Comprehensive Course Listing Across 8 Semesters
| Semester | Course Code | Course Title | Credit Structure (L-T-P-C) | Prerequisites |
|---|---|---|---|---|
| 1 | CS101 | Engineering Mathematics I | 3-1-0-4 | - |
| 1 | CS102 | Programming Fundamentals | 3-1-0-4 | - |
| 1 | CS103 | Introduction to Computer Science | 3-1-0-4 | - |
| 1 | CS104 | Physics for Computing | 3-1-0-4 | - |
| 1 | CS105 | English Communication Skills | 3-1-0-4 | - |
| 1 | CS106 | Computer Lab I | 0-0-2-2 | - |
| 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 | Electronics for Computing | 3-1-0-4 | - |
| 2 | CS206 | Computer Lab II | 0-0-2-2 | CS106 |
| 3 | CS301 | Database Management Systems | 3-1-0-4 | CS202 |
| 3 | CS302 | Operating Systems | 3-1-0-4 | CS203 |
| 3 | CS303 | Software Engineering | 3-1-0-4 | CS204 |
| 3 | CS304 | Theory of Computation | 3-1-0-4 | CS201 |
| 3 | CS305 | Computer Networks | 3-1-0-4 | CS203 |
| 3 | CS306 | Computer Lab III | 0-0-2-2 | CS206 |
| 4 | CS401 | Design and Analysis of Algorithms | 3-1-0-4 | CS301 |
| 4 | CS402 | Artificial Intelligence | 3-1-0-4 | CS301 |
| 4 | CS403 | Cybersecurity Fundamentals | 3-1-0-4 | CS302 |
| 4 | CS404 | Human Computer Interaction | 3-1-0-4 | CS204 |
| 4 | CS405 | Web Technologies | 3-1-0-4 | CS303 |
| 4 | CS406 | Computer Lab IV | 0-0-2-2 | CS306 |
| 5 | CS501 | Machine Learning | 3-1-0-4 | CS401 |
| 5 | CS502 | Data Mining and Big Data Analytics | 3-1-0-4 | CS401 |
| 5 | CS503 | Cloud Computing | 3-1-0-4 | CS401 |
| 5 | CS504 | Advanced Database Systems | 3-1-0-4 | CS301 |
| 5 | CS505 | Embedded Systems | 3-1-0-4 | CS203 |
| 5 | CS506 | Computer Lab V | 0-0-2-2 | CS406 |
| 6 | CS601 | Neural Networks and Deep Learning | 3-1-0-4 | CS501 |
| 6 | CS602 | Blockchain Technology | 3-1-0-4 | CS403 |
| 6 | CS603 | Computer Graphics and Animation | 3-1-0-4 | CS404 |
| 6 | CS604 | Internet of Things (IoT) | 3-1-0-4 | CS505 |
| 6 | CS605 | Security in Modern Computing | 3-1-0-4 | CS403 |
| 6 | CS606 | Computer Lab VI | 0-0-2-2 | CS506 |
| 7 | CS701 | Capstone Project I | 3-1-0-4 | CS601, CS602 |
| 7 | CS702 | Advanced Topics in AI | 3-1-0-4 | CS501 |
| 7 | CS703 | Research Methodology | 3-1-0-4 | - |
| 7 | CS704 | Entrepreneurship in Tech | 3-1-0-4 | - |
| 7 | CS705 | Professional Ethics and Social Responsibility | 3-1-0-4 | - |
| 7 | CS706 | Computer Lab VII | 0-0-2-2 | CS606 |
| 8 | CS801 | Capstone Project II | 3-1-0-4 | CS701 |
| 8 | CS802 | Internship & Industry Exposure | 3-1-0-4 | CS701 |
| 8 | CS803 | Final Year Thesis | 3-1-0-4 | CS701, CS702 |
| 8 | CS804 | Advanced Research in CS | 3-1-0-4 | CS703 |
| 8 | CS805 | Capstone Presentation | 3-1-0-4 | CS801, CS802 |
| 8 | CS806 | Computer Lab VIII | 0-0-2-2 | CS706 |
Detailed Course Descriptions for Advanced Departmental Electives
Machine Learning (CS501): This course explores the mathematical foundations of machine learning algorithms, including supervised and unsupervised learning techniques. Students will learn to implement models using Python libraries like scikit-learn and TensorFlow, gaining hands-on experience in building predictive systems.
Data Mining and Big Data Analytics (CS502): Focused on extracting meaningful patterns from large datasets, this course covers data preprocessing, clustering, classification, association rules, and anomaly detection. Students will use tools like Hadoop, Spark, and MongoDB to analyze real-world data sets.
Cloud Computing (CS503): This course delves into cloud architecture, deployment models, and service types (IaaS, PaaS, SaaS). It includes practical labs on AWS, Azure, and Google Cloud Platform, enabling students to deploy scalable applications in virtual environments.
Advanced Database Systems (CS504): This course covers advanced topics in database design and implementation, including transaction management, indexing strategies, query optimization, and distributed databases. Students will gain expertise in Oracle, PostgreSQL, and MySQL.
Embedded Systems (CS505): Designed for students interested in hardware-software integration, this course introduces microcontrollers, real-time operating systems, sensor networks, and embedded software development using C and ARM architecture.
Neural Networks and Deep Learning (CS601): Students will study artificial neural networks, convolutional networks, recurrent networks, and transformers. Using PyTorch and Keras, they will build models for image recognition, natural language processing, and time-series forecasting.
Blockchain Technology (CS602): This course explores blockchain fundamentals, smart contracts, consensus mechanisms, and decentralized applications. Students will create their own blockchains using Ethereum and Hyperledger Fabric frameworks.
Computer Graphics and Animation (CS603): Covering 3D modeling, rendering techniques, animation principles, and interactive graphics, this course uses tools like Blender, Unity, and Unreal Engine to develop immersive visual experiences.
Internet of Things (IoT) (CS604): This course examines IoT architectures, communication protocols, security issues, and edge computing. Students will build IoT devices using Raspberry Pi, Arduino, and ESP32 microcontrollers.
Security in Modern Computing (CS605): Addressing contemporary cybersecurity challenges, this course covers network defense, ethical hacking, cryptography, and incident response strategies. Students will participate in simulated attacks and learn to secure enterprise systems.
Project-Based Learning Approach
The department strongly advocates for project-based learning as a core component of its curriculum. Projects are assigned at different stages of the program to reinforce theoretical knowledge with practical implementation.
Mini-projects are introduced in the second year, focusing on small-scale problems within specific domains such as web development or data analysis. These projects are evaluated based on functionality, documentation, and presentation quality.
The final-year capstone project is a major undertaking that spans both semesters of the eighth year. Students select a topic aligned with their specialization and work closely with faculty mentors to design, implement, and present an innovative solution. The evaluation criteria include technical depth, creativity, impact, and teamwork.
Faculty members play a pivotal role in guiding students through their projects. They provide mentorship during research phases, offer feedback on progress reports, and facilitate networking with industry professionals. Each student is paired with a faculty advisor who ensures alignment between project goals and academic standards.