Comprehensive Course Listing Across All Semesters
| Semester | Course Code | Course Title | L-T-P-C | Pre-requisites |
|---|---|---|---|---|
| 1 | EC101 | Engineering Mathematics I | 3-1-0-4 | - |
| 1 | EC102 | Basic Electrical Engineering | 3-1-0-4 | - |
| 1 | EC103 | Introduction to Electronics | 3-1-0-4 | - |
| 1 | EC104 | Programming and Problem Solving | 3-1-0-4 | - |
| 1 | EC105 | Physical Sciences Lab | 0-0-3-2 | - |
| 2 | EC201 | Engineering Mathematics II | 3-1-0-4 | EC101 |
| 2 | EC202 | Analog Electronics I | 3-1-0-4 | EC103 |
| 2 | EC203 | Digital Logic Design | 3-1-0-4 | - |
| 2 | EC204 | Computer Organization and Architecture | 3-1-0-4 | EC104 |
| 2 | EC205 | Digital Electronics Lab | 0-0-3-2 | EC203 |
| 3 | EC301 | Engineering Mathematics III | 3-1-0-4 | EC201 |
| 3 | EC302 | Analog Electronics II | 3-1-0-4 | EC202 |
| 3 | EC303 | Signals and Systems | 3-1-0-4 | EC201 |
| 3 | EC304 | Microprocessors and Microcontrollers | 3-1-0-4 | EC204 |
| 3 | EC305 | Microelectronics Lab | 0-0-3-2 | EC302 |
| 4 | EC401 | Probability and Statistics | 3-1-0-4 | EC201 |
| 4 | EC402 | Communication Systems | 3-1-0-4 | EC303 |
| 4 | EC403 | Control Systems | 3-1-0-4 | EC303 |
| 4 | EC404 | Embedded Systems | 3-1-0-4 | EC304 |
| 4 | EC405 | Embedded Systems Lab | 0-0-3-2 | EC404 |
| 5 | EC501 | VLSI Design | 3-1-0-4 | EC302 |
| 5 | EC502 | Power Electronics | 3-1-0-4 | EC202 |
| 5 | EC503 | Antennas and Wave Propagation | 3-1-0-4 | EC402 |
| 5 | EC504 | RF and Microwave Engineering | 3-1-0-4 | EC402 |
| 5 | EC505 | VLSI Lab | 0-0-3-2 | EC501 |
| 6 | EC601 | Robotics and Automation | 3-1-0-4 | EC403 |
| 6 | EC602 | Image Processing and Pattern Recognition | 3-1-0-4 | EC401 |
| 6 | EC603 | Cybersecurity Fundamentals | 3-1-0-4 | EC402 |
| 6 | EC604 | Renewable Energy Systems | 3-1-0-4 | EC502 |
| 6 | EC605 | Renewable Energy Systems Lab | 0-0-3-2 | EC604 |
| 7 | EC701 | Advanced Signal Processing | 3-1-0-4 | EC303 |
| 7 | EC702 | Biomedical Electronics | 3-1-0-4 | EC302 |
| 7 | EC703 | Neural Networks and Deep Learning | 3-1-0-4 | EC401 |
| 7 | EC704 | Wireless Sensor Networks | 3-1-0-4 | EC402 |
| 7 | EC705 | Biomedical Electronics Lab | 0-0-3-2 | EC702 |
| 8 | EC801 | Capstone Project I | 3-0-0-6 | - |
| 8 | EC802 | Capstone Project II | 3-0-0-6 | EC801 |
| 8 | EC803 | Industrial Training | 0-0-6-3 | - |
Detailed Overview of Advanced Departmental Electives
The department offers a rich array of advanced elective courses designed to deepen students' understanding and enhance their practical skills:
1. VLSI Design
This course provides an in-depth exploration of Very Large Scale Integration (VLSI) design methodologies, including logic synthesis, layout design, and testing strategies. Students engage with CAD tools like Cadence and Mentor Graphics to design integrated circuits from gate-level to system-level abstraction.
2. Power Electronics
This elective delves into the principles of power conversion and control using semiconductor devices. Topics include rectifiers, inverters, DC-DC converters, and motor drives. Practical sessions involve designing and simulating power electronic circuits using MATLAB/Simulink.
3. Antennas and Wave Propagation
Students study the theory and application of various types of antennas including dipole, loop, patch, and array antennas. The course covers wave propagation in different media, radiation patterns, and antenna measurements using specialized equipment.
4. RF and Microwave Engineering
This advanced course explores high-frequency circuit design, transmission lines, and microwave components such as filters, amplifiers, and oscillators. Emphasis is placed on practical design challenges and real-world applications in telecommunications and radar systems.
5. Robotics and Automation
Students learn about robot kinematics, dynamics, control systems, and sensor integration. The course includes hands-on projects involving Arduino-based robots, robotic arms, and autonomous vehicle designs.
6. Image Processing and Pattern Recognition
This course introduces students to image enhancement, segmentation, feature extraction, and machine learning algorithms for pattern recognition. Applications include medical imaging, surveillance systems, and computer vision technologies.
7. Cybersecurity Fundamentals
The focus is on protecting digital assets from cyber threats through encryption, authentication protocols, network security models, and incident response strategies. Students gain hands-on experience with tools like Wireshark, Nmap, and Burp Suite.
8. Renewable Energy Systems
This course covers solar photovoltaic systems, wind turbines, energy storage technologies, and smart grid integration. Practical labs involve designing and testing renewable energy installations using real-time monitoring systems.
9. Advanced Signal Processing
This elective explores advanced signal processing techniques including wavelet transforms, adaptive filtering, and spectral estimation methods. Students work on projects involving audio/video signal processing, speech recognition, and biomedical data analysis.
10. Biomedical Electronics
Students study electronic systems used in healthcare applications such as ECG monitors, pacemakers, and medical imaging devices. The course includes lab sessions on designing biosensors and interfacing with biological signals using microcontrollers and embedded systems.
11. Neural Networks and Deep Learning
This course introduces students to artificial neural networks, deep learning architectures, and their applications in image recognition, natural language processing, and predictive analytics. Practical sessions involve using TensorFlow and PyTorch for model development.
12. Wireless Sensor Networks
The course covers design principles, communication protocols, and deployment strategies for wireless sensor networks. Students build and test networks using Zigbee, Bluetooth Low Energy, and LoRa technologies in various environments.
Project-Based Learning Philosophy
Our department places strong emphasis on project-based learning as a core component of the curriculum. This approach ensures that students gain real-world experience while reinforcing theoretical concepts learned in class.
Mini Projects (Years 3-4)
Mini projects are assigned at the end of each semester to help students apply concepts from multiple courses simultaneously. These projects typically last 8-10 weeks and involve teams of 3-5 students working under faculty supervision.
Final-Year Thesis/Capstone Project
The capstone project is a significant culmination of the academic journey, requiring students to undertake an original research or development project. Students select projects based on their interests and career aspirations, often aligned with industry needs or faculty research areas.
Project Selection Process
Students can choose from a list of proposed projects provided by faculty members or submit their own ideas after consultation with mentors. The selection process involves submitting a proposal outlining objectives, methodology, timeline, and expected outcomes.
Evaluation Criteria
- Technical depth and innovation in solution design
- Project execution and problem-solving capabilities
- Presentation skills and documentation quality
- Collaboration and teamwork during the project lifecycle
The evaluation process includes both internal assessments by faculty advisors and external reviews by industry experts, ensuring that projects meet professional standards and industry expectations.