Comprehensive Course Structure
The Bachelor of Computer Science program is structured over 8 semesters with a blend of core courses, departmental electives, science electives, and laboratory components. This comprehensive structure ensures students gain both breadth and depth in their understanding.
| Semester | Course Code | Course Title | Credit Structure (L-T-P-C) | Prerequisites |
|---|---|---|---|---|
| 1 | CSE101 | Introduction to Programming | 3-0-0-3 | - |
| 1 | CSE102 | Mathematics for Computer Science | 3-0-0-3 | - |
| 1 | CSE103 | Physics for Engineering | 3-0-0-3 | - |
| 1 | CSE104 | Chemistry for Engineering | 3-0-0-3 | - |
| 1 | CSE105 | Communication Skills | 2-0-0-2 | - |
| 1 | CSE106 | Programming Lab | 0-0-3-1 | - |
| 2 | CSE201 | Data Structures and Algorithms | 3-0-0-3 | CSE101 |
| 2 | CSE202 | Discrete Mathematics | 3-0-0-3 | - |
| 2 | CSE203 | Digital Electronics | 3-0-0-3 | - |
| 2 | CSE204 | Object Oriented Programming | 3-0-0-3 | CSE101 |
| 2 | CSE205 | Physics Lab | 0-0-3-1 | - |
| 3 | CSE301 | Database Management Systems | 3-0-0-3 | CSE201 |
| 3 | CSE302 | Operating Systems | 3-0-0-3 | CSE204 |
| 3 | CSE303 | Computer Networks | 3-0-0-3 | CSE201 |
| 3 | CSE304 | Software Engineering | 3-0-0-3 | CSE204 |
| 3 | CSE305 | Mathematics for Computer Science II | 3-0-0-3 | CSE102 |
| 3 | CSE306 | Systems Lab | 0-0-3-1 | CSE201 |
| 4 | CSE401 | Machine Learning | 3-0-0-3 | CSE301 |
| 4 | CSE402 | Cryptography and Network Security | 3-0-0-3 | CSE303 |
| 4 | CSE403 | Data Mining and Analytics | 3-0-0-3 | CSE301 |
| 4 | CSE404 | Web Technologies | 3-0-0-3 | CSE204 |
| 4 | CSE405 | Human Computer Interaction | 3-0-0-3 | - |
| 4 | CSE406 | Project Lab I | 0-0-3-1 | CSE301, CSE302 |
| 5 | CSE501 | Deep Learning | 3-0-0-3 | CSE401 |
| 5 | CSE502 | Distributed Systems | 3-0-0-3 | CSE302 |
| 5 | CSE503 | Mobile Application Development | 3-0-0-3 | CSE204 |
| 5 | CSE504 | Cloud Computing | 3-0-0-3 | CSE301 |
| 5 | CSE505 | Computer Vision | 3-0-0-3 | CSE401 |
| 5 | CSE506 | Project Lab II | 0-0-3-1 | CSE401, CSE402 |
| 6 | CSE601 | Blockchain Technologies | 3-0-0-3 | - |
| 6 | CSE602 | Internet of Things | 3-0-0-3 | - |
| 6 | CSE603 | Software Architecture and Design Patterns | 3-0-0-3 | CSE304 |
| 6 | CSE604 | Computer Graphics | 3-0-0-3 | - |
| 6 | CSE605 | Game Development | 3-0-0-3 | - |
| 6 | CSE606 | Internship Preparation | 0-0-0-2 | - |
| 7 | CSE701 | Advanced Algorithms | 3-0-0-3 | CSE201 |
| 7 | CSE702 | Research Methodology | 3-0-0-3 | - |
| 7 | CSE703 | Special Topics in Computer Science | 3-0-0-3 | - |
| 7 | CSE704 | Capstone Project I | 0-0-6-3 | - |
| 7 | CSE705 | Professional Ethics | 2-0-0-2 | - |
| 8 | CSE801 | Capstone Project II | 0-0-6-3 | CSE704 |
| 8 | CSE802 | Thesis Writing and Presentation | 2-0-0-2 | - |
| 8 | CSE803 | Entrepreneurship and Innovation | 2-0-0-2 | - |
| 8 | CSE804 | Final Project Defense | 0-0-0-3 | CSE801 |
Detailed Departmental Elective Courses
The department offers a wide array of advanced electives designed to cater to specific interests and career goals:
- Advanced Machine Learning: This course explores neural network architectures, reinforcement learning, natural language processing, and computer vision applications. Students learn to build scalable ML models using frameworks like TensorFlow and PyTorch.
- Network Security and Cryptography: A comprehensive exploration of modern cryptographic algorithms, secure communication protocols, firewall configurations, and penetration testing techniques. Practical labs involve setting up secure networks and analyzing vulnerabilities.
- Big Data Analytics: Students gain hands-on experience with Hadoop, Spark, and other big data tools to process and analyze large datasets. The course includes real-world case studies from finance, healthcare, and e-commerce sectors.
- Software Architecture and Design Patterns: Focuses on designing robust software systems using industry-standard patterns such as MVC, Singleton, Factory, Observer, and others. Students learn architectural principles through practical implementation.
- Computer Graphics and Visualization: Covers 3D modeling, rendering techniques, animation, and virtual reality development. Students work with industry-standard tools like Blender, Unity, and Unreal Engine.
- Cloud Computing Technologies: Examines cloud infrastructure, deployment models, microservices architecture, and DevOps practices. Labs include configuring AWS, Azure, and GCP environments.
- Embedded Systems Design: Teaches the design and implementation of embedded systems using ARM processors, RTOS, and IoT platforms. Students develop real-time applications for sensors and actuators.
- Distributed Systems: Explores concepts such as consensus algorithms, distributed databases, and fault tolerance in large-scale systems. Students implement distributed solutions using tools like Kafka, Docker, and Kubernetes.
- Game Development: A practical course covering game engine architecture, scripting, level design, and user interface development. Projects include building 2D/3D games using Unity or Unreal Engine.
- Blockchain and Smart Contracts: Introduces blockchain fundamentals, consensus mechanisms, smart contract development using Solidity, and decentralized applications (dApps). Students explore Ethereum, Hyperledger Fabric, and other platforms.
Project-Based Learning Philosophy
The department's philosophy on project-based learning emphasizes the integration of theory with real-world application. From early semesters, students are encouraged to work on mini-projects that reinforce core concepts learned in class. These projects often simulate industry problems and allow students to apply their knowledge in practical contexts.
Mini-projects are structured across multiple semesters, with increasing complexity and scope:
- Year 1: Basic programming assignments, simple algorithm implementations, and small-scale software prototypes.
- Year 2: Data structures and algorithms projects, database design tasks, and basic system simulations.
- Year 3: Network security assessments, machine learning model development, and web application builds.
- Year 4: Capstone projects involving industry collaboration, research initiatives, or entrepreneurial ventures.
Each project is evaluated based on several criteria:
- Technical correctness and implementation quality
- Innovation and problem-solving approach
- Team collaboration and communication skills
- Presentation and documentation standards
- Adherence to deadlines and milestones
The final-year thesis/capstone project is a significant component of the program. Students are assigned faculty mentors based on their area of interest and chosen specialization. Projects typically span two semesters and involve extensive research, prototyping, and documentation.
Faculty selection is based on expertise in relevant domains and availability of resources. Students can propose their own ideas or choose from suggested projects aligned with current industry trends and research directions. The project timeline includes regular check-ins, milestone reviews, and final presentations to faculty panels and industry experts.