Curriculum Overview
The Computer Applications program at Itm Sls Baroda University Vadodara is structured to provide a comprehensive educational experience over eight semesters. The curriculum balances theoretical knowledge with practical application, ensuring students are well-prepared for professional roles in the technology industry.
| Semester | Course Code | Course Title | Credit (L-T-P-C) | Prerequisites |
|---|---|---|---|---|
| I | CS101 | Introduction to Programming | 3-0-0-3 | - |
| I | CS102 | Mathematics for Computing | 4-0-0-4 | - |
| I | CS103 | Digital Logic Design | 3-0-0-3 | - |
| I | CS104 | English for Technical Communication | 2-0-0-2 | - |
| I | CS105 | Introduction to Computer Science | 3-0-0-3 | - |
| I | CS106 | Physics for Computing | 3-0-0-3 | - |
| I | CS107 | Chemistry for Engineers | 3-0-0-3 | - |
| I | CS108 | Workshop in Computer Applications | 0-0-2-1 | - |
| II | CS201 | Data Structures and Algorithms | 4-0-0-4 | CS101 |
| II | CS202 | Object-Oriented Programming | 3-0-0-3 | CS101 |
| II | CS203 | Database Management Systems | 3-0-0-3 | CS101 |
| II | CS204 | Operating Systems | 3-0-0-3 | CS101 |
| II | CS205 | Discrete Mathematics | 3-0-0-3 | CS102 |
| II | CS206 | Computer Organization | 3-0-0-3 | CS103 |
| II | CS207 | Lab: Programming Lab | 0-0-2-1 | - |
| III | CS301 | Computer Networks | 3-0-0-3 | CS204 |
| III | CS302 | Compiler Design | 3-0-0-3 | CS201 |
| III | CS303 | Software Engineering | 3-0-0-3 | CS202 |
| III | CS304 | Artificial Intelligence | 3-0-0-3 | CS201 |
| III | CS305 | Human Computer Interaction | 3-0-0-3 | CS202 |
| III | CS306 | Statistics for Computing | 3-0-0-3 | CS102 |
| III | CS307 | Lab: Software Engineering Lab | 0-0-2-1 | - |
| IV | CS401 | Machine Learning | 3-0-0-3 | CS304 |
| IV | CS402 | Cryptography and Network Security | 3-0-0-3 | CS301 |
| IV | CS403 | Data Mining | 3-0-0-3 | CS306 |
| IV | CS404 | Cloud Computing | 3-0-0-3 | CS301 |
| IV | CS405 | Mobile Application Development | 3-0-0-3 | CS202 |
| IV | CS406 | Web Technologies | 3-0-0-3 | CS202 |
| IV | CS407 | Lab: Machine Learning Lab | 0-0-2-1 | - |
| V | CS501 | Advanced Database Systems | 3-0-0-3 | CS303 |
| V | CS502 | Distributed Systems | 3-0-0-3 | CS301 |
| V | CS503 | Big Data Analytics | 3-0-0-3 | CS403 |
| V | CS504 | Computer Vision | 3-0-0-3 | CS401 |
| V | CS505 | Internet of Things (IoT) | 3-0-0-3 | CS301 |
| V | CS506 | Game Development | 3-0-0-3 | CS202 |
| V | CS507 | Lab: IoT Lab | 0-0-2-1 | - |
| VI | CS601 | Reinforcement Learning | 3-0-0-3 | CS401 |
| VI | CS602 | Neural Networks | 3-0-0-3 | CS401 |
| VI | CS603 | Blockchain Technology | 3-0-0-3 | CS202 |
| VI | CS604 | Network Security | 3-0-0-3 | CS402 |
| VI | CS605 | Mobile Security | 3-0-0-3 | CS405 |
| VI | CS606 | Web Application Security | 3-0-0-3 | CS406 |
| VI | CS607 | Lab: Blockchain Lab | 0-0-2-1 | - |
| VII | CS701 | Advanced Topics in AI | 3-0-0-3 | CS401 |
| VII | CS702 | Research Methodology | 3-0-0-3 | - |
| VII | CS703 | Capstone Project | 0-0-4-4 | - |
| VIII | CS801 | Internship | 0-0-0-6 | - |
| VIII | CS802 | Final Year Thesis | 0-0-4-4 | - |
Detailed Course Descriptions
The department offers a variety of advanced departmental elective courses that allow students to tailor their education according to their interests and career goals.
- Machine Learning: This course delves into supervised and unsupervised learning techniques, neural networks, deep learning architectures, reinforcement learning, and practical applications in various domains. Students gain hands-on experience with libraries like TensorFlow, Keras, and Scikit-learn.
- Cryptography and Network Security: Students explore symmetric and asymmetric encryption methods, digital signatures, hash functions, secure protocols, and network security vulnerabilities. Practical sessions include penetration testing using tools like Wireshark and Metasploit.
- Data Mining: Focuses on extracting knowledge from large datasets through clustering, classification, association rule mining, and anomaly detection algorithms. Tools like Weka and Python-based libraries are extensively used.
- Cloud Computing: Covers cloud service models (IaaS, PaaS, SaaS), virtualization technologies, containerization using Docker, orchestration with Kubernetes, and cloud architecture design principles. Hands-on labs include deploying applications on AWS and Azure platforms.
- Mobile Application Development: Students learn to develop cross-platform apps using Flutter and React Native frameworks, integrating with REST APIs, handling local storage, and implementing secure authentication mechanisms.
- Web Technologies: Explores modern web development practices including responsive design, JavaScript frameworks (React, Angular), Node.js backend development, and database integration with MongoDB and PostgreSQL.
- Human Computer Interaction: Studies cognitive psychology, usability testing, interaction design principles, prototyping tools, and user experience evaluation methods. Students create interactive prototypes using Figma and Adobe XD.
- Internet of Things (IoT): Introduces sensor networks, embedded systems programming, wireless communication protocols, edge computing, and smart city applications. Labs involve building IoT projects using Raspberry Pi and Arduino microcontrollers.
- Game Development: Covers game design principles, graphics rendering engines, physics simulation, scripting languages (C#), and mobile game development using Unity engine. Students build complete games from concept to release.
- Blockchain Technology: Explores blockchain architecture, smart contracts, consensus algorithms, decentralized applications (dApps), and cryptocurrency systems. Practical sessions include building Ethereum-based dApps with Solidity and Truffle frameworks.
Project-Based Learning Framework
The department emphasizes project-based learning as a core component of the curriculum. Students engage in mandatory mini-projects during their second and third years, followed by a comprehensive final-year thesis or capstone project.
Mini-projects are designed to reinforce classroom concepts through practical implementation. Each group consists of 3-4 students who select projects based on their interests and faculty guidance. Projects may be industry-sponsored, research-oriented, or community-focused. Evaluation criteria include technical proficiency, creativity, teamwork, documentation quality, and presentation effectiveness.
The final-year thesis/capstone project spans two semesters and involves significant independent research. Students work closely with faculty mentors to define research questions, design experiments, gather data, analyze results, and present findings at departmental symposiums. This process develops critical thinking, problem-solving, and academic writing skills essential for post-graduate studies or industry roles.