Curriculum Overview
The curriculum for the Electronics program at Gurukula Kangri Vishwavidyalaya Haridwar Faculty Of Engineering And Technology is designed to provide a comprehensive understanding of electronic principles, practical applications, and emerging technologies. The program spans four academic years with a total of eight semesters, each structured to build upon previous knowledge while introducing new concepts and skills.
| Semester | Course Code | Course Title | Credits (L-T-P-C) | Prerequisites |
|---|---|---|---|---|
| 1 | ENG101 | English for Engineering | 3-0-0-3 | - |
| 1 | MAT101 | Calculus and Differential Equations | 4-0-0-4 | - |
| 1 | PHY101 | Physics for Electronics | 3-0-0-3 | - |
| 1 | CHM101 | Chemistry for Engineers | 3-0-0-3 | - |
| 1 | CSE101 | Introduction to Programming | 2-0-2-3 | - |
| 1 | ELE101 | Basic Electrical Engineering | 3-0-0-3 | - |
| 2 | MAT201 | Linear Algebra and Probability | 4-0-0-4 | MAT101 |
| 2 | PHY201 | Modern Physics | 3-0-0-3 | PHY101 |
| 2 | ELE201 | Electrical Circuits and Networks | 4-0-0-4 | ELE101 |
| 2 | ELE202 | Electronic Devices and Circuits | 3-0-0-3 | ELE101 |
| 2 | CSE201 | Data Structures and Algorithms | 3-0-0-3 | CSE101 |
| 2 | ELE203 | Signals and Systems | 3-0-0-3 | MAT101 |
| 3 | MAT301 | Statistics and Numerical Methods | 3-0-0-3 | MAT201 |
| 3 | ELE301 | Microprocessors and Microcontrollers | 3-0-0-3 | ELE202 |
| 3 | ELE302 | Control Systems | 3-0-0-3 | ELE203 |
| 3 | ELE303 | Digital Signal Processing | 3-0-0-3 | ELE203 |
| 3 | ELE304 | Analog Integrated Circuits | 3-0-0-3 | ELE202 |
| 3 | ELE305 | Electromagnetic Fields and Waves | 3-0-0-3 | PHY201 |
| 4 | ELE401 | VLSI Design | 3-0-0-3 | ELE304 |
| 4 | ELE402 | Communication Systems | 3-0-0-3 | ELE203 |
| 4 | ELE403 | Power Electronics | 3-0-0-3 | ELE201 |
| 4 | ELE404 | Embedded Systems | 3-0-0-3 | ELE301 |
| 4 | ELE405 | Sensor Technology | 3-0-0-3 | ELE202 |
| 5 | ELE501 | Advanced Embedded Systems | 3-0-0-3 | ELE404 |
| 5 | ELE502 | Wireless Communications | 3-0-0-3 | ELE402 |
| 5 | ELE503 | Renewable Energy Systems | 3-0-0-3 | ELE403 |
| 5 | ELE504 | Biomedical Electronics | 3-0-0-3 | ELE202 |
| 5 | ELE505 | Optoelectronics | 3-0-0-3 | ELE305 |
| 6 | ELE601 | Machine Learning for Electronics | 3-0-0-3 | ELE303 |
| 6 | ELE602 | Quantum Electronics | 3-0-0-3 | ELE505 |
| 6 | ELE603 | Smart Grid Technologies | 3-0-0-3 | ELE503 |
| 6 | ELE604 | Advanced Control Systems | 3-0-0-3 | ELE302 |
| 6 | ELE605 | Research Methodology | 2-0-0-2 | - |
| 7 | ELE701 | Capstone Project I | 4-0-0-4 | ELE605 |
| 7 | ELE702 | Research Internship | 2-0-0-2 | - |
| 8 | ELE801 | Capstone Project II | 4-0-0-4 | ELE701 |
| 8 | ELE802 | Electronics Thesis | 4-0-0-4 | ELE701 |
The curriculum includes a balanced mix of core theoretical subjects, departmental electives, science electives, and practical laboratory sessions. Core subjects provide fundamental knowledge essential for understanding electronic systems, while departmental electives allow students to specialize in areas of interest such as AI, embedded systems, renewable energy, or biomedical electronics.
Advanced Departmental Elective Courses
Among the advanced departmental electives offered in the Electronics program are several specialized courses designed to prepare students for emerging industry trends and research opportunities. These include Machine Learning for Electronics, which introduces students to applying AI techniques in electronic system design; Quantum Electronics, focusing on quantum phenomena and their applications in electronics; Smart Grid Technologies, covering modern energy distribution systems; and Advanced Control Systems, delving deeper into control theory and implementation.
Each course is structured around specific learning outcomes that align with industry needs. For example, Machine Learning for Electronics emphasizes hands-on experience with neural networks, deep learning frameworks, and hardware-software co-design. Students learn to implement machine learning models on embedded platforms using tools like TensorFlow Lite, PyTorch, and ARM-based development kits.
Quantum Electronics explores quantum mechanics principles and their application in modern electronic devices such as quantum dots, quantum wells, and quantum computers. Through theoretical lectures and lab sessions, students gain insight into quantum computing architectures, photonic circuits, and superconducting qubits.
Smart Grid Technologies covers the integration of renewable energy sources into traditional power grids. Students study grid stability, demand response systems, smart meters, and distributed generation technologies. Practical components include simulations using MATLAB/Simulink and real-time monitoring of smart grid operations.
Advanced Control Systems builds upon foundational control theory by introducing modern control strategies such as robust control, adaptive control, and optimal control. Students work with software tools like MATLAB/Simulink and LabVIEW to design and simulate control systems for various applications including robotics, aerospace, and industrial automation.
Project-Based Learning Philosophy
The department's philosophy on project-based learning is rooted in the belief that students learn best when they engage actively with real-world problems. Projects are assigned at multiple levels throughout the program, from small group assignments to large-scale capstone projects involving industry partners.
Mini-projects are typically introduced in the second year and involve solving specific engineering challenges within a limited timeframe. These projects help students apply theoretical knowledge to practical situations while developing teamwork and communication skills.
The final-year thesis or capstone project is a significant component of the program, lasting approximately six months. Students select a topic related to their area of interest, often in collaboration with faculty members or industry sponsors. The process involves literature review, experimental design, implementation, data analysis, and presentation.
Faculty mentors play a crucial role in guiding students through each stage of the project process. They provide technical expertise, feedback on progress, and support in navigating challenges encountered during research or development phases.