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Scholarships & exams

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+91 88943 57155
Pune, Maharashtra, India

Duration

4 Years

Bachelor Of Technology

Dr B R Ambedkar Institute Of Technology Port Blair
Duration
4 Years
Bachelor Of Technology UG OFFLINE

Duration

4 Years

Bachelor Of Technology

Dr B R Ambedkar Institute Of Technology Port Blair
Duration
Apply

Fees

₹8,00,000

Placement

92.0%

Avg Package

₹7,00,000

Highest Package

₹15,00,000

OverviewAdmissionsCurriculumFeesPlacements
4 Years
Bachelor Of Technology
UG
OFFLINE

Fees

₹8,00,000

Placement

92.0%

Avg Package

₹7,00,000

Highest Package

₹15,00,000

Seats

120

Students

1,200

ApplyCollege

Seats

120

Students

1,200

Curriculum

Comprehensive Course Structure

The Bachelor of Technology program at Dr B R Ambedkar Institute Of Technology Port Blair is meticulously structured to provide students with a well-rounded and industry-relevant education. The program is divided into eight semesters, each with a carefully designed sequence of core courses, departmental electives, science electives, and laboratory sessions. The curriculum is regularly updated to reflect the latest industry trends and technological advancements, ensuring that students are well-prepared for the challenges of the modern engineering landscape.

SemesterCourse CodeCourse TitleCredit Structure (L-T-P-C)Prerequisites
1ENG101Engineering Mathematics I3-1-0-4None
1PHY101Physics for Engineers3-1-0-4None
1CHM101Chemistry for Engineers3-1-0-4None
1ESC101Engineering Drawing & Graphics2-0-2-3None
1CS101Introduction to Programming2-0-2-3None
1ME101Introduction to Engineering2-0-0-2None
1ENG102English for Engineers2-0-0-2None
1PHYS101Physics Lab0-0-3-1PHY101
1CHML101Chemistry Lab0-0-3-1CHM101
2ENG201Engineering Mathematics II3-1-0-4ENG101
2ME201Mechanics of Materials3-1-0-4ME101
2EC201Electrical Circuits3-1-0-4None
2CS201Data Structures & Algorithms3-1-0-4CS101
2PHYS201Thermodynamics3-1-0-4PHY101
2ME202Fluid Mechanics3-1-0-4ME101
2CS202Database Management Systems3-1-0-4CS101
2EC202Electronic Devices & Circuits3-1-0-4EC201
2PHYS202Thermodynamics Lab0-0-3-1PHYS201
2ME203Mechanics of Materials Lab0-0-3-1ME201
3ENG301Engineering Mathematics III3-1-0-4ENG201
3ME301Strength of Materials3-1-0-4ME201
3EC301Signals & Systems3-1-0-4EC201
3CS301Operating Systems3-1-0-4CS201
3PHYS301Electromagnetic Fields3-1-0-4PHYS201
3ME302Machine Design3-1-0-4ME201
3CS302Computer Networks3-1-0-4CS201
3EC302Control Systems3-1-0-4EC301
3PHYS302Electromagnetic Fields Lab0-0-3-1PHYS301
3ME303Machine Design Lab0-0-3-1ME302
4ENG401Engineering Mathematics IV3-1-0-4ENG301
4ME401Heat Transfer3-1-0-4ME201
4EC401Communication Systems3-1-0-4EC301
4CS401Software Engineering3-1-0-4CS301
4PHYS401Quantum Physics3-1-0-4PHYS301
4ME402Manufacturing Processes3-1-0-4ME301
4CS402Artificial Intelligence3-1-0-4CS301
4EC402Embedded Systems3-1-0-4EC301
4PHYS402Quantum Physics Lab0-0-3-1PHYS401
4ME403Manufacturing Lab0-0-3-1ME402
5ENG501Advanced Mathematics3-1-0-4ENG401
5ME501Structural Analysis3-1-0-4ME301
5EC501Microprocessors & Microcontrollers3-1-0-4EC401
5CS501Machine Learning3-1-0-4CS401
5PHYS501Optics & Lasers3-1-0-4PHYS401
5ME502Automotive Engineering3-1-0-4ME401
5CS502Big Data Analytics3-1-0-4CS401
5EC502Optical Communication3-1-0-4EC401
5PHYS502Optics Lab0-0-3-1PHYS501
5ME503Automotive Lab0-0-3-1ME502
6ENG601Probability & Statistics3-1-0-4ENG501
6ME601Advanced Mechanics3-1-0-4ME501
6EC601Antenna & Wave Propagation3-1-0-4EC501
6CS601Deep Learning3-1-0-4CS501
6PHYS601Nuclear Physics3-1-0-4PHYS501
6ME602Robotics & Automation3-1-0-4ME501
6CS602Blockchain Technology3-1-0-4CS501
6EC602Wireless Networks3-1-0-4EC501
6PHYS602Nuclear Physics Lab0-0-3-1PHYS601
6ME603Robotics Lab0-0-3-1ME602
7ENG701Engineering Economics3-1-0-4ENG601
7ME701Finite Element Analysis3-1-0-4ME601
7EC701RF & Microwave Engineering3-1-0-4EC601
7CS701Computer Vision3-1-0-4CS601
7PHYS701Condensed Matter Physics3-1-0-4PHYS601
7ME702Advanced Manufacturing3-1-0-4ME601
7CS702Internet of Things3-1-0-4CS601
7EC702Signal Processing3-1-0-4EC601
7PHYS702Condensed Matter Lab0-0-3-1PHYS701
7ME703Advanced Manufacturing Lab0-0-3-1ME702
8ENG801Project Management3-1-0-4ENG701
8ME801Engineering Design3-1-0-4ME701
8EC801Advanced Communication3-1-0-4EC701
8CS801Cloud Computing3-1-0-4CS701
8PHYS801Advanced Physics3-1-0-4PHYS701
8ME802Capstone Project3-1-0-4ME701
8CS802Capstone Project3-1-0-4CS701
8EC802Capstone Project3-1-0-4EC701
8PHYS802Capstone Project3-1-0-4PHYS701
8ME803Capstone Project Lab0-0-3-1ME802
8CS803Capstone Project Lab0-0-3-1CS802
8EC803Capstone Project Lab0-0-3-1EC802
8PHYS803Capstone Project Lab0-0-3-1PHYS802

Advanced Departmental Elective Courses

The Department of Computer Science offers a range of advanced elective courses that allow students to specialize in cutting-edge technologies. These courses are designed to provide in-depth knowledge and practical skills in emerging fields.

One of the most popular courses is Machine Learning, which covers topics such as supervised and unsupervised learning, neural networks, and deep learning. Students learn to apply these concepts to real-world problems, using tools like TensorFlow and PyTorch. The course includes hands-on projects that simulate industry scenarios, ensuring that students are well-prepared for careers in AI and data science.

Another advanced elective is Data Science and Analytics, which focuses on statistical analysis, data visualization, and predictive modeling. Students gain experience with big data technologies like Hadoop and Spark, and learn to use Python and R for data manipulation and analysis. The course also covers ethical considerations in data usage and privacy.

Software Engineering is a course that emphasizes the development lifecycle, including requirements gathering, design, implementation, testing, and maintenance. Students work on group projects to simulate real-world software development environments, gaining experience in agile methodologies and project management tools.

Artificial Intelligence is a comprehensive course that covers the fundamentals of AI, including search algorithms, knowledge representation, and machine learning. Students explore the ethical implications of AI and work on projects that involve building intelligent systems.

Computer Networks is designed to provide students with a deep understanding of network architecture, protocols, and security. The course includes practical sessions on network simulation and troubleshooting, preparing students for roles in network engineering and cybersecurity.

Big Data Analytics is an elective that focuses on processing and analyzing large datasets. Students learn to use tools like Apache Kafka, Hadoop, and Spark to extract insights from data. The course also covers data mining and machine learning techniques specific to big data environments.

Internet of Things (IoT) is a course that explores the design and implementation of smart systems. Students learn about sensor networks, embedded systems, and cloud integration, with hands-on experience in building IoT applications.

Blockchain Technology is a cutting-edge elective that covers the fundamentals of blockchain, smart contracts, and distributed systems. Students explore the applications of blockchain in various industries, including finance, healthcare, and supply chain management.

Cloud Computing is a course that focuses on cloud architecture, deployment models, and service offerings. Students gain experience with cloud platforms like AWS, Azure, and Google Cloud, learning to design and deploy scalable applications.

Mobile Application Development is an elective that teaches students to build applications for iOS and Android platforms. The course covers user interface design, app functionality, and deployment strategies, with students working on real-world projects.

Security Engineering is a course that focuses on protecting information systems from cyber threats. Students learn about encryption, network security, and risk management, with practical sessions on penetration testing and vulnerability assessment.

Human-Computer Interaction is a course that explores the design and evaluation of user interfaces. Students learn about usability principles, user experience design, and accessibility, with hands-on projects involving prototyping and user testing.

Computer Vision is a course that covers image processing, pattern recognition, and deep learning applications. Students work on projects involving object detection, image segmentation, and facial recognition, using libraries like OpenCV and TensorFlow.

Database Systems is a course that delves into the design and implementation of relational and non-relational databases. Students learn about normalization, indexing, and query optimization, with practical sessions on SQL and NoSQL databases.

Human-Machine Interaction is a course that focuses on the interaction between humans and machines. Students explore cognitive psychology, user experience design, and the development of intelligent systems that can adapt to user needs.

Project-Based Learning Philosophy

The Department of Computer Science at Dr B R Ambedkar Institute Of Technology Port Blair places a strong emphasis on project-based learning, recognizing that hands-on experience is crucial for developing practical skills and deepening understanding of complex concepts. The program's approach to project-based learning is designed to be both structured and flexible, allowing students to explore their interests while meeting academic objectives.

Mini-projects are introduced in the early semesters to help students build foundational skills and gain confidence in applying theoretical concepts. These projects are typically completed in teams and are designed to be manageable yet challenging. For instance, in the second semester, students might work on a simple web application or a basic data structure implementation. These projects are evaluated based on technical correctness, presentation, and teamwork.

As students progress, the complexity of projects increases, with each project building upon the previous one. By the fourth semester, students are expected to work on more sophisticated projects that integrate multiple concepts and technologies. For example, a project might involve designing and implementing a complete software system with a user interface, database integration, and backend services.

The final-year project, also known as the Capstone Project, is a significant component of the program. Students are expected to work independently or in small teams to develop a substantial project that addresses a real-world problem. The project must demonstrate a deep understanding of engineering principles, innovation, and practical application. Students are assigned faculty mentors who provide guidance throughout the project lifecycle.

The evaluation criteria for projects are comprehensive and include technical excellence, innovation, presentation, and documentation. Students are also encouraged to present their projects at departmental symposiums and industry events, where they receive feedback from experts and professionals.

The Department of Computer Science provides a supportive environment for project development, with access to state-of-the-art labs, software tools, and mentorship. Students are encouraged to collaborate with industry partners and research groups, ensuring that their projects are relevant and impactful.

Overall, the project-based learning approach at Dr B R Ambedkar Institute Of Technology Port Blair ensures that students not only acquire theoretical knowledge but also develop the practical skills and confidence needed to succeed in their careers.