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Fees
₹6,50,000
Placement
94.0%
Avg Package
₹6,50,000
Highest Package
₹9,50,000
Fees
₹6,50,000
Placement
94.0%
Avg Package
₹6,50,000
Highest Package
₹9,50,000
Seats
100
Students
300
Seats
100
Students
300
| Semester | Course Code | Course Title | Credits (L-T-P-C) | Prerequisites |
|---|---|---|---|---|
| 1 | CS101 | Introduction to Programming | 3-0-0-3 | - |
| 1 | CS102 | Mathematics for Computer Science | 3-0-0-3 | - |
| 1 | CS103 | Physics for CS Students | 3-0-0-3 | - |
| 1 | CS104 | English Communication Skills | 2-0-0-2 | - |
| 1 | CS105 | Computer Organization & Architecture | 3-0-0-3 | - |
| 1 | CS106 | Lab: Programming Fundamentals | 0-0-3-1 | - |
| 2 | CS201 | Data Structures & Algorithms | 3-0-0-3 | CS101 |
| 2 | CS202 | Database Management Systems | 3-0-0-3 | CS101 |
| 2 | CS203 | Operating Systems | 3-0-0-3 | CS105 |
| 2 | CS204 | Object-Oriented Programming | 3-0-0-3 | CS101 |
| 2 | CS205 | Discrete Mathematics | 3-0-0-3 | - |
| 2 | CS206 | Lab: Data Structures & Algorithms | 0-0-3-1 | CS101 |
| 3 | CS301 | Software Engineering Principles | 3-0-0-3 | CS204 |
| 3 | CS302 | Computer Networks | 3-0-0-3 | CS205 |
| 3 | CS303 | Web Technologies | 3-0-0-3 | CS204 |
| 3 | CS304 | Artificial Intelligence | 3-0-0-3 | CS201 |
| 3 | CS305 | Machine Learning | 3-0-0-3 | CS201 |
| 3 | CS306 | Lab: Software Engineering | 0-0-3-1 | CS204 |
| 4 | CS401 | Cybersecurity Fundamentals | 3-0-0-3 | CS202 |
| 4 | CS402 | Big Data Analytics | 3-0-0-3 | CS201 |
| 4 | CS403 | Distributed Systems | 3-0-0-3 | CS302 |
| 4 | CS404 | Human-Computer Interaction | 3-0-0-3 | CS301 |
| 4 | CS405 | Internet of Things (IoT) | 3-0-0-3 | CS205 |
| 4 | CS406 | Lab: IoT & Distributed Systems | 0-0-3-1 | CS302 |
| 5 | CS501 | Advanced Data Science | 3-0-0-3 | CS305 |
| 5 | CS502 | Deep Learning | 3-0-0-3 | CS305 |
| 5 | CS503 | Blockchain Technologies | 3-0-0-3 | CS201 |
| 5 | CS504 | Game Development | 3-0-0-3 | CS303 |
| 5 | CS505 | Mobile Application Development | 3-0-0-3 | CS303 |
| 5 | CS506 | Lab: Advanced Topics | 0-0-3-1 | CS305 |
| 6 | CS601 | Research Methodology | 2-0-0-2 | - |
| 6 | CS602 | Capstone Project | 3-0-0-3 | CS501 |
| 6 | CS603 | Mini Project | 2-0-0-2 | CS304 |
| 6 | CS604 | Internship | 0-0-0-6 | - |
| 7 | CS701 | Special Topics in CS | 3-0-0-3 | CS501 |
| 7 | CS702 | Advanced Cybersecurity | 3-0-0-3 | CS401 |
| 7 | CS703 | Quantitative Finance | 3-0-0-3 | CS201 |
| 7 | CS704 | Virtual Reality & Augmented Reality | 3-0-0-3 | CS304 |
| 7 | CS705 | Entrepreneurship in Tech | 2-0-0-2 | - |
| 7 | CS706 | Lab: Special Topics | 0-0-3-1 | CS501 |
| 8 | CS801 | Final Year Thesis | 3-0-0-3 | CS602 |
| 8 | CS802 | Industry Project | 3-0-0-3 | CS701 |
| 8 | CS803 | Capstone Presentation | 0-0-0-3 | CS602 |
Each course within the Computer Science program is designed to build upon foundational knowledge while introducing new paradigms and methodologies. For instance, Data Structures & Algorithms (CS201) forms the backbone of any computer science education, equipping students with essential tools for efficient problem-solving in software development. Similarly, Database Management Systems (CS202) introduces students to data storage, retrieval, and optimization techniques crucial in modern applications.
Deep Learning: This course focuses on neural network architectures and their applications in natural language processing, computer vision, and reinforcement learning. Students explore frameworks like TensorFlow and PyTorch through hands-on labs and projects involving image recognition systems.
Human-Computer Interaction: Emphasizing usability design principles, this elective teaches students how to create intuitive interfaces that enhance user experience across various platforms. Topics include cognitive psychology, interaction design patterns, and prototyping tools like Figma and Sketch.
Blockchain Technologies: This course explores decentralized systems, smart contracts, and cryptocurrency mechanisms. Students gain practical experience in developing blockchain applications using Ethereum and Hyperledger Fabric frameworks.
Game Development: Through this elective, students learn game design principles, 3D modeling, animation techniques, and real-time rendering using engines like Unity and Unreal Engine. Projects include building interactive games for mobile and PC platforms.
Mobile Application Development: Designed for students aiming to develop cross-platform mobile apps, this course covers Android and iOS development using Java/Kotlin and Swift respectively. Students build functional applications that integrate with cloud services and APIs.
Quantitative Finance: Combines mathematical modeling with financial analysis to understand trading strategies, derivatives pricing, and portfolio optimization. This elective prepares students for roles in quantitative research or algorithmic trading firms.
Cybersecurity Fundamentals: Introduces students to threat detection, encryption methods, network security protocols, and incident response planning. Labs simulate real-world scenarios including penetration testing and malware analysis.
Big Data Analytics: Focuses on processing large datasets using Hadoop, Spark, and cloud-based analytics platforms. Students learn data cleaning, visualization, and predictive modeling techniques applied in sectors like healthcare, finance, and marketing.
Distributed Systems: Explores the design and implementation of systems that operate across multiple computers, covering topics such as consensus algorithms, load balancing, and fault tolerance. This course prepares students for roles in cloud computing or enterprise IT infrastructure.
Internet of Things (IoT): Covers sensor networks, embedded programming, and real-time data processing. Students work with Arduino, Raspberry Pi, and ESP32 devices to develop smart home systems and industrial monitoring solutions.
Virtual Reality & Augmented Reality: Teaches students how to design immersive experiences using VR/AR tools and platforms. Projects include developing virtual museums, educational simulations, and industrial training modules.
The department strongly believes in project-based learning as a means of fostering innovation, creativity, and practical application of theoretical knowledge. Students are encouraged to work on open-ended problems that mirror real-world challenges, thereby preparing them for professional environments.
Mini-projects are assigned in the third and fifth semesters, focusing on specific technical domains such as web development or algorithmic design. These projects involve small teams of 3-5 students, each contributing distinct roles based on their strengths and interests.
The final-year thesis project, undertaken in the seventh and eighth semesters, allows students to pursue independent research under faculty supervision. Students propose a topic aligned with current industry trends or emerging technologies, conduct literature review, design experiments, and present findings in a formal report and oral defense.
Evaluation criteria for projects include technical depth, innovation, clarity of documentation, teamwork, and presentation skills. Faculty mentors guide students throughout the process, ensuring academic rigor while encouraging creative freedom.
