Course Schedule Overview
The Electrical Engineering curriculum at Get Group Of Institution Faculty Of Technology is designed to provide a robust foundation in core principles followed by advanced specializations tailored to individual interests and career goals. The program spans eight semesters, with each semester carrying a specific credit load and structured around core subjects, departmental electives, science electives, and laboratory components.
| Semester | Course Code | Course Title | Credit Structure (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 | Basic Electrical Circuits | 3-1-0-4 | - |
| 1 | EE104 | Introduction to Programming | 2-0-2-3 | - |
| 1 | EE105 | Engineering Drawing and Graphics | 1-0-2-2 | - |
| 2 | EE201 | Engineering Mathematics II | 3-1-0-4 | EE101 |
| 2 | EE202 | Electromagnetic Fields and Waves | 3-1-0-4 | EE102 |
| 2 | EE203 | Digital Logic Design | 3-1-0-4 | EE103 |
| 2 | EE204 | Circuit Analysis | 3-1-0-4 | EE103 |
| 2 | EE205 | Signals and Systems | 3-1-0-4 | EE101 |
| 3 | EE301 | Power Electronics | 3-1-0-4 | EE203, EE204 |
| 3 | EE302 | Control Systems | 3-1-0-4 | EE205 |
| 3 | EE303 | Communication Systems | 3-1-0-4 | EE205 |
| 3 | EE304 | Microprocessors and Microcontrollers | 3-1-0-4 | EE203, EE204 |
| 3 | EE305 | Electrical Machines | 3-1-0-4 | EE204 |
| 4 | EE401 | Advanced Power Systems | 3-1-0-4 | EE305 |
| 4 | EE402 | Renewable Energy Sources | 3-1-0-4 | EE305 |
| 4 | EE403 | Digital Signal Processing | 3-1-0-4 | EE205 |
| 4 | EE404 | Embedded Systems | 3-1-0-4 | EE304 |
| 4 | EE405 | Electromagnetic Compatibility | 3-1-0-4 | EE202 |
| 5 | EE501 | Power System Protection | 3-1-0-4 | EE401 |
| 5 | EE502 | Industrial Automation | 3-1-0-4 | EE302 |
| 5 | EE503 | VLSI Design | 3-1-0-4 | EE304 |
| 5 | EE504 | Wireless Communication | 3-1-0-4 | EE303 |
| 5 | EE505 | Antenna Theory and Design | 3-1-0-4 | EE202 |
| 6 | EE601 | Smart Grid Technologies | 3-1-0-4 | EE501 |
| 6 | EE602 | Robotics and Control | 3-1-0-4 | EE302 |
| 6 | EE603 | Image Processing | 3-1-0-4 | EE403 |
| 6 | EE604 | Machine Learning for Electrical Systems | 3-1-0-4 | EE403 |
| 6 | EE605 | Energy Storage Technologies | 3-1-0-4 | EE402 |
| 7 | EE701 | Thesis Research I | 0-0-6-6 | - |
| 7 | EE702 | Capstone Project Planning | 0-0-4-4 | - |
| 8 | EE801 | Thesis Research II | 0-0-6-6 | - |
| 8 | EE802 | Final Capstone Project | 0-0-8-8 | - |
Advanced Departmental Electives
Departmental electives in the Electrical Engineering program offer students the opportunity to specialize in emerging fields that are increasingly relevant to industry demands. Below are detailed descriptions of some advanced elective courses:
1. Power System Protection
This course delves into the principles and practices of protecting power systems from faults and abnormal conditions. Students learn about relay settings, fault analysis, protective relaying schemes, and modern digital protection technologies. The course includes simulations using software like ETAP and PSCAD to model real-world scenarios.
2. Industrial Automation
Industrial automation explores the integration of control systems, sensors, actuators, and programmable logic controllers (PLCs) in manufacturing environments. Topics include SCADA systems, industrial networks, and process control methodologies. Students gain hands-on experience through lab sessions involving PLC programming and simulation tools like MATLAB/Simulink.
3. VLSI Design
VLSI (Very Large Scale Integration) design focuses on the design and implementation of integrated circuits using CAD tools such as Cadence and Synopsys. The course covers CMOS technology, logic synthesis, floorplanning, and physical design aspects. Students work on real chip designs and learn to optimize performance, power consumption, and area efficiency.
4. Wireless Communication
This elective introduces students to the fundamentals of wireless communication systems including modulation techniques, channel coding, multiple access schemes, and network architectures. It also covers modern standards like 5G, LTE, and Wi-Fi protocols with emphasis on practical implementation through lab exercises using software-defined radios.
5. Antenna Theory and Design
This course covers the theory and design of various types of antennas including dipole, patch, helical, and array antennas. Students learn about radiation patterns, impedance matching, and antenna measurement techniques. Practical sessions involve designing and testing physical antennas using simulation tools like CST Studio Suite.
6. Smart Grid Technologies
Smart grids integrate renewable energy sources, demand response systems, and advanced metering infrastructure to enhance grid reliability and efficiency. The course addresses topics such as distributed generation, microgrids, energy storage, and smart grid communication protocols. Students explore real-time grid management systems using simulation tools like OpenDSS.
7. Robotics and Control
This course integrates control theory with robotics applications, focusing on mobile robots, manipulators, and autonomous systems. Students learn about kinematics, dynamics, sensor fusion, and control algorithms such as PID, state-space models, and model predictive control. Practical sessions involve building and programming robotic platforms using ROS (Robot Operating System).
8. Image Processing
Image processing involves the analysis and manipulation of digital images using mathematical operations and algorithms. This course covers topics like filtering, edge detection, image segmentation, feature extraction, and object recognition. Students implement algorithms in Python using libraries such as OpenCV and scikit-image.
9. Machine Learning for Electrical Systems
This elective applies machine learning techniques to solve problems in electrical engineering domains including power systems, signal processing, and control systems. Topics include neural networks, deep learning, reinforcement learning, and data analytics. Students develop projects involving predictive modeling, anomaly detection, and intelligent system design.
10. Energy Storage Technologies
This course explores various energy storage technologies including batteries, supercapacitors, compressed air systems, and pumped hydro storage. It discusses energy storage economics, system integration challenges, and future trends in the sector. Students analyze real-world case studies and conduct simulations using tools like MATLAB/Simulink.
Project-Based Learning Philosophy
The Electrical Engineering program at Get Group Of Institution Faculty Of Technology emphasizes project-based learning as a cornerstone of its educational approach. This philosophy is rooted in the belief that students learn best when they engage with real-world problems and apply theoretical knowledge to practical solutions.
Mini-projects are introduced starting from the second year, where students work in small groups on specific technical challenges related to their coursework. These projects typically span 4-6 weeks and are evaluated based on innovation, feasibility, presentation quality, and peer review. Examples include designing a simple DC motor controller, implementing a basic wireless communication system, or analyzing power consumption in residential buildings.
The final-year thesis/capstone project is a significant component of the program's academic experience. Students select a topic aligned with their specialization track and work under the guidance of a faculty mentor for 8-10 months. The project culminates in a comprehensive report, oral presentation, and demonstration of the developed solution.
Project selection occurs through a formal process involving proposal submission, faculty review, and final approval by the departmental committee. Students can propose their own ideas or choose from pre-defined topics provided by faculty members. The program encourages interdisciplinary collaboration with other departments such as Computer Science, Mechanical Engineering, and Materials Science to enrich project outcomes.