Comprehensive Course Structure
| Semester | Course Code | Full Course Title | Credit Structure (L-T-P-C) | Prerequisites |
|---|---|---|---|---|
| I | EGE101 | Engineering Mathematics I | 3-1-0-4 | - |
| I | EGE102 | Basic Electronics | 3-1-0-4 | - |
| I | EGE103 | Engineering Physics | 3-1-0-4 | - |
| I | EGE104 | Programming in C | 2-0-2-3 | - |
| I | EGE105 | Engineering Graphics | 2-0-2-3 | - |
| I | EGE106 | Workshop Practice | 0-0-4-2 | - |
| II | EGE201 | Engineering Mathematics II | 3-1-0-4 | EGE101 |
| II | EGE202 | Electrical Circuits | 3-1-0-4 | EGE102 |
| II | EGE203 | Digital Logic Design | 3-1-0-4 | EGE102 |
| II | EGE204 | Computer Organization | 3-1-0-4 | EGE104 |
| II | EGE205 | Engineering Chemistry | 3-1-0-4 | - |
| III | EGE301 | Signals and Systems | 3-1-0-4 | EGE201 |
| III | EGE302 | Analog Electronics | 3-1-0-4 | EGE202 |
| III | EGE303 | Microwave Engineering | 3-1-0-4 | EGE202 |
| III | EGE304 | Data Structures and Algorithms | 3-1-0-4 | EGE204 |
| III | EGE305 | Electromagnetic Field Theory | 3-1-0-4 | EGE201 |
| IV | EGE401 | Microprocessors and Microcontrollers | 3-1-0-4 | EGE302 |
| IV | EGE402 | Embedded Systems | 3-1-0-4 | EGE304 |
| IV | EGE403 | VLSI Design | 3-1-0-4 | EGE302 |
| IV | EGE404 | Communication Systems | 3-1-0-4 | EGE301 |
| IV | EGE405 | Power Electronics | 3-1-0-4 | EGE202 |
| V | EGE501 | Control Systems | 3-1-0-4 | EGE301 |
| V | EGE502 | Wireless Communication | 3-1-0-4 | EGE404 |
| V | EGE503 | Robotics | 3-1-0-4 | EGE402 |
| V | EGE504 | Image Processing | 3-1-0-4 | EGE301 |
| V | EGE505 | Advanced Digital Design | 3-1-0-4 | EGE302 |
| VI | EGE601 | Internet of Things (IoT) | 3-1-0-4 | EGE503 |
| VI | EGE602 | Digital Signal Processing | 3-1-0-4 | EGE301 |
| VI | EGE603 | Wireless Sensor Networks | 3-1-0-4 | EGE502 |
| VI | EGE604 | Renewable Energy Systems | 3-1-0-4 | EGE405 |
| VI | EGE605 | Project Management | 3-1-0-4 | - |
| VII | EGE701 | Final Year Project | 0-0-8-8 | EGE501, EGE602 |
| VIII | EGE801 | Mini Project | 0-0-4-4 | EGE701 |
Detailed Departmental Elective Courses
Advanced Digital Design: This course focuses on the design and implementation of complex digital systems using modern tools and techniques. Students learn about high-level synthesis, verification methods, and design automation.
VLSI Design: The course covers integrated circuit design principles, layout design, and testing methodologies. It includes hands-on experience with industry-standard CAD tools for designing custom chips.
Wireless Communication: This elective explores wireless transmission technologies, modulation schemes, and network protocols. Students gain practical skills in setting up wireless networks and analyzing signal quality.
Digital Signal Processing: The course delves into the mathematical foundations of digital signal processing, including filtering techniques, spectral analysis, and real-time processing applications.
Control Systems: This course teaches the principles of feedback control systems, stability analysis, and controller design. Practical labs involve designing and simulating control systems for various applications.
Image Processing: Students learn to apply mathematical algorithms to process and analyze images. Topics include image enhancement, segmentation, feature extraction, and pattern recognition techniques.
Robotics: This course combines mechanical engineering with electronics and computer science. Students build robots from scratch and program them using ROS (Robot Operating System).
Internet of Things (IoT): The course introduces IoT concepts, including sensor networks, cloud computing integration, and secure communication protocols. Practical assignments involve developing smart applications.
Wireless Sensor Networks: This elective covers the design and deployment of wireless sensor networks for environmental monitoring, healthcare, and industrial applications.
Renewable Energy Systems: Students study solar panels, wind turbines, and battery storage systems. The course emphasizes practical implementation and energy management strategies.
Embedded Software Development: The course focuses on developing software for embedded devices, including real-time operating systems, memory optimization, and debugging techniques.
Signal Transmission Techniques: This subject explores advanced signal transmission methods used in modern communication systems, including multiplexing, error correction, and modulation schemes.
Smart Grid Technologies: Students learn about smart grid infrastructure, demand response systems, and energy efficiency improvements in power distribution networks.
Advanced Microcontroller Programming: This course provides deep insights into microcontroller architecture and programming. Practical labs involve developing complex embedded applications using ARM Cortex-M series processors.
Quantum Computing Fundamentals: An introductory course covering quantum mechanics principles, qubit manipulation, and quantum algorithms for future computing technologies.
Project-Based Learning Philosophy
The department's approach to project-based learning emphasizes practical application of theoretical knowledge. Students engage in both mini-projects and a comprehensive final-year thesis or capstone project.
Mini-projects are conducted during the third and fourth years, allowing students to explore specific areas of interest under faculty guidance. These projects often involve collaboration with industry partners and are evaluated based on innovation, technical execution, and presentation skills.
The final-year thesis or capstone project is a significant undertaking that requires students to independently design, implement, and document a complete system or solution. This process involves extensive literature review, prototyping, testing, and documentation.
Students select their projects based on faculty expertise, industry trends, and personal interests. Each student is assigned a faculty mentor who provides guidance throughout the project lifecycle. Regular progress reports and milestone reviews ensure timely completion and quality output.