
| 6 | CS602 | Mobile Application Development | 3-0-0-3 | CS505 |
| 6 | CS603 | DevOps and CI/CD | 3-0-0-3 | CS405 |
| 6 | CS604 | Quantitative Finance | 3-0-0-3 | CS301 |
| 6 | CS605 | Internet of Things (IoT) | 3-0-0-3 | CS404 |
| 6 | CS606 | Lab (Mobile Application Development) | 0-0-3-1 | - |
| 7 | CS701 | Research Methodology | 3-0-0-3 | CS601 |
| 7 | CS702 | Project Management | 3-0-0-3 | - |
| 7 | CS703 | Special Topics in Computer Science | 3-0-0-3 | CS601 |
| 7 | CS704 | Capstone Project I | 3-0-0-3 | CS501 |
| 7 | CS705 | Internship (Optional) | 0-0-0-6 | - |
| 8 | CS801 | Capstone Project II | 3-0-0-3 | CS704 |
| 8 | CS802 | Advanced Research in Computer Science | 3-0-0-3 | CS701 |
| 8 | CS803 | Career Counseling and Resume Building | 2-0-0-2 | - |
| 8 | CS804 | Final Interview Preparation | 2-0-0-2 | - |
Departmental electives offer students the opportunity to specialize further and explore niche areas within Computer Science. These courses are designed to align with current industry trends and technological advancements.
This course delves into advanced topics in machine learning including deep learning architectures, reinforcement learning, and natural language processing. Students will implement models using TensorFlow and PyTorch frameworks.
Focused on building cross-platform mobile applications, this course covers both iOS and Android development environments. Students learn UI/UX design principles and integrate backend services using Firebase.
This elective explores modern DevOps practices including containerization with Docker, orchestration with Kubernetes, and automation pipelines using Jenkins and GitLab CI.
Designed for students interested in financial technology, this course covers quantitative modeling, risk management systems, and algorithmic trading strategies using Python and R.
This course introduces students to IoT architecture, sensor networks, edge computing, and smart city applications. Practical components include building prototype IoT devices using Arduino and Raspberry Pi.
The department emphasizes project-based learning as a core component of the curriculum. This approach fosters hands-on experience, critical thinking, and innovation among students.
Throughout the program, students undertake mini-projects that align with their interests and academic progress. These projects typically span 3-4 months and involve collaboration with faculty members or industry mentors.
The final-year project is a comprehensive endeavor that integrates all learned concepts and showcases the student's ability to solve complex problems. Students work closely with a faculty advisor throughout the process, culminating in a presentation and documentation of their findings.
Students select projects based on interest areas, faculty availability, and project relevance to industry needs. The department provides a list of proposed projects from faculty members and encourages student-initiated ideas.
