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Fees
₹15,00,000
Placement
92.5%
Avg Package
₹6,50,000
Highest Package
₹12,00,000
Fees
₹15,00,000
Placement
92.5%
Avg Package
₹6,50,000
Highest Package
₹12,00,000
Seats
200
Students
300
Seats
200
Students
300
| Semester | Course Code | Course Title | Credit (L-T-P-C) | Prerequisite |
|---|---|---|---|---|
| 1 | CS101 | Engineering Mathematics I | 3-1-0-4 | - |
| 1 | CS102 | Introduction to Programming | 3-0-0-3 | - |
| 1 | CS103 | Physics for Engineers | 3-1-0-4 | - |
| 1 | CS104 | Chemistry for Engineers | 3-1-0-4 | - |
| 1 | CS105 | English Communication Skills | 2-0-0-2 | - |
| 1 | CS106 | Engineering Graphics and Design | 2-0-0-2 | - |
| 1 | CS107 | Computer Programming Lab | 0-0-3-1 | - |
| 2 | CS201 | Engineering Mathematics II | 3-1-0-4 | CS101 |
| 2 | CS202 | Data Structures and Algorithms | 3-1-0-4 | CS102 |
| 2 | CS203 | Digital Logic and Computer Organization | 3-1-0-4 | - |
| 2 | CS204 | Object-Oriented Programming | 3-1-0-4 | CS102 |
| 2 | CS205 | Electronic Devices and Circuits | 3-1-0-4 | - |
| 2 | CS206 | Data Structures Lab | 0-0-3-1 | CS202 |
| 2 | CS207 | Object-Oriented Programming Lab | 0-0-3-1 | CS204 |
| 3 | CS301 | Database Management Systems | 3-1-0-4 | CS202 |
| 3 | CS302 | Operating Systems | 3-1-0-4 | CS204 |
| 3 | CS303 | Computer Networks | 3-1-0-4 | CS203 |
| 3 | CS304 | Software Engineering | 3-1-0-4 | CS202 |
| 3 | CS305 | Probability and Statistics | 3-1-0-4 | CS101 |
| 3 | CS306 | Database Systems Lab | 0-0-3-1 | CS301 |
| 3 | CS307 | Operating Systems Lab | 0-0-3-1 | CS302 |
| 4 | CS401 | Compiler Design | 3-1-0-4 | CS301 |
| 4 | CS402 | Artificial Intelligence | 3-1-0-4 | CS302 |
| 4 | CS403 | Machine Learning | 3-1-0-4 | CS305 |
| 4 | CS404 | Cybersecurity Fundamentals | 3-1-0-4 | CS303 |
| 4 | CS405 | Human Computer Interaction | 3-1-0-4 | CS202 |
| 4 | CS406 | AI and ML Lab | 0-0-3-1 | CS402 |
| 5 | CS501 | Advanced Algorithms | 3-1-0-4 | CS202 |
| 5 | CS502 | Distributed Systems | 3-1-0-4 | CS303 |
| 5 | CS503 | Big Data Analytics | 3-1-0-4 | CS301 |
| 5 | CS504 | Internet of Things | 3-1-0-4 | CS203 |
| 5 | CS505 | Software Testing and Quality Assurance | 3-1-0-4 | CS304 |
| 5 | CS506 | IoT Lab | 0-0-3-1 | CS504 |
| 6 | CS601 | Cloud Computing | 3-1-0-4 | CS303 |
| 6 | CS602 | Computer Vision | 3-1-0-4 | CS402 |
| 6 | CS603 | Natural Language Processing | 3-1-0-4 | CS402 |
| 6 | CS604 | Network Security | 3-1-0-4 | CS303 |
| 6 | CS605 | Mobile Application Development | 3-1-0-4 | CS204 |
| 6 | CS606 | Web Technologies Lab | 0-0-3-1 | CS304 |
| 7 | CS701 | Research Methodology | 2-0-0-2 | - |
| 7 | CS702 | Capstone Project I | 3-0-0-3 | - |
| 7 | CS703 | Thesis Writing and Presentation | 2-0-0-2 | - |
| 8 | CS801 | Capstone Project II | 4-0-0-4 | CS702 |
| 8 | CS802 | Internship | 3-0-0-3 | - |
| 8 | CS803 | Elective Courses | 4-0-0-4 | - |
Course: Artificial Intelligence and Machine Learning
Learning Objectives: This course introduces students to the fundamentals of AI and ML, including supervised and unsupervised learning techniques, neural networks, deep learning architectures, and reinforcement learning. Students will gain hands-on experience with frameworks like TensorFlow and PyTorch.
Course: Cybersecurity Fundamentals
Learning Objectives: This course covers essential concepts in cybersecurity, including network security, cryptography, ethical hacking, and risk assessment. Students will learn how to protect systems from threats and implement secure design principles.
Course: Software Engineering
Learning Objectives: This course provides a comprehensive overview of software engineering principles, including requirements analysis, system design, testing strategies, and project management. Students will work on group projects to apply these concepts in real-world scenarios.
Course: Data Science and Big Data Analytics
Learning Objectives: Students will learn how to collect, process, and analyze large datasets using tools like Python, R, SQL, and Spark. The course covers statistical modeling, data visualization, and predictive analytics techniques.
Course: Internet of Things (IoT)
Learning Objectives: This course explores the architecture and implementation of IoT systems, including sensor networks, embedded programming, and cloud integration. Students will design and develop IoT applications for smart environments.
Course: Human-Computer Interaction
Learning Objectives: The course focuses on designing user interfaces that are intuitive, accessible, and effective. Students will learn about usability testing, interaction design, and cognitive psychology principles applied to UI development.
Course: Game Development
Learning Objectives: This course introduces students to game design and development using modern engines like Unity and Unreal. Topics include 2D/3D graphics programming, animation, sound design, and game physics.
Course: Computer Networks
Learning Objectives: Students will study the architecture and protocols of computer networks, including TCP/IP, routing algorithms, network security, and wireless communication. The course includes practical labs on network simulation and troubleshooting.
Course: Mobile Application Development
Learning Objectives: This course covers mobile app development for both iOS and Android platforms. Students will learn about UI/UX design, native programming languages, and cross-platform frameworks like React Native and Flutter.
Course: Robotics and Automation
Learning Objectives: The course explores the principles of robotics, including control systems, sensor integration, and automation technologies. Students will build robotic systems and program them to perform specific tasks.
The department emphasizes a project-based learning approach that encourages students to apply theoretical knowledge to practical problems. Projects are designed to simulate real-world scenarios and provide students with opportunities to collaborate, innovate, and lead.
Mini-projects begin in the second year and culminate in a final-year thesis or capstone project. These projects are assigned based on student interests and faculty expertise, ensuring personalized mentorship and guidance.
The evaluation criteria for these projects include technical depth, innovation, presentation quality, and peer feedback. Students are encouraged to present their work at conferences and competitions to gain recognition and networking opportunities.
