Comprehensive Course Structure
| Semester | Course Code | Course Title | Credit (L-T-P-C) | Prerequisites |
|---|---|---|---|---|
| 1 | ENG101 | Engineering Graphics | 3-0-0-3 | - |
| 1 | MAT101 | Calculus I | 4-0-0-4 | - |
| 1 | MAT102 | Linear Algebra | 3-0-0-3 | - |
| 1 | PHY101 | Physics I | 4-0-0-4 | - |
| 1 | CHM101 | Chemistry I | 3-0-0-3 | - |
| 1 | BIO101 | Biology I | 3-0-0-3 | - |
| 1 | CSE101 | Introduction to Programming | 3-0-2-4 | - |
| 1 | ENG102 | Basic Electrical Engineering | 3-0-0-3 | - |
| 1 | ENG103 | Engineering Mechanics | 3-0-0-3 | - |
| 1 | ENG104 | Workshop Practice | 0-0-3-1 | - |
| 2 | MAT201 | Calculus II | 4-0-0-4 | MAT101 |
| 2 | MAT202 | Differential Equations | 3-0-0-3 | MAT101 |
| 2 | PHY201 | Physics II | 4-0-0-4 | PHY101 |
| 2 | CHM201 | Chemistry II | 3-0-0-3 | CHM101 |
| 2 | BIO201 | Biology II | 3-0-0-3 | BIO101 |
| 2 | CSE201 | Data Structures and Algorithms | 3-0-2-4 | CSE101 |
| 2 | ENG201 | Circuit Analysis | 3-0-0-3 | ENG102 |
| 2 | ENG202 | Digital Electronics | 3-0-2-4 | ENG102 |
| 2 | ENG203 | Engineering Materials | 3-0-0-3 | - |
| 2 | ENG204 | Basic Thermodynamics | 3-0-0-3 | - |
| 3 | MAT301 | Calculus III | 4-0-0-4 | MAT201 |
| 3 | MAT302 | Probability and Statistics | 3-0-0-3 | MAT201 |
| 3 | CSE301 | Database Management Systems | 3-0-2-4 | CSE201 |
| 3 | CSE302 | Computer Organization and Architecture | 3-0-0-3 | CSE201 |
| 3 | ENG301 | Signal Processing | 3-0-0-3 | ENG201 |
| 3 | ENG302 | Control Systems | 3-0-0-3 | ENG201 |
| 3 | ENG303 | Power Electronics | 3-0-0-3 | ENG201 |
| 3 | ENG304 | Machine Design | 3-0-0-3 | - |
| 3 | ENG305 | Computer Networks | 3-0-2-4 | CSE201 |
| 3 | ENG306 | Electromagnetic Fields and Waves | 3-0-0-3 | PHY201 |
| 4 | MAT401 | Numerical Methods | 3-0-0-3 | MAT201 |
| 4 | CSE401 | Software Engineering | 3-0-2-4 | CSE301 |
| 4 | CSE402 | Artificial Intelligence and Machine Learning | 3-0-2-4 | CSE201 |
| 4 | ENG401 | Advanced Control Systems | 3-0-0-3 | ENG302 |
| 4 | ENG402 | Renewable Energy Systems | 3-0-0-3 | - |
| 4 | ENG403 | Structural Analysis | 3-0-0-3 | - |
| 4 | ENG404 | Foundation Engineering | 3-0-0-3 | - |
| 4 | ENG405 | Biomedical Instrumentation | 3-0-0-3 | - |
| 4 | ENG406 | Robotics and Automation | 3-0-2-4 | - |
| 5 | CSE501 | Advanced Database Systems | 3-0-2-4 | CSE301 |
| 5 | CSE502 | Network Security | 3-0-2-4 | CSE301 |
| 5 | CSE503 | Big Data Analytics | 3-0-2-4 | CSE201 |
| 5 | ENG501 | Advanced Signal Processing | 3-0-0-3 | ENG301 |
| 5 | ENG502 | Power System Analysis | 3-0-0-3 | - |
| 5 | ENG503 | Steel Structures | 3-0-0-3 | - |
| 5 | ENG504 | Concrete Technology | 3-0-0-3 | - |
| 5 | ENG505 | Biomedical Devices | 3-0-0-3 | - |
| 5 | ENG506 | Sustainable Design and Construction | 3-0-0-3 | - |
| 6 | CSE601 | Machine Learning and Deep Learning | 3-0-2-4 | CSE201 |
| 6 | CSE602 | Cybersecurity | 3-0-2-4 | CSE301 |
| 6 | CSE603 | Data Mining | 3-0-2-4 | CSE201 |
| 6 | ENG601 | Advanced Power Electronics | 3-0-0-3 | ENG303 |
| 6 | ENG602 | Earthquake Resistant Design | 3-0-0-3 | - |
| 6 | ENG603 | Advanced Materials | 3-0-0-3 | - |
| 6 | ENG604 | Biomedical Signal Processing | 3-0-0-3 | - |
| 6 | ENG605 | Automation and Robotics | 3-0-2-4 | - |
| 7 | CSE701 | Research Methodology | 3-0-0-3 | - |
| 7 | CSE702 | Capstone Project I | 0-0-6-6 | - |
| 7 | ENG701 | Advanced Structural Analysis | 3-0-0-3 | ENG304 |
| 7 | ENG702 | Advanced Biomedical Engineering | 3-0-0-3 | ENG505 |
| 7 | ENG703 | Sustainable Construction Materials | 3-0-0-3 | - |
| 7 | ENG704 | Advanced Renewable Energy Systems | 3-0-0-3 | ENG402 |
| 7 | ENG705 | Industrial Automation | 3-0-2-4 | - |
| 8 | CSE801 | Capstone Project II | 0-0-6-6 | - |
| 8 | ENG801 | Final Year Thesis | 0-0-6-6 | - |
Detailed Course Descriptions
Advanced Database Systems: This course delves into advanced concepts in database design, implementation, and management. Students will explore topics such as transaction processing, concurrency control, recovery mechanisms, indexing strategies, query optimization, and distributed databases. The course emphasizes practical implementation through hands-on laboratory sessions and project work. Learning outcomes include understanding the architecture of modern database systems, designing scalable database solutions, and implementing advanced data management techniques.
Network Security: This course provides a comprehensive overview of network security principles and practices. Students will study topics such as cryptography, secure protocols, firewall configurations, intrusion detection systems, vulnerability assessment, and risk management. The course combines theoretical knowledge with practical exercises using industry-standard tools and platforms. Learning outcomes include identifying security vulnerabilities, implementing secure network configurations, and developing strategies to protect against cyber threats.
Big Data Analytics: This course explores the fundamentals of big data analytics and its applications in various domains. Students will learn about data collection, processing, storage, and analysis using technologies such as Hadoop, Spark, and NoSQL databases. The course covers topics such as data mining, machine learning algorithms, statistical analysis, and visualization techniques. Learning outcomes include understanding big data ecosystems, applying analytical tools to large datasets, and extracting meaningful insights from complex data structures.
Advanced Signal Processing: This course builds upon fundamental signal processing concepts to explore advanced techniques and applications. Students will study topics such as multirate systems, filter banks, wavelets, spectral estimation, and adaptive filtering. The course emphasizes practical implementation through laboratory sessions and project work. Learning outcomes include designing advanced signal processing algorithms, analyzing complex signals, and applying signal processing techniques to real-world problems.
Power System Analysis: This course covers the principles and methods of power system analysis and design. Students will study topics such as power flow analysis, fault analysis, stability analysis, load forecasting, and economic dispatch. The course combines theoretical concepts with practical applications using industry-standard software tools. Learning outcomes include analyzing power systems, designing efficient electrical networks, and understanding power system economics.
Steel Structures: This course focuses on the design and analysis of steel structures. Students will study topics such as structural behavior, design principles, connection details, load calculations, and construction methods. The course emphasizes practical applications through laboratory sessions and project work. Learning outcomes include designing safe and efficient steel structures, understanding structural behavior under various loads, and applying design codes and standards.
Concrete Technology: This course explores the properties, mix design, and applications of concrete materials in construction. Students will study topics such as cement chemistry, concrete mix design, testing methods, durability factors, and quality control. The course combines theoretical knowledge with practical laboratory sessions. Learning outcomes include designing appropriate concrete mixes, understanding concrete behavior under various conditions, and ensuring quality control in concrete construction.
Biomedical Devices: This course introduces students to the design and application of biomedical devices. Students will study topics such as bioinstrumentation, medical imaging, biosensors, and medical device regulations. The course emphasizes practical applications through laboratory sessions and project work. Learning outcomes include designing biomedical devices, understanding medical device standards, and applying engineering principles to healthcare applications.
Sustainable Design and Construction: This course explores sustainable practices in building design and construction. Students will study topics such as green building materials, energy-efficient design, waste reduction strategies, and environmental impact assessment. The course combines theoretical knowledge with practical applications through case studies and project work. Learning outcomes include applying sustainable design principles, evaluating environmental impacts, and developing sustainable construction practices.
Advanced Power Electronics: This course covers advanced topics in power electronics and their applications. Students will study topics such as power converters, inverters, DC-DC converters, and motor drives. The course emphasizes practical implementation through laboratory sessions and project work. Learning outcomes include designing power electronic circuits, understanding power conversion techniques, and applying power electronics to industrial applications.
Earthquake Resistant Design: This course focuses on the principles and methods of earthquake-resistant design. Students will study topics such as seismic analysis, structural response, design codes, and retrofitting techniques. The course combines theoretical concepts with practical applications using industry-standard software tools. Learning outcomes include analyzing seismic loads, designing earthquake-resistant structures, and understanding building codes for seismic regions.
Advanced Materials: This course explores advanced materials and their properties in engineering applications. Students will study topics such as composite materials, nanomaterials, smart materials, and material selection criteria. The course combines theoretical knowledge with practical laboratory sessions. Learning outcomes include understanding material properties, selecting appropriate materials for specific applications, and applying advanced materials in engineering designs.
Biomedical Signal Processing: This course focuses on the processing and analysis of biomedical signals. Students will study topics such as ECG, EEG, EMG, and other physiological signals. The course emphasizes practical implementation through laboratory sessions and project work. Learning outcomes include analyzing biomedical signals, applying signal processing techniques to healthcare applications, and developing biomedical signal processing algorithms.
Automation and Robotics: This course introduces students to the principles of automation and robotics. Students will study topics such as control systems, sensor technology, robot kinematics, and industrial automation. The course combines theoretical knowledge with practical laboratory sessions and project work. Learning outcomes include designing automated systems, understanding robotic applications, and applying automation principles in engineering.
Capstone Project I: This course provides students with an opportunity to work on a comprehensive engineering project under faculty supervision. Students will select a project topic, conduct literature review, design project methodology, and develop project deliverables. The course emphasizes teamwork, project management, and technical communication skills. Learning outcomes include applying engineering principles to solve real-world problems, working effectively in teams, and presenting technical concepts clearly.
Project-Based Learning Philosophy
The department's philosophy on project-based learning is rooted in the belief that hands-on experience is essential for developing competent engineers who can adapt to the dynamic demands of industry. Project-based learning encourages students to apply theoretical knowledge to practical problems, fostering innovation, critical thinking, and problem-solving skills.
The mandatory mini-projects in the second and third years provide students with opportunities to explore specific engineering concepts and develop practical skills. These projects are typically completed in teams and involve research, design, implementation, and presentation phases. Students work under the guidance of faculty mentors who provide technical support and feedback throughout the project lifecycle.
The final-year thesis or capstone project is a significant undertaking that allows students to demonstrate their expertise in a specialized area of engineering. Students select projects based on their interests and career aspirations, often collaborating with industry partners. The project involves extensive research, design, implementation, and documentation phases. Faculty mentors guide students through each stage of the project, ensuring that they meet academic standards and industry expectations.
Project selection is a collaborative process involving faculty mentors and students. Students are encouraged to propose project ideas based on their interests and available resources. The department provides guidelines for project proposal submission, including criteria for feasibility, relevance, and academic rigor. Faculty members evaluate project proposals and assign mentors based on expertise and availability.