Comprehensive Course List Across 8 Semesters
| Semester | Course Code | Course Title | Credits (L-T-P-C) | Prerequisites |
|---|---|---|---|---|
| 1 | EE101 | Engineering Mathematics I | 3-1-0-4 | - |
| 1 | EE102 | Physics for Electrical Engineering | 3-1-0-4 | - |
| 1 | EE103 | Introduction to Programming | 2-0-2-4 | - |
| 1 | EE104 | Basic Electrical Engineering | 3-1-0-4 | - |
| 1 | EE105 | Chemistry for Engineers | 3-1-0-4 | - |
| 1 | EE106 | English Communication Skills | 2-0-0-2 | - |
| 2 | EE201 | Engineering Mathematics II | 3-1-0-4 | EE101 |
| 2 | EE202 | Electromagnetic Fields | 3-1-0-4 | EE102 |
| 2 | EE203 | Digital Logic Design | 3-1-0-4 | EE104 |
| 2 | EE204 | Circuit Analysis | 3-1-0-4 | EE104 |
| 2 | EE205 | Signals and Systems | 3-1-0-4 | EE201 |
| 2 | EE206 | Engineering Graphics | 2-0-2-4 | - |
| 3 | EE301 | Electronics Devices and Circuits | 3-1-0-4 | EE204 |
| 3 | EE302 | Power Electronics | 3-1-0-4 | EE204 |
| 3 | EE303 | Control Systems | 3-1-0-4 | EE205 |
| 3 | EE304 | Microprocessor and Microcontroller | 3-1-0-4 | EE203 |
| 3 | EE305 | Electrical Machines | 3-1-0-4 | EE204 |
| 3 | EE306 | Probability and Statistics for Engineers | 3-1-0-4 | EE201 |
| 4 | EE401 | Power Systems | 3-1-0-4 | EE305 |
| 4 | EE402 | Communication Systems | 3-1-0-4 | EE205 |
| 4 | EE403 | Embedded Systems | 3-1-0-4 | EE304 |
| 4 | EE404 | Computer Architecture | 3-1-0-4 | EE203 |
| 4 | EE405 | Advanced Control Systems | 3-1-0-4 | EE303 |
| 4 | EE406 | Digital Signal Processing | 3-1-0-4 | EE205 |
| 5 | EE501 | Renewable Energy Systems | 3-1-0-4 | EE401 |
| 5 | EE502 | Artificial Intelligence & Machine Learning | 3-1-0-4 | EE406 |
| 5 | EE503 | Smart Grid Technologies | 3-1-0-4 | EE401 |
| 5 | EE504 | VLSI Design | 3-1-0-4 | EE301 |
| 5 | EE505 | Signal Processing | 3-1-0-4 | EE406 |
| 5 | EE506 | Robotics and Automation | 3-1-0-4 | EE303 |
| 6 | EE601 | Advanced Power Electronics | 3-1-0-4 | EE302 |
| 6 | EE602 | Wireless Communication | 3-1-0-4 | EE402 |
| 6 | EE603 | Network Security | 3-1-0-4 | EE402 |
| 6 | EE604 | Internet of Things (IoT) | 3-1-0-4 | EE403 |
| 6 | EE605 | Energy Storage Systems | 3-1-0-4 | EE501 |
| 6 | EE606 | Project Management | 2-0-0-2 | - |
| 7 | EE701 | Research Methodology | 2-0-0-2 | - |
| 7 | EE702 | Advanced Embedded Systems | 3-1-0-4 | EE403 |
| 7 | EE703 | Advanced AI Applications | 3-1-0-4 | EE502 |
| 7 | EE704 | Industrial Internship | 6-0-0-6 | - |
| 8 | EE801 | Final Year Project / Thesis | 8-0-0-8 | - |
Advanced Departmental Electives
These courses are designed to deepen understanding in specialized areas of electrical engineering:
- Renewable Energy Systems: This course explores the principles and technologies behind solar, wind, hydroelectric, and geothermal power generation. Students learn about grid integration, energy storage systems, and policy frameworks supporting renewable energy adoption.
- Artificial Intelligence & Machine Learning: An intensive study of algorithms used in AI, including neural networks, deep learning, reinforcement learning, and natural language processing. The course emphasizes practical implementation using Python and TensorFlow.
- Smart Grid Technologies: Focuses on modernizing electrical grids with smart sensors, automation, and communication systems. Topics include demand response management, grid stability, and cybersecurity in power systems.
- VLSI Design: Covers the design and implementation of Very Large Scale Integration (VLSI) circuits. Students learn about logic synthesis, layout design, testing, and verification techniques using industry-standard tools like Cadence and Synopsys.
- Signal Processing: A comprehensive exploration of digital signal processing concepts including filtering, spectral analysis, and transform methods. Applications include audio and image processing, biomedical signal analysis, and telecommunications.
- Robotics and Automation: Integrates mechanical engineering with electrical systems to design autonomous robots. The course includes topics like sensor integration, control algorithms, path planning, and machine vision.
- Advanced Power Electronics: Delves into advanced topologies in power conversion such as resonant converters, multilevel inverters, and high-frequency switching circuits. Practical applications include electric vehicle charging systems and renewable energy inverters.
- Wireless Communication: Examines modern wireless communication standards including 5G, Wi-Fi, Bluetooth, and satellite communications. Students gain hands-on experience with RF design tools and protocols used in cellular networks.
- Network Security: Addresses the challenges of securing networked systems against cyber threats. Topics include cryptography, firewall implementation, intrusion detection, and secure protocol design.
- Internet of Things (IoT): Explores the architecture and applications of IoT devices in smart cities, healthcare, agriculture, and industrial automation. Students work on real-world projects involving microcontrollers, sensors, and cloud connectivity.
Project-Based Learning Philosophy
The department strongly believes in project-based learning as a core component of engineering education. Projects are integrated throughout the curriculum to reinforce theoretical concepts with practical applications:
- Mini-Projects: Conducted in second and third years, these projects allow students to apply learned concepts to real-world problems under faculty supervision.
- Final-Year Thesis/Capstone Project: Students undertake a major project that contributes to their academic profile and industry readiness. Projects are selected based on student interest, faculty expertise, and alignment with current trends in electrical engineering.
Students select their projects in consultation with faculty mentors who guide them through the research process, data collection, analysis, and documentation. Evaluation criteria include innovation, technical depth, presentation quality, and team collaboration.