Course Structure Overview
The Bachelor of Computer Science program at Dr B R Ambedkar Institute Of Technology Port Blair is structured over eight semesters, with each semester designed to build upon the previous one. The curriculum includes core courses, departmental electives, science electives, and laboratory sessions. The program emphasizes a balance between theoretical knowledge and practical application, ensuring that students are well-prepared for both industry roles and further academic pursuits.
| Semester | Course Code | Course Title | Credit Structure (L-T-P-C) | Prerequisites |
|---|---|---|---|---|
| 1 | CS101 | Introduction to Computer Science | 3-0-0-3 | None |
| 1 | CS102 | Mathematics for Computing | 3-0-0-3 | None |
| 1 | CS103 | Engineering Graphics | 2-0-0-2 | None |
| 1 | CS104 | Programming Fundamentals | 3-0-0-3 | None |
| 1 | CS105 | Physics for Computer Science | 3-0-0-3 | None |
| 1 | CS106 | Chemistry for Computing | 3-0-0-3 | None |
| 2 | CS201 | Data Structures and Algorithms | 3-0-0-3 | CS104 |
| 2 | CS202 | Database Systems | 3-0-0-3 | CS104 |
| 2 | CS203 | Computer Architecture | 3-0-0-3 | CS103 |
| 2 | CS204 | Software Engineering | 3-0-0-3 | CS104 |
| 2 | CS205 | Operating Systems | 3-0-0-3 | CS201 |
| 2 | CS206 | Mathematics for Computing II | 3-0-0-3 | CS102 |
| 3 | CS301 | Artificial Intelligence | 3-0-0-3 | CS201 |
| 3 | CS302 | Cybersecurity | 3-0-0-3 | CS201 |
| 3 | CS303 | Data Science | 3-0-0-3 | CS201 |
| 3 | CS304 | Software Testing | 3-0-0-3 | CS204 |
| 3 | CS305 | Human-Computer Interaction | 3-0-0-3 | CS204 |
| 3 | CS306 | Mobile Application Development | 3-0-0-3 | CS201 |
| 4 | CS401 | Machine Learning | 3-0-0-3 | CS301 |
| 4 | CS402 | Network Security | 3-0-0-3 | CS302 |
| 4 | CS403 | Big Data Analytics | 3-0-0-3 | CS303 |
| 4 | CS404 | Cloud Computing | 3-0-0-3 | CS205 |
| 4 | CS405 | Database Design | 3-0-0-3 | CS202 |
| 4 | CS406 | Software Architecture | 3-0-0-3 | CS204 |
| 5 | CS501 | Advanced Algorithms | 3-0-0-3 | CS201 |
| 5 | CS502 | Computer Vision | 3-0-0-3 | CS301 |
| 5 | CS503 | Deep Learning | 3-0-0-3 | CS401 |
| 5 | CS504 | Blockchain Technology | 3-0-0-3 | CS302 |
| 5 | CS505 | UX Design | 3-0-0-3 | CS305 |
| 5 | CS506 | Mobile App Security | 3-0-0-3 | CS306 |
| 6 | CS601 | Reinforcement Learning | 3-0-0-3 | CS401 |
| 6 | CS602 | Quantum Computing | 3-0-0-3 | CS205 |
| 6 | CS603 | IoT Security | 3-0-0-3 | CS302 |
| 6 | CS604 | Advanced Data Mining | 3-0-0-3 | CS303 |
| 6 | CS605 | DevOps | 3-0-0-3 | CS404 |
| 6 | CS606 | Network Protocols | 3-0-0-3 | CS205 |
| 7 | CS701 | Research Project I | 3-0-0-3 | CS501 |
| 7 | CS702 | Research Project II | 3-0-0-3 | CS701 |
| 7 | CS703 | Capstone Project | 3-0-0-3 | CS702 |
| 7 | CS704 | Thesis | 3-0-0-3 | CS703 |
| 7 | CS705 | Internship | 3-0-0-3 | CS704 |
| 7 | CS706 | Professional Development | 3-0-0-3 | CS705 |
| 8 | CS801 | Capstone Project | 3-0-0-3 | CS703 |
| 8 | CS802 | Thesis | 3-0-0-3 | CS704 |
| 8 | CS803 | Internship | 3-0-0-3 | CS705 |
| 8 | CS804 | Professional Development | 3-0-0-3 | CS706 |
| 8 | CS805 | Final Project | 3-0-0-3 | CS801 |
| 8 | CS806 | Graduation | 3-0-0-3 | CS805 |
Advanced Departmental Electives
Advanced departmental electives provide students with in-depth knowledge and practical skills in specialized areas of computer science. These courses are designed to enhance students' expertise and prepare them for advanced roles in the industry.
Artificial Intelligence
This course explores the principles and techniques of artificial intelligence, including machine learning, natural language processing, and computer vision. Students learn to design and implement AI systems that can solve complex problems and make intelligent decisions.
Cybersecurity
This course focuses on protecting digital assets and infrastructure from cyber threats. Students study network security, cryptography, ethical hacking, and risk management, gaining practical skills through hands-on labs and industry collaborations.
Data Science
This course provides students with the tools and techniques to extract insights from large datasets. Students learn to use statistical methods and machine learning to analyze data and build predictive models.
Software Testing
This course covers various testing methodologies and tools used in software development. Students learn to design and execute tests to ensure software quality and reliability.
Human-Computer Interaction
This course focuses on the design and evaluation of user interfaces and user experiences. Students study human psychology, usability testing, and interaction design to create intuitive and user-friendly systems.
Mobile Application Development
This course provides students with the skills to develop applications for mobile platforms such as iOS and Android. Students learn mobile development frameworks and design principles for mobile interfaces.
Machine Learning
This course explores the principles and techniques of machine learning, including supervised and unsupervised learning, neural networks, and deep learning. Students learn to build and train models to solve real-world problems.
Network Security
This course focuses on securing computer networks and protecting data from unauthorized access. Students study network protocols, firewall configurations, and intrusion detection systems.
Big Data Analytics
This course provides students with the tools and techniques to analyze large datasets. Students learn to use big data frameworks such as Hadoop and Spark to process and analyze data at scale.
Cloud Computing
This course explores the principles and practices of cloud computing. Students learn to design and deploy applications on cloud platforms such as AWS, Azure, and Google Cloud.
Database Design
This course focuses on the design and implementation of database systems. Students study database architecture, query optimization, and data modeling to create efficient and scalable databases.
Software Architecture
This course covers the design and structure of software systems. Students learn to design scalable and maintainable software architectures using design patterns and principles.
Project-Based Learning
The program emphasizes project-based learning to ensure that students gain practical experience and apply their knowledge in real-world scenarios. The project-based learning approach includes mandatory mini-projects and a final-year thesis/capstone project.
Mini-Projects
Mini-projects are designed to give students hands-on experience with specific topics and technologies. These projects are typically completed in groups and are evaluated based on technical execution, creativity, and presentation.
Final-Year Thesis/Capstone Project
The final-year thesis or capstone project is a comprehensive project that integrates all the knowledge and skills acquired throughout the program. Students work on a research or development project under the guidance of a faculty mentor. The project is evaluated based on originality, technical depth, and impact.
Project Selection and Mentorship
Students select their projects based on their interests and career goals. Faculty mentors are assigned based on the project topic and the expertise of the faculty members. The mentorship process ensures that students receive guidance and support throughout the project.