Search and navigate to colleges and courses
Apply
Scholarships & exams
Fees
₹2,50,000
Placement
92.0%
Avg Package
₹4,50,000
Highest Package
₹8,00,000
Fees
₹2,50,000
Placement
92.0%
Avg Package
₹4,50,000
Highest Package
₹8,00,000
Seats
120
Students
180
Seats
120
Students
180
The Electronics Engineering program at Govt Polytechnic Gopeshwar Chamoli is structured over 8 semesters, with a blend of core courses, departmental electives, science electives, and laboratory sessions. Each semester builds upon the previous one, ensuring a progressive learning experience.
| Year | Semester | Course Code | Course Title | Credit Structure (L-T-P-C) | Prerequisites |
|---|---|---|---|---|---|
| 1 | I | EE101 | Engineering Mathematics I | 3-1-0-4 | - |
| 1 | I | EE102 | Physics for Electronics | 3-1-0-4 | - |
| 1 | I | EE103 | Chemistry for Electronics | 3-1-0-4 | - |
| 1 | I | EE104 | Basic Electrical Engineering | 3-1-0-4 | - |
| 1 | I | EE105 | Introduction to Programming | 2-1-0-3 | - |
| 1 | I | EE106 | Workshop Practice I | 0-0-2-1 | - |
| 1 | II | EE201 | Engineering Mathematics II | 3-1-0-4 | EE101 |
| 1 | II | EE202 | Electronics Devices and Circuits | 3-1-0-4 | EE104 |
| 1 | II | EE203 | Digital Logic Design | 3-1-0-4 | EE105 |
| 1 | II | EE204 | Computer Organization | 3-1-0-4 | EE105 |
| 1 | II | EE205 | Electromagnetic Fields and Waves | 3-1-0-4 | EE102 |
| 1 | II | EE206 | Workshop Practice II | 0-0-2-1 | - |
| 2 | III | EE301 | Signals and Systems | 3-1-0-4 | EE201, EE202 |
| 2 | III | EE302 | Analog Electronic Circuits | 3-1-0-4 | EE202 |
| 2 | III | EE303 | Digital Integrated Circuits | 3-1-0-4 | EE203 |
| 2 | III | EE304 | Microprocessor and Microcontroller | 3-1-0-4 | EE204 |
| 2 | III | EE305 | Electronic Measurements and Instrumentation | 3-1-0-4 | EE202 |
| 2 | III | EE306 | Workshop Practice III | 0-0-2-1 | - |
| 2 | IV | EE401 | Control Systems | 3-1-0-4 | EE301 |
| 2 | IV | EE402 | Power Electronics | 3-1-0-4 | EE202 |
| 2 | IV | EE403 | Communication Systems | 3-1-0-4 | EE301 |
| 2 | IV | EE404 | VLSI Design | 3-1-0-4 | EE303 |
| 2 | IV | EE405 | Embedded Systems | 3-1-0-4 | EE304 |
| 2 | IV | EE406 | Workshop Practice IV | 0-0-2-1 | - |
| 3 | V | EE501 | Advanced Signal Processing | 3-1-0-4 | EE301 |
| 3 | V | EE502 | Wireless Communication | 3-1-0-4 | EE403 |
| 3 | V | EE503 | Power System Analysis | 3-1-0-4 | EE202 |
| 3 | V | EE504 | Robotics and Automation | 3-1-0-4 | EE401 |
| 3 | V | EE505 | Artificial Intelligence & Machine Learning | 3-1-0-4 | EE301, EE304 |
| 3 | V | EE506 | Workshop Practice V | 0-0-2-1 | - |
| 3 | VI | EE601 | Advanced Control Systems | 3-1-0-4 | EE401 |
| 3 | VI | EE602 | Optical Communication | 3-1-0-4 | EE403 |
| 3 | VI | EE603 | Renewable Energy Systems | 3-1-0-4 | EE402 |
| 3 | VI | EE604 | Microelectromechanical Systems (MEMS) | 3-1-0-4 | EE302 |
| 3 | VI | EE605 | Internet of Things (IoT) | 3-1-0-4 | EE505 |
| 3 | VI | EE606 | Workshop Practice VI | 0-0-2-1 | - |
| 4 | VII | EE701 | Final Year Project I | 0-0-6-6 | EE505, EE605 |
| 4 | VII | EE702 | Capstone Project Development | 0-0-4-4 | - |
| 4 | VII | EE703 | Advanced VLSI Design | 3-1-0-4 | EE404 |
| 4 | VII | EE704 | Research Methodology | 2-1-0-3 | - |
| 4 | VII | EE705 | Professional Ethics and Management | 2-1-0-3 | - |
| 4 | VII | EE706 | Workshop Practice VII | 0-0-2-1 | - |
| 4 | VIII | EE801 | Final Year Project II | 0-0-6-6 | EE701 |
| 4 | VIII | EE802 | Project Presentation and Defense | 0-0-2-2 | - |
| 4 | VIII | EE803 | Industry Exposure Workshop | 0-0-2-2 | - |
| 4 | VIII | EE804 | Elective Courses (Optional) | 3-1-0-4 | - |
| 4 | VIII | EE805 | Entrepreneurship and Innovation | 2-1-0-3 | - |
| 4 | VIII | EE806 | Workshop Practice VIII | 0-0-2-1 | - |
Advanced Signal Processing: This course delves into advanced topics in signal processing including filter design, wavelet transforms, and spectral estimation. Students learn to implement these techniques using MATLAB and Python, preparing them for careers in audio/video processing, biomedical signal analysis, and data science.
Wireless Communication: Focuses on modern wireless communication systems including cellular networks, Wi-Fi, Bluetooth, and satellite communications. The course covers modulation schemes, multiple access techniques, and network protocols, providing students with insights into the functioning of contemporary wireless infrastructure.
Power System Analysis: This elective explores power generation, transmission, and distribution systems. Topics include load flow analysis, short circuit calculations, and stability studies. Students gain practical knowledge in designing efficient power systems for industrial and residential applications.
Robotics and Automation: Combines mechanical engineering principles with electronics to design automated systems. The course includes robot kinematics, sensor integration, control algorithms, and programming using ROS (Robot Operating System). Practical labs involve building and testing robots capable of performing specific tasks.
Artificial Intelligence & Machine Learning: Introduces students to AI concepts and machine learning algorithms including supervised and unsupervised learning. The course covers neural networks, deep learning frameworks like TensorFlow and PyTorch, and applications in image recognition, natural language processing, and predictive analytics.
Advanced Control Systems: Extends the study of control systems by covering modern control theory including state-space representation, optimal control, and adaptive control. Students learn to model complex systems and design controllers using simulation tools like MATLAB/Simulink.
Optical Communication: Explores the principles and applications of optical fiber communication systems. Topics include light sources, detectors, transmission media, and network topologies. The course provides hands-on experience with optical components and systems used in modern telecommunications.
Renewable Energy Systems: Focuses on solar, wind, and hydroelectric power generation technologies. Students study energy conversion principles, grid integration, and system design for sustainable energy solutions. Case studies from real-world installations provide practical context to theoretical concepts.
Microelectromechanical Systems (MEMS): Covers the design and fabrication of microscale mechanical devices using semiconductor manufacturing techniques. The course includes topics such as sensing mechanisms, actuators, and packaging technologies used in automotive, biomedical, and consumer electronics applications.
Internet of Things (IoT): Introduces IoT concepts including network protocols, sensor networks, edge computing, and cloud integration. Students develop IoT solutions using platforms like Arduino, Raspberry Pi, and AWS IoT Core, preparing them for careers in smart cities, industrial automation, and connected healthcare.
The department's approach to project-based learning is rooted in the belief that real-world problem-solving skills are best developed through hands-on experience. Projects are structured to encourage creativity, teamwork, and critical thinking while aligning with current industry trends and challenges.
Mini-projects begin in the second year and continue throughout the program, allowing students to apply theoretical knowledge in practical scenarios. These projects are typically completed in groups of 3-4 students and involve designing, prototyping, testing, and presenting solutions to real-world problems.
The final-year thesis or capstone project is a comprehensive endeavor that integrates all learned concepts and provides an opportunity for students to demonstrate mastery in their chosen specialization. Students select projects based on their interests and career goals, working closely with faculty mentors who guide them through the research and development process.
Evaluation criteria for projects include technical merit, innovation, documentation quality, presentation skills, and peer feedback. The project defense is conducted by a panel of faculty members and industry experts, ensuring that students receive constructive criticism and valuable insights into their work.
Faculty mentorship plays a crucial role in the success of these projects. Mentors provide guidance on project selection, research methodology, technical challenges, and professional development. Regular meetings and progress reports ensure continuous support and timely completion of projects.
