Comprehensive Course Structure
The Electronics curriculum at Roorkee College Of Engineering is meticulously structured to ensure a progressive and comprehensive learning experience over four years. The program includes core subjects, departmental electives, science electives, and laboratory components designed to build both theoretical understanding and practical skills.
| Semester | Course Code | Course Title | Credits (L-T-P-C) | Prerequisites |
|---|---|---|---|---|
| I | ES101 | Engineering Mathematics I | 3-0-2-4 | - |
| I | ES102 | Physics for Electronics | 3-0-2-4 | - |
| I | ES103 | Chemistry for Engineers | 3-0-2-4 | - |
| I | ES104 | Introduction to Electronics | 3-0-2-4 | - |
| I | ES105 | Programming for Engineers | 3-0-2-4 | - |
| I | ES106 | Engineering Graphics | 2-0-2-3 | - |
| I | ES107 | Workshop Practice | 0-0-4-2 | - |
| II | ES201 | Engineering Mathematics II | 3-0-2-4 | ES101 |
| II | ES202 | Circuit Analysis | 3-0-2-4 | ES102 |
| II | ES203 | Electronic Devices | 3-0-2-4 | ES102 |
| II | ES204 | Digital Logic Design | 3-0-2-4 | ES104 |
| II | ES205 | Signals and Systems | 3-0-2-4 | ES101 |
| II | ES206 | Lab: Circuit Analysis | 0-0-4-2 | ES202 |
| III | ES301 | Control Systems | 3-0-2-4 | ES205 |
| III | ES302 | Microprocessors and Microcontrollers | 3-0-2-4 | ES204 |
| III | ES303 | Communication Systems | 3-0-2-4 | ES205 |
| III | ES304 | Electromagnetic Fields | 3-0-2-4 | ES102 |
| III | ES305 | Probability and Statistics | 3-0-2-4 | ES101 |
| III | ES306 | Lab: Microprocessors | 0-0-4-2 | ES302 |
| IV | ES401 | Embedded Systems Design | 3-0-2-4 | ES302 |
| IV | ES402 | VLSI Design Fundamentals | 3-0-2-4 | ES302 |
| IV | ES403 | Power Electronics | 3-0-2-4 | ES203 |
| IV | ES404 | Signal Processing | 3-0-2-4 | ES205 |
| IV | ES405 | Antennas and Wave Propagation | 3-0-2-4 | ES304 |
| IV | ES406 | Lab: Embedded Systems | 0-0-4-2 | ES401 |
| V | ES501 | Machine Learning for Signal Processing | 3-0-2-4 | ES404 |
| V | ES502 | Wireless Communication | 3-0-2-4 | ES303 |
| V | ES503 | Biomedical Electronics | 3-0-2-4 | ES302 |
| V | ES504 | Robotics and Control Systems | 3-0-2-4 | ES301 |
| V | ES505 | Advanced VLSI Design | 3-0-2-4 | ES402 |
| V | ES506 | Lab: Advanced VLSI Design | 0-0-4-2 | ES505 |
| VI | ES601 | Internet of Things (IoT) | 3-0-2-4 | ES401 |
| VI | ES602 | Power System Analysis | 3-0-2-4 | ES303 |
| VI | ES603 | Renewable Energy Systems | 3-0-2-4 | ES303 |
| VI | ES604 | Computer Vision and Image Processing | 3-0-2-4 | ES404 |
| VI | ES605 | Advanced Control Systems | 3-0-2-4 | ES301 |
| VI | ES606 | Lab: IoT and Embedded Systems | 0-0-4-2 | ES601 |
| VII | ES701 | Capstone Project I | 3-0-2-4 | - |
| VII | ES702 | Research Methodology | 3-0-2-4 | - |
| VII | ES703 | Advanced Topics in Electronics | 3-0-2-4 | - |
| VIII | ES801 | Capstone Project II | 3-0-2-4 | ES701 |
| VIII | ES802 | Electronics in Industry | 3-0-2-4 | - |
| VIII | ES803 | Entrepreneurship and Innovation | 3-0-2-4 | - |
Advanced Departmental Electives
The department offers several advanced elective courses designed to deepen students' understanding of specialized areas within electronics:
- Machine Learning for Signal Processing: This course explores the intersection of signal processing and machine learning, focusing on applications in audio, image, and biomedical signals. Students learn to implement algorithms using Python and MATLAB, with a focus on real-world case studies.
- Wireless Communication: A comprehensive exploration of wireless communication systems including modulation techniques, multiple access methods, and network protocols. The course integrates theoretical concepts with practical implementation using software-defined radios.
- Biomedical Electronics: Focuses on the application of electronic principles in healthcare, covering topics such as medical imaging, biosensors, and patient monitoring systems. Students gain hands-on experience with biomedical instrumentation.
- Robotics and Control Systems: Combines control theory with robotics applications, teaching students to design and implement autonomous robotic systems using microcontrollers and sensors.
- Advanced VLSI Design: Covers advanced topics in very large-scale integration including system-on-chip design, low-power design techniques, and advanced fabrication processes. Students work on real-world design projects using industry-standard tools.
- Internet of Things (IoT): Explores the architecture and implementation of IoT systems, covering sensor networks, cloud computing integration, and security considerations in connected devices.
- Power System Analysis: Introduces students to the analysis of electrical power systems including load flow studies, stability analysis, and protection schemes. The course emphasizes practical applications in modern power grids.
- Renewable Energy Systems: Focuses on the integration of renewable energy sources into the power grid, covering solar and wind energy conversion systems, energy storage technologies, and smart grid concepts.
- Computer Vision and Image Processing: Combines image processing techniques with machine learning algorithms to solve problems in computer vision applications such as object recognition and tracking.
- Advanced Control Systems: Covers modern control theory including state-space methods, robust control, and optimal control. The course emphasizes design and implementation of control systems for complex industrial processes.
Project-Based Learning Philosophy
The department strongly believes in project-based learning as a means to bridge the gap between theoretical knowledge and practical application. Students are encouraged to engage in hands-on projects from their first year, gradually increasing in complexity and scope.
The structure of the project-based learning approach includes:
- Mini-projects (Year I-II): These are smaller-scale projects designed to reinforce fundamental concepts and build basic skills. Projects typically involve designing simple circuits or implementing basic algorithms.
- Intermediate Projects (Year III): These projects focus on more complex applications, often involving integration of multiple concepts and technologies. Students work in teams to develop prototypes or simulation models.
- Capstone Projects (Year IV): The final-year capstone project is a comprehensive endeavor that requires students to apply all their knowledge to solve a real-world problem. Projects are often sponsored by industry partners and involve extensive research and development.
Evaluation criteria for projects include:
- Technical Execution
- Innovation and Creativity
- Team Collaboration
- Documentation Quality
- Presentation Skills
- Problem-Solving Approach
The project selection process involves a combination of faculty recommendations, student interest, and industry relevance. Students are matched with mentors based on their interests and expertise, ensuring personalized guidance throughout the project lifecycle.