Comprehensive Course Structure
| Semester | Course Code | Course Title | Credit Structure (L-T-P-C) | Prerequisites |
|---|---|---|---|---|
| 1 | EG101 | Engineering Mathematics I | 3-1-0-4 | - |
| 1 | EG102 | Physics for Electronics | 3-1-0-4 | - |
| 1 | EG103 | Basic Electrical Circuits | 3-1-0-4 | - |
| 1 | EG104 | Introduction to Programming | 2-0-2-3 | - |
| 1 | EG105 | Engineering Drawing | 1-0-2-2 | - |
| 1 | EG106 | Workshop Practice | 0-0-3-1 | - |
| 2 | EG201 | Engineering Mathematics II | 3-1-0-4 | EG101 |
| 2 | EG202 | Electromagnetic Fields | 3-1-0-4 | EG102 |
| 2 | EG203 | Analog Electronic Circuits | 3-1-0-4 | EG103 |
| 2 | EG204 | Digital Logic Design | 3-1-0-4 | - |
| 2 | EG205 | Signals and Systems | 3-1-0-4 | EG101 |
| 2 | EG206 | Computer Organization & Architecture | 3-1-0-4 | EG204 |
| 3 | EG301 | Microprocessor and Microcontroller | 3-1-0-4 | EG206 |
| 3 | EG302 | Control Systems | 3-1-0-4 | EG205 |
| 3 | EG303 | Communication Systems | 3-1-0-4 | EG205 |
| 3 | EG304 | VLSI Design | 3-1-0-4 | EG203 |
| 3 | EG305 | Power Electronics | 3-1-0-4 | EG203 |
| 3 | EG306 | Embedded Systems | 3-1-0-4 | EG301 |
| 4 | EG401 | Digital Signal Processing | 3-1-0-4 | EG205 |
| 4 | EG402 | Computer Networks | 3-1-0-4 | EG303 |
| 4 | EG403 | Wireless Communication | 3-1-0-4 | EG303 |
| 4 | EG404 | Internet of Things | 3-1-0-4 | EG306 |
| 4 | EG405 | Renewable Energy Systems | 3-1-0-4 | EG203 |
| 4 | EG406 | Project Management | 3-1-0-4 | - |
| 5 | EG501 | Artificial Intelligence in Electronics | 3-1-0-4 | EG401 |
| 5 | EG502 | Advanced Microprocessor Design | 3-1-0-4 | EG301 |
| 5 | EG503 | Signal Processing Applications | 3-1-0-4 | EG401 |
| 5 | EG504 | RF and Microwave Engineering | 3-1-0-4 | EG202 |
| 5 | EG505 | Computer Vision | 3-1-0-4 | EG401 |
| 5 | EG506 | Capstone Project I | 0-0-6-6 | - |
| 6 | EG601 | Advanced VLSI Design | 3-1-0-4 | EG304 |
| 6 | EG602 | Neural Networks and Deep Learning | 3-1-0-4 | EG501 |
| 6 | EG603 | Smart Sensors and Actuators | 3-1-0-4 | EG305 |
| 6 | EG604 | Power System Analysis | 3-1-0-4 | EG203 |
| 6 | EG605 | Capstone Project II | 0-0-6-6 | - |
| 7 | EG701 | Emerging Technologies in Electronics | 3-1-0-4 | EG501 |
| 7 | EG702 | Quantum Computing Fundamentals | 3-1-0-4 | EG202 |
| 7 | EG703 | Advanced Wireless Technologies | 3-1-0-4 | EG403 |
| 7 | EG704 | Data Analytics in Electronics | 3-1-0-4 | EG401 |
| 7 | EG705 | Entrepreneurship in Tech | 3-1-0-4 | - |
| 8 | EG801 | Industry Internship | 0-0-12-12 | - |
Advanced Departmental Elective Courses
The department offers several advanced elective courses designed to provide specialized knowledge and practical skills in emerging areas of electronics. These courses are developed in consultation with industry experts and are aligned with global trends.
One such course is 'Artificial Intelligence in Electronics,' which explores the integration of AI algorithms into electronic systems. Students learn about neural networks, deep learning frameworks, and how these technologies can be applied to improve performance in various domains like robotics, healthcare, and smart manufacturing.
'Advanced VLSI Design' delves into advanced fabrication techniques, layout design, and optimization strategies for integrated circuits. The course includes hands-on projects using industry-standard tools such as Cadence and Synopsys, preparing students for roles in semiconductor design companies.
'Smart Sensors and Actuators' focuses on the development and implementation of sensor technologies used in IoT applications. Students explore topics such as MEMS sensors, wireless sensor networks, and data fusion techniques to build intelligent sensing systems.
'Power System Analysis' introduces students to the analysis and design of electrical power systems. The course covers fundamental concepts like load flow analysis, fault analysis, and stability studies, which are essential for careers in energy sector companies.
'Neural Networks and Deep Learning' is a comprehensive course that covers theoretical foundations and practical applications of neural networks. Students gain experience in building and training deep learning models using frameworks like TensorFlow and PyTorch, enabling them to pursue roles in AI research and development.
'Quantum Computing Fundamentals' explores the principles of quantum mechanics and their application in computing. This cutting-edge course provides insights into quantum algorithms, quantum error correction, and the potential impact of quantum computing on electronics.
'Advanced Wireless Technologies' examines current and future wireless communication standards, including 5G, Wi-Fi 6, and satellite communications. Students study modulation techniques, antenna design, and network protocols to understand how modern wireless systems function.
'Data Analytics in Electronics' integrates statistical methods with electronic engineering principles. Students learn how to extract meaningful insights from large datasets using tools like Python and R, preparing them for roles in data-driven electronics companies.
'Entrepreneurship in Tech' teaches students how to identify market opportunities, develop business plans, and launch startups in the tech sector. The course includes guest lectures from successful entrepreneurs and mentorship support for developing innovative ideas.
Project-Based Learning Philosophy
Our department strongly believes in project-based learning as a means of fostering innovation and practical application. This philosophy is reflected throughout the curriculum, with mandatory mini-projects in early semesters and a comprehensive capstone project in the final year.
The structure of these projects involves selecting a topic relevant to current industry needs or emerging technologies. Students form teams and work under the guidance of faculty mentors who provide expertise and support. The evaluation criteria include innovation, technical execution, presentation quality, and impact potential.
Mini-projects in the first two years are typically focused on applying basic concepts learned in lectures to real-world scenarios. For example, students might design a simple microcontroller-based system or analyze circuit performance using simulation software.
The final-year capstone project is a significant undertaking that allows students to demonstrate their mastery of the subject. Projects often involve collaboration with industry partners, resulting in solutions that address actual problems faced by organizations. These projects are evaluated by both faculty members and external reviewers from the industry.