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Fees
₹6,50,000
Placement
92.0%
Avg Package
₹6,50,000
Highest Package
₹18,00,000
Fees
₹6,50,000
Placement
92.0%
Avg Package
₹6,50,000
Highest Package
₹18,00,000
Seats
240
Students
240
Seats
240
Students
240
| Semester | Course Code | Course Title | Credit Structure (L-T-P-C) | Prerequisites |
|---|---|---|---|---|
| I | EE101 | Engineering Mathematics I | 3-1-0-4 | None |
| I | EE102 | Physics for Engineers | 3-1-0-4 | None |
| I | EE103 | Introduction to Electrical Engineering | 3-0-0-3 | None |
| I | EE104 | Programming for Engineers | 2-0-2-3 | None |
| I | EE105 | Engineering Graphics and Design | 2-0-2-3 | None |
| I | EE106 | Workshop Practice | 0-0-4-2 | None |
| II | EE201 | Engineering Mathematics II | 3-1-0-4 | EE101 |
| II | EE202 | Circuit Analysis | 3-1-0-4 | EE102 |
| II | EE203 | Electromagnetics | 3-1-0-4 | EE102 |
| II | EE204 | Electronic Devices and Circuits | 3-1-0-4 | EE103 |
| II | EE205 | Signals and Systems | 3-1-0-4 | EE201 |
| II | EE206 | Digital Logic Design | 3-1-0-4 | EE204 |
| III | EE301 | Power Systems Analysis | 3-1-0-4 | EE202 |
| III | EE302 | Control Systems | 3-1-0-4 | EE205 |
| III | EE303 | Communication Systems | 3-1-0-4 | EE205 |
| III | EE304 | Microprocessors and Microcontrollers | 3-1-0-4 | EE206 |
| III | EE305 | Embedded Systems | 3-1-0-4 | EE304 |
| III | EE306 | Electromagnetic Fields and Waves | 3-1-0-4 | EE203 |
| IV | EE401 | Power Electronics | 3-1-0-4 | EE301 |
| IV | EE402 | VLSI Design | 3-1-0-4 | EE304 |
| IV | EE403 | Digital Signal Processing | 3-1-0-4 | EE205 |
| IV | EE404 | Renewable Energy Systems | 3-1-0-4 | EE301 |
| IV | EE405 | Robotics and Automation | 3-1-0-4 | EE302 |
| IV | EE406 | Advanced Control Systems | 3-1-0-4 | EE302 |
| V | EE501 | Artificial Intelligence and Machine Learning | 3-1-0-4 | EE303 |
| V | EE502 | Wireless Communication | 3-1-0-4 | EE303 |
| V | EE503 | Internet of Things (IoT) | 3-1-0-4 | EE305 |
| V | EE504 | Advanced Signal Processing | 3-1-0-4 | EE403 |
| V | EE505 | Smart Grid Technologies | 3-1-0-4 | EE301 |
| V | EE506 | Energy Storage Systems | 3-1-0-4 | EE404 |
| VI | EE601 | Research Methodology | 2-0-2-3 | EE501 |
| VI | EE602 | Advanced Topics in Electrical Engineering | 3-1-0-4 | EE504 |
| VI | EE603 | Industrial Project | 0-0-8-4 | EE402 |
| VII | EE701 | Mini Project I | 0-0-6-3 | EE501 |
| VII | EE702 | Mini Project II | 0-0-6-3 | EE502 |
| VIII | EE801 | Final Year Thesis/Capstone Project | 0-0-12-8 | EE701 |
These advanced courses offer in-depth exploration of specialized areas within electrical engineering, enabling students to gain expertise tailored to their interests and career goals.
This course introduces students to the fundamental concepts of artificial intelligence, including neural networks, deep learning architectures, computer vision, and natural language processing. Through hands-on labs and projects, students will implement AI models using frameworks like TensorFlow and PyTorch.
Focusing on modern wireless communication techniques, this course covers cellular networks, satellite communications, and emerging technologies such as 5G and beyond. Students will explore modulation schemes, error correction codes, and network protocols in practical scenarios.
This elective explores the architecture, protocols, and applications of IoT systems. Students will learn about sensor networks, embedded programming, cloud integration, and security aspects of connected devices. Practical implementation includes building IoT-based solutions using platforms like Arduino and Raspberry Pi.
This course builds upon foundational signal processing knowledge by introducing advanced techniques such as adaptive filtering, wavelet transforms, spectral estimation, and multirate systems. Students will apply these methods to real-world signals from biomedical, audio, and radar applications.
Students will examine the evolution of power grids into smart networks capable of integrating renewable sources, managing demand response, and enhancing reliability. Topics include grid stability analysis, smart metering, energy management systems, and regulatory frameworks.
This course focuses on the design and implementation of energy storage technologies for applications in transportation, utilities, and distributed generation. Students will study battery chemistry, supercapacitors, flywheels, and emerging storage solutions.
At Institute Of Advanced Research Gandhinagar, project-based learning is central to the educational experience. It encourages students to apply theoretical knowledge in real-world settings, fostering creativity, collaboration, and critical thinking skills.
Students undertake two mini projects during their final two semesters, each lasting approximately 12 weeks. These projects are selected based on student interest and faculty expertise. Students receive guidance from assigned mentors throughout the project lifecycle, from initial idea development to final presentation.
The capstone project is a comprehensive research endeavor that integrates knowledge from all previous semesters. Students propose projects aligned with their specialization, conduct independent research, and present findings in a formal thesis and defense.
Projects are evaluated based on technical depth, innovation, presentation quality, and team collaboration. Regular progress reports, milestone reviews, and final presentations ensure continuous improvement and accountability.
