Search and navigate to colleges and courses
Apply
Scholarships & exams
Fees
₹12,00,000
Placement
92.5%
Avg Package
₹7,50,000
Highest Package
₹18,00,000
Fees
₹12,00,000
Placement
92.5%
Avg Package
₹7,50,000
Highest Package
₹18,00,000
Seats
600
Students
1,800
Seats
600
Students
1,800
| Semester | Course Code | Course Title | Credit Structure (L-T-P-C) | Prerequisites |
|---|---|---|---|---|
| I | CS101 | Introduction to Programming | 3-0-0-3 | - |
| I | CS102 | Mathematics for Computer Science | 4-0-0-4 | - |
| I | CS103 | Computer Organization and Architecture | 3-0-0-3 | - |
| I | CS104 | English for Academic Purposes | 2-0-0-2 | - |
| I | CS105 | Physics for Computer Science | 3-0-0-3 | - |
| I | CS106 | Introduction to Algorithms | 3-0-0-3 | - |
| II | CS201 | Data Structures and Algorithms | 3-0-0-3 | CS101 |
| II | CS202 | Discrete Mathematics | 4-0-0-4 | CS102 |
| II | CS203 | Database Management Systems | 3-0-0-3 | CS106 |
| II | CS204 | Operating Systems | 3-0-0-3 | CS103 |
| II | CS205 | Electrical and Electronics Engineering | 3-0-0-3 | - |
| II | CS206 | Object-Oriented Programming | 3-0-0-3 | CS101 |
| III | CS301 | Computer Networks | 3-0-0-3 | CS204 |
| III | CS302 | Software Engineering | 3-0-0-3 | CS206 |
| III | CS303 | Compiler Design | 3-0-0-3 | CS201 |
| III | CS304 | Design and Analysis of Algorithms | 3-0-0-3 | CS201 |
| III | CS305 | Human Computer Interaction | 3-0-0-3 | - |
| III | CS306 | Mathematical Foundations of Computer Science | 4-0-0-4 | CS202 |
| IV | CS401 | Artificial Intelligence | 3-0-0-3 | CS304 |
| IV | CS402 | Cryptography and Network Security | 3-0-0-3 | CS301 |
| IV | CS403 | Web Technologies | 3-0-0-3 | CS206 |
| IV | CS404 | Data Mining and Warehousing | 3-0-0-3 | CS302 |
| IV | CS405 | Embedded Systems | 3-0-0-3 | CS205 |
| IV | CS406 | Mobile Computing | 3-0-0-3 | CS301 |
| V | CS501 | Machine Learning | 3-0-0-3 | CS401 |
| V | CS502 | Big Data Analytics | 3-0-0-3 | CS404 |
| V | CS503 | Neural Networks and Deep Learning | 3-0-0-3 | CS501 |
| V | CS504 | Cloud Computing | 3-0-0-3 | CS301 |
| V | CS505 | Computer Vision and Image Processing | 3-0-0-3 | CS401 |
| V | CS506 | Game Development | 3-0-0-3 | CS206 |
| VI | CS601 | Advanced Data Structures | 3-0-0-3 | CS201 |
| VI | CS602 | Quantitative Finance | 3-0-0-3 | CS404 |
| VI | CS603 | Internet of Things (IoT) | 3-0-0-3 | CS405 |
| VI | CS604 | Virtual Reality and Augmented Reality | 3-0-0-3 | CS206 |
| VI | CS605 | Information Retrieval | 3-0-0-3 | CS304 |
| VI | CS606 | Research Methodology | 2-0-0-2 | - |
| VII | CS701 | Capstone Project - I | 4-0-0-4 | - |
| VIII | CS801 | Capstone Project - II | 6-0-0-6 | CS701 |
Advanced Departmental Elective Courses include:
This course delves into supervised and unsupervised learning algorithms, including regression, classification, clustering, and neural networks. Students learn to implement machine learning models using Python libraries such as scikit-learn and TensorFlow.
Students explore data processing frameworks like Hadoop and Spark, covering topics from data ingestion to visualization. The course emphasizes real-world applications in business intelligence and scientific computing.
Advanced neural network architectures including convolutional, recurrent, and transformers are studied with practical implementations using PyTorch and Keras. Students gain experience in building deep learning models for computer vision and NLP tasks.
This course covers cloud service models (IaaS, PaaS, SaaS), virtualization, containerization technologies like Docker, and deployment strategies on platforms such as AWS, Azure, and GCP. Students also learn about security considerations in cloud environments.
Students study image filtering, edge detection, feature extraction, object recognition techniques, and deep learning applications in computer vision. Practical labs involve using OpenCV and TensorFlow for real-time video analysis and object tracking.
This course introduces game design principles, scripting with Unity, and asset creation using Blender. Students develop interactive 2D and 3D games, gaining skills in animation, physics simulation, and user interface design.
Topics include advanced tree structures, graphs, heaps, hash tables, and algorithmic complexity analysis. Emphasis is placed on solving complex computational problems using optimized data structures.
This course explores mathematical models used in financial markets, including derivatives pricing, portfolio optimization, and risk management. Students use Python for quantitative analysis and backtesting strategies.
Students study IoT protocols, sensor integration, edge computing, and smart city applications. Practical components involve building IoT devices using Arduino and Raspberry Pi with cloud connectivity.
This course covers VR/AR development environments, spatial computing, user experience design for immersive experiences, and content creation tools like Unity and Unreal Engine. Projects include interactive 3D environments and mobile AR applications.
The department believes that project-based learning is crucial for developing practical skills and deep understanding of computer science concepts. Projects are integrated throughout the curriculum to reinforce classroom learning and encourage innovation.
Mini-projects begin in the second semester, where students work on small-scale applications or algorithms, gradually progressing to more complex tasks by the end of their academic journey. These projects are evaluated based on design quality, functionality, documentation, and presentation skills.
The final-year capstone project is a significant milestone, requiring students to select a topic relevant to current industry trends, collaborate with faculty mentors, and present their work at an internal symposium and potentially at national conferences.
Faculty members guide students through the entire process of project selection, research methodology, implementation, testing, and final presentation. The evaluation criteria include technical proficiency, creativity, teamwork, and adherence to deadlines.
