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.