Course Structure and Academic Plan
The Bachelor of Electronics and Communication program is designed over 8 semesters, with each semester carrying a specific set of core subjects, departmental electives, science electives, and laboratory sessions. The curriculum emphasizes a balanced approach between theoretical knowledge and practical application.
Year I - Semester I
| Course Code | Course Title | Credits (L-T-P-C) | Prerequisites |
|---|---|---|---|
| EC101 | Engineering Mathematics I | 4-0-0-4 | - |
| EC102 | Physics for Electronics | 3-0-0-3 | - |
| EC103 | Chemistry for Engineers | 3-0-0-3 | - |
| EC104 | Basic Electrical and Electronics Engineering | 4-0-0-4 | - |
| EC105 | Introduction to Programming | 3-0-0-3 | - |
| EC106 | Communication Skills | 2-0-0-2 | - |
| EC107 | Engineering Drawing and Computer Graphics | 3-0-0-3 | - |
Year I - Semester II
| Course Code | Course Title | Credits (L-T-P-C) | Prerequisites |
|---|---|---|---|
| EC201 | Engineering Mathematics II | 4-0-0-4 | EC101 |
| EC202 | Digital Logic Design | 3-0-0-3 | - |
| EC203 | Analog Electronics | 4-0-0-4 | EC104 |
| EC204 | Signals and Systems | 4-0-0-4 | EC201 |
| EC205 | Electromagnetic Fields | 3-0-0-3 | EC102 |
| EC206 | Electronic Devices | 4-0-0-4 | EC104 |
| EC207 | Data Structures and Algorithms | 3-0-0-3 | EC105 |
Year II - Semester III
| Course Code | Course Title | Credits (L-T- P-C) | Prerequisites |
|---|---|---|---|
| EC301 | Microprocessor Architecture | 4-0-0-4 | EC202 |
| EC302 | Embedded Systems | 4-0-0-4 | EC207 |
| EC303 | Communication Systems | 4-0-0-4 | EC204 |
| EC304 | Control Systems | 4-0-0-4 | EC201 |
| EC305 | VLSI Design | 4-0-0-4 | EC206 |
| EC306 | Computer Networks | 4-0-0-4 | EC207 |
| EC307 | Probability and Statistics | 3-0-0-3 | EC201 |
Year II - Semester IV
| Course Code | Course Title | Credits (L-T-P-C) | Prerequisites |
|---|---|---|---|
| EC401 | Digital Signal Processing | 4-0-0-4 | EC204 |
| EC402 | Image Processing | 3-0-0-3 | EC401 |
| EC403 | Wireless Communication | 4-0-0-4 | EC303 |
| EC404 | Network Security | 3-0-0-3 | EC306 |
| EC405 | RF Circuit Design | 3-0-0-3 | EC205 |
| EC406 | Microcontroller Programming | 3-0-0-3 | EC302 |
| EC407 | Introduction to Machine Learning | 3-0-0-3 | EC307 |
Year III - Semester V
| Course Code | Course Title | Credits (L-T-P-C) | Prerequisites |
|---|---|---|---|
| EC501 | Advanced Communication Systems | 4-0-0-4 | EC303 |
| EC502 | Cryptography and Network Security | 4-0-0-4 | EC404 |
| EC503 | Robotics and Automation | 4-0-0-4 | EC304 |
| EC504 | Renewable Energy Systems | 4-0-0-4 | EC203 |
| EC505 | Smart Grid Technologies | 3-0-0-3 | EC504 |
| EC506 | Internet of Things (IoT) | 3-0-0-3 | EC302 |
| EC507 | Artificial Intelligence | 4-0-0-4 | EC407 |
Year III - Semester VI
| Course Code | Course Title | Credits (L-T-P-C) | Prerequisites |
|---|---|---|---|
| EC601 | Advanced Signal Processing Techniques | 4-0-0-4 | EC401 |
| EC602 | Quantum Computing Applications | 3-0-0-3 | EC507 |
| EC603 | Satellite Communication Systems | 4-0-0-4 | EC303 |
| EC604 | Mobile Network Technologies | 3-0-0-3 | EC501 |
| EC605 | Embedded System Design | 4-0-0-4 | EC302 |
| EC606 | Nanotechnology in Electronics | 3-0-0-3 | EC206 |
| EC607 | Digital Image Analysis | 3-0-0-3 | EC402 |
Year IV - Semester VII
| Course Code | Course Title | Credits (L-T-P-C) | Prerequisites |
|---|---|---|---|
| EC701 | Capstone Project I | 6-0-0-6 | - |
| EC702 | Research Methodology | 3-0-0-3 | - |
| EC703 | Advanced Control Systems | 4-0-0-4 | EC304 |
| EC704 | Wireless Sensor Networks | 3-0-0-3 | EC501 |
| EC705 | Deep Learning Architectures | 4-0-0-4 | EC507 |
| EC706 | Advanced Microprocessor Design | 3-0-0-3 | EC301 |
| EC707 | System Integration and Testing | 4-0-0-4 | - |
Year IV - Semester VIII
| Course Code | Course Title | Credits (L-T-P-C) | Prerequisites |
|---|---|---|---|
| EC801 | Capstone Project II | 6-0-0-6 | EC701 |
| EC802 | Entrepreneurship Development | 3-0-0-3 | - |
| EC803 | Industry Internship | 6-0-0-6 | - |
| EC804 | Professional Ethics and Social Responsibility | 2-0-0-2 | - |
| EC805 | Advanced Topics in Communication Engineering | 3-0-0-3 | - |
| EC806 | Final Project Presentation | 2-0-0-2 | EC801 |
| EC807 | Research Thesis Writing | 3-0-0-3 | - |
Detailed Course Descriptions
The department offers several advanced departmental electives that provide students with specialized knowledge and skills in emerging areas of electronics and communication engineering. These courses are designed to keep pace with current industry trends and technological advancements.
Advanced Communication Systems
This course covers advanced concepts in digital modulation techniques, error correction codes, spread spectrum systems, and OFDM technologies. Students gain hands-on experience in designing and simulating communication systems using MATLAB and Simulink tools.
Cryptography and Network Security
Students learn about symmetric and asymmetric encryption algorithms, key management protocols, secure socket layer (SSL), and network security frameworks. The course includes practical sessions on implementing security measures in real-world scenarios.
Robotics and Automation
This course explores robot kinematics, control systems, sensor integration, and autonomous navigation using AI techniques. Students build working prototypes of robotic systems and develop control algorithms for various tasks.
Renewable Energy Systems
The course delves into solar panel technologies, wind energy conversion systems, energy storage solutions, and smart grid integration. Practical labs involve designing and testing renewable energy setups in controlled environments.
Smart Grid Technologies
This subject focuses on intelligent power distribution networks, demand response mechanisms, and grid stability analysis. Students learn about grid monitoring systems and develop strategies for efficient energy management.
Internet of Things (IoT)
The course introduces IoT architectures, wireless communication protocols, sensor networks, cloud computing integration, and data analytics in IoT applications. Practical labs involve building connected devices and implementing IoT platforms.
Artificial Intelligence
This elective explores neural networks, machine learning algorithms, natural language processing, and computer vision. Students implement AI models using Python and TensorFlow frameworks to solve real-world problems.
Advanced Signal Processing Techniques
The course covers advanced signal processing methods including wavelet transforms, adaptive filtering, beamforming techniques, and spectral estimation. It includes practical sessions on signal analysis tools and software development.
Quantum Computing Applications
This cutting-edge course introduces quantum computing principles, qubit manipulation, quantum algorithms, and their applications in communication and cryptography. Students explore theoretical concepts through simulations and experiments.
Satellite Communication Systems
The subject focuses on satellite orbit mechanics, satellite communication links, transponder design, and ground station operations. Practical labs involve simulating satellite communications using specialized software tools.
Project-Based Learning Philosophy
Project-based learning is a cornerstone of the program's pedagogy. The curriculum includes mandatory mini-projects in the second and third years, followed by a comprehensive final-year thesis/capstone project. These projects are designed to encourage creativity, critical thinking, and practical application of knowledge.
Mini-Projects
In the second year, students work on mini-projects that focus on applying fundamental concepts learned in core courses. Projects may involve building simple electronic circuits, developing basic communication systems, or exploring embedded software solutions. Students form teams and receive guidance from faculty mentors throughout the project lifecycle.
Final-Year Capstone Project
The final-year capstone project is a significant undertaking that allows students to synthesize their knowledge and skills in a real-world engineering context. Projects are selected based on student interests, faculty expertise, and industry relevance. Students work under the supervision of a faculty mentor and often collaborate with external partners.
Evaluation Criteria
Projects are evaluated based on technical merit, innovation, presentation quality, documentation, and teamwork. A panel of faculty members and industry experts assesses each project during a formal presentation session. The evaluation process ensures that students develop both technical and soft skills essential for professional success.