Comprehensive Course Structure
The Bachelor of Science in Information Technology program at Dr B R Ambedkar Institute Of Technology Port Blair is structured over eight semesters, with a carefully balanced mix of core courses, departmental electives, science electives, and laboratory sessions. The program ensures that students build a strong foundation in the first two years before progressing to more specialized and advanced topics in the latter years. The curriculum is designed to be both rigorous and practical, with an emphasis on real-world applications and problem-solving skills.
| Semester | Course Code | Course Title | Credit Structure (L-T-P-C) | Pre-requisites |
|---|---|---|---|---|
| 1 | IT101 | Mathematics for Information Technology | 3-1-0-4 | None |
| 1 | IT102 | Physics for IT | 3-1-0-4 | None |
| 1 | IT103 | Chemistry for IT | 3-1-0-4 | None |
| 1 | IT104 | Introduction to Programming | 3-1-2-6 | None |
| 1 | IT105 | English for IT | 3-1-0-4 | None |
| 1 | IT106 | Computer Fundamentals | 3-1-0-4 | None |
| 2 | IT201 | Data Structures and Algorithms | 3-1-2-6 | IT104 |
| 2 | IT202 | Database Management Systems | 3-1-2-6 | IT104 |
| 2 | IT203 | Computer Organization | 3-1-0-4 | IT106 |
| 2 | IT204 | Operating Systems | 3-1-2-6 | IT203 |
| 2 | IT205 | Web Technologies | 3-1-2-6 | IT104 |
| 2 | IT206 | Object-Oriented Programming | 3-1-2-6 | IT104 |
| 3 | IT301 | Software Engineering | 3-1-2-6 | IT201 |
| 3 | IT302 | Artificial Intelligence | 3-1-2-6 | IT201 |
| 3 | IT303 | Cybersecurity | 3-1-2-6 | IT204 |
| 3 | IT304 | Data Science | 3-1-2-6 | IT201 |
| 3 | IT305 | Internet of Things | 3-1-2-6 | IT204 |
| 3 | IT306 | Cloud Computing | 3-1-2-6 | IT204 |
| 4 | IT401 | Machine Learning | 3-1-2-6 | IT304 |
| 4 | IT402 | Network Security | 3-1-2-6 | IT303 |
| 4 | IT403 | Distributed Systems | 3-1-2-6 | IT204 |
| 4 | IT404 | Human-Computer Interaction | 3-1-2-6 | IT205 |
| 4 | IT405 | Information Systems | 3-1-2-6 | IT301 |
| 4 | IT406 | Mobile Application Development | 3-1-2-6 | IT205 |
| 5 | IT501 | Advanced Data Structures | 3-1-2-6 | IT201 |
| 5 | IT502 | Deep Learning | 3-1-2-6 | IT401 |
| 5 | IT503 | Security Architecture | 3-1-2-6 | IT303 |
| 5 | IT504 | Big Data Analytics | 3-1-2-6 | IT304 |
| 5 | IT505 | Embedded Systems | 3-1-2-6 | IT305 |
| 5 | IT506 | DevOps | 3-1-2-6 | IT201 |
| 6 | IT601 | Computer Vision | 3-1-2-6 | IT401 |
| 6 | IT602 | Blockchain Technology | 3-1-2-6 | IT303 |
| 6 | IT603 | Advanced Networking | 3-1-2-6 | IT204 |
| 6 | IT604 | UX Design | 3-1-2-6 | IT404 |
| 6 | IT605 | Enterprise Architecture | 3-1-2-6 | IT405 |
| 6 | IT606 | Mobile Security | 3-1-2-6 | IT603 |
| 7 | IT701 | Research Methodology | 3-1-0-4 | IT201 |
| 7 | IT702 | Capstone Project | 3-1-0-4 | IT605 |
| 7 | IT703 | Internship | 3-1-0-4 | IT606 |
| 8 | IT801 | Advanced Topics in IT | 3-1-0-4 | IT702 |
| 8 | IT802 | Final Project | 3-1-0-4 | IT702 |
| 8 | IT803 | Industry Exposure | 3-1-0-4 | IT703 |
Advanced Departmental Electives
The department offers a range of advanced departmental electives designed to provide students with specialized knowledge and skills in emerging areas of information technology. These courses are taught by faculty members who are experts in their respective fields and have extensive industry experience.
Machine Learning: This course provides an in-depth understanding of machine learning algorithms and their applications. Students will learn about supervised and unsupervised learning, neural networks, deep learning, and reinforcement learning. The course includes hands-on projects using popular frameworks such as TensorFlow and PyTorch.
Network Security: This course covers the principles and practices of network security. Students will study topics such as cryptography, firewall design, intrusion detection systems, and secure network protocols. The course includes practical labs where students will implement and test security measures.
Distributed Systems: This course explores the design and implementation of distributed systems. Students will study concepts such as distributed algorithms, consensus protocols, and fault tolerance. The course includes projects involving distributed computing frameworks such as Hadoop and Spark.
Human-Computer Interaction: This course focuses on the design and evaluation of user interfaces. Students will learn about user experience design, usability testing, and interaction design principles. The course includes practical sessions where students will prototype and test user interfaces.
Information Systems: This course covers the design and management of information systems in organizations. Students will study topics such as enterprise architecture, information governance, and digital transformation. The course includes case studies of real-world information systems and projects involving system design.
Mobile Application Development: This course provides students with the skills necessary to develop mobile applications for iOS and Android platforms. Students will learn about mobile app design, development frameworks, and deployment strategies. The course includes hands-on projects involving the development of mobile applications.
Deep Learning: This course focuses on the principles and applications of deep learning. Students will study neural network architectures, convolutional neural networks, and recurrent neural networks. The course includes projects involving image recognition, natural language processing, and other deep learning applications.
Big Data Analytics: This course covers the principles and practices of big data analytics. Students will study data mining, statistical modeling, and machine learning techniques for analyzing large datasets. The course includes hands-on projects using big data platforms such as Hadoop and Spark.
Embedded Systems: This course provides an overview of embedded systems and their applications. Students will study microcontrollers, real-time operating systems, and embedded software development. The course includes practical labs involving the development of embedded systems.
DevOps: This course covers the principles and practices of DevOps. Students will study continuous integration, deployment automation, and infrastructure as code. The course includes hands-on projects involving DevOps tools such as Jenkins, Docker, and Kubernetes.
Project-Based Learning Philosophy
The department's philosophy on project-based learning is rooted in the belief that students learn best when they are actively engaged in solving real-world problems. The curriculum is structured to provide students with opportunities to apply their knowledge in practical settings, thereby reinforcing theoretical concepts and developing essential skills such as teamwork, communication, and problem-solving.
The mandatory mini-projects are designed to be completed in the second and third years of the program. These projects are typically small-scale and focus on specific aspects of information technology. Students are encouraged to work in teams and collaborate with faculty members to develop and implement solutions to real-world challenges.
The final-year thesis/capstone project is a comprehensive endeavor that allows students to integrate all the knowledge and skills they have acquired throughout their studies. The project is typically sponsored by industry partners and addresses real business challenges. Students are required to conduct a literature review, design and implement a solution, and present their findings to a panel of faculty members and industry experts.
Students select their projects and faculty mentors based on their interests and career goals. The selection process involves a proposal submission, followed by a review by faculty members. Students are encouraged to propose projects that align with their interests and have potential for real-world impact.