Comprehensive Course Listing Across 8 Semesters
| Semester | Course Code | Course Title | Credit Structure (L-T-P-C) | Prerequisites |
|---|---|---|---|---|
| 1 | CS101 | Introduction to Programming | 3-0-0-3 | - |
| 1 | CS102 | Mathematics for Computing | 4-0-0-4 | - |
| 1 | CS103 | Physics of Information Systems | 3-0-0-3 | - |
| 1 | CS104 | Computer Organization and Architecture | 3-0-0-3 | - |
| 1 | CS105 | Lab: Introduction to Programming | 0-0-3-0 | - |
| 2 | CS201 | Data Structures and Algorithms | 3-0-0-3 | CS101 |
| 2 | CS202 | Database Management Systems | 3-0-0-3 | CS101 |
| 2 | CS203 | Object-Oriented Programming | 3-0-0-3 | CS101 |
| 2 | CS204 | Digital Logic Design | 3-0-0-3 | CS103 |
| 2 | CS205 | Lab: Data Structures and Algorithms | 0-0-3-0 | CS101 |
| 3 | CS301 | Operating Systems | 3-0-0-3 | CS201 |
| 3 | CS302 | Computer Networks | 3-0-0-3 | CS201 |
| 3 | CS303 | Software Engineering | 3-0-0-3 | CS201 |
| 3 | CS304 | Probability and Statistics for Computing | 3-0-0-3 | CS201 |
| 3 | CS305 | Lab: Operating Systems | 0-0-3-0 | CS201 |
| 4 | CS401 | Artificial Intelligence and Machine Learning | 3-0-0-3 | CS201, CS304 |
| 4 | CS402 | Cybersecurity Fundamentals | 3-0-0-3 | CS201 |
| 4 | CS403 | Data Mining and Warehousing | 3-0-0-3 | CS201, CS304 |
| 4 | CS404 | Human-Computer Interaction | 3-0-0-3 | CS201 |
| 4 | CS405 | Lab: AI and ML Concepts | 0-0-3-0 | CS201, CS304 |
| 5 | CS501 | Advanced Computer Architecture | 3-0-0-3 | CS204 |
| 5 | CS502 | Cloud Computing and Distributed Systems | 3-0-0-3 | CS302 |
| 5 | CS503 | Mobile Application Development | 3-0-0-3 | CS203 |
| 5 | CS504 | Blockchain and Cryptocurrency | 3-0-0-3 | CS201 |
| 5 | CS505 | Lab: Cloud and Distributed Systems | 0-0-3-0 | CS302 |
| 6 | CS601 | Embedded Systems and IoT | 3-0-0-3 | CS204 |
| 6 | CS602 | Game Development | 3-0-0-3 | CS201 |
| 6 | CS603 | Computational Biology | 3-0-0-3 | CS201, CS304 |
| 6 | CS604 | Research Methodology and Ethics | 3-0-0-3 | - |
| 6 | CS605 | Lab: Embedded Systems | 0-0-3-0 | CS204 |
| 7 | CS701 | Capstone Project I | 3-0-0-3 | CS401, CS502 |
| 7 | CS702 | Advanced Topics in AI/ML | 3-0-0-3 | CS401 |
| 7 | CS703 | Internship Preparation and Industry Exposure | 2-0-0-2 | - |
| 8 | CS801 | Capstone Project II | 3-0-0-3 | CS701 |
| 8 | CS802 | Thesis Writing and Presentation Skills | 3-0-0-3 | CS604 |
| 8 | CS803 | Final Year Project Defense | 0-0-0-3 | CS701, CS801 |
Detailed Overview of Departmental Electives
Departmental electives offer students the opportunity to explore specialized areas within computer applications. These courses are designed to complement core curriculum and provide depth in specific domains based on individual interests and career goals.
Advanced Machine Learning Concepts
This course delves into advanced topics in machine learning including reinforcement learning, deep neural networks, generative models, and transfer learning. Students will learn to implement complex algorithms using frameworks like TensorFlow and PyTorch, and understand how these techniques are applied in real-world scenarios such as autonomous vehicles and recommendation systems.
Secure Software Development
This elective focuses on secure coding practices, vulnerability analysis, and risk management in software development. Students will study common security flaws like buffer overflows, injection attacks, and cross-site scripting, and learn how to prevent them through secure design principles and defensive programming techniques.
Big Data Technologies
This course explores the tools and technologies used for processing large datasets, including Hadoop, Spark, Kafka, and NoSQL databases. Students will gain hands-on experience in building scalable data pipelines and performing analytics on distributed systems.
Human-Computer Interaction Design
This elective emphasizes user-centered design principles and usability evaluation methods. Students will learn to conduct user research, prototype interfaces, and assess interaction quality using both qualitative and quantitative approaches.
Distributed Systems
This course covers the architecture and implementation of distributed systems, including consensus algorithms, fault tolerance, and scalability considerations. Students will study cloud computing models, microservices architectures, and real-time communication protocols.
Quantum Computing Fundamentals
This course introduces quantum mechanics and its applications in computing. Students will explore qubit manipulation, quantum algorithms, error correction techniques, and the potential impact of quantum computers on cryptography and optimization problems.
Mobile App Security
This elective addresses security challenges specific to mobile platforms. Students will learn about mobile malware, secure coding practices for iOS and Android, and protection mechanisms against common threats like man-in-the-middle attacks and data leakage.
Computer Vision and Image Processing
This course explores the theory and practice of image recognition, object detection, and scene understanding. Students will study convolutional neural networks, feature extraction methods, and applications in robotics, surveillance, and medical imaging.
Blockchain Applications
This elective examines how blockchain technology can be used beyond cryptocurrency, covering smart contracts, decentralized finance (DeFi), supply chain tracking, and digital identity management. Students will develop practical skills in creating blockchain-based applications using platforms like Ethereum and Hyperledger.
Data Visualization Techniques
This course focuses on transforming complex data into meaningful visual representations. Students will learn to use tools like D3.js, Tableau, and Python libraries to create interactive dashboards, maps, and charts that effectively communicate insights to stakeholders.
Project-Based Learning Philosophy
The department's philosophy on project-based learning is centered on experiential education and real-world problem-solving. Projects are designed to mirror industry standards and challenges, providing students with opportunities to apply theoretical knowledge in practical contexts.
Mini-Projects Structure
Mini-projects are assigned at the end of each semester starting from the second year. These projects typically involve small teams working on specific aspects of a larger domain or challenge. Students are encouraged to propose their own project ideas, subject to faculty approval.
Final-Year Thesis/Capstone Project
The capstone project is a significant component of the program, requiring students to conduct independent research or develop a substantial software solution. Projects must demonstrate originality, technical depth, and relevance to current industry trends.
Evaluation Criteria
Projects are evaluated based on multiple criteria including innovation, technical execution, documentation quality, presentation skills, and collaboration effectiveness. Faculty mentors guide students throughout the process, ensuring that they meet academic standards while pursuing their interests.
Project Selection Process
Students select projects based on faculty guidance, industry partnerships, personal interest, and career goals. The department maintains a database of potential project topics derived from ongoing research initiatives, industry collaborations, and alumni feedback.