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Fees
₹1,80,000
Placement
92.0%
Avg Package
₹4,50,000
Highest Package
₹8,00,000
Fees
₹1,80,000
Placement
92.0%
Avg Package
₹4,50,000
Highest Package
₹8,00,000
Seats
90
Students
360
Seats
90
Students
360
| Semester | Course Code | Course Title | Credit Structure (L-T-P-C) | Pre-requisites |
|---|---|---|---|---|
| 1 | EE101 | Engineering Mathematics I | 3-1-0-4 | - |
| 1 | EE102 | Physics for Engineers | 3-1-0-4 | - |
| 1 | EE103 | Chemistry for Engineers | 3-1-0-4 | - |
| 1 | EE104 | Basic Electrical Engineering | 3-1-0-4 | - |
| 1 | EE105 | Computer Programming | 2-0-2-3 | - |
| 1 | EE106 | Engineering Graphics & Design | 2-0-2-3 | - |
| 2 | EE201 | Engineering Mathematics II | 3-1-0-4 | EE101 |
| 2 | EE202 | Electrical Circuits & Networks | 3-1-0-4 | EE104 |
| 2 | EE203 | Electromagnetic Fields & Waves | 3-1-0-4 | EE102 |
| 2 | EE204 | Electronic Devices & Circuits | 3-1-0-4 | EE104 |
| 2 | EE205 | Engineering Mechanics | 3-1-0-4 | - |
| 2 | EE206 | Lab: Electrical Circuits & Networks | 0-0-3-1 | - |
| 3 | EE301 | Engineering Mathematics III | 3-1-0-4 | EE201 |
| 3 | EE302 | Electrical Machines I | 3-1-0-4 | EE202 |
| 3 | EE303 | Power Electronics & Drives | 3-1-0-4 | EE204 |
| 3 | EE304 | Signals & Systems | 3-1-0-4 | EE201 |
| 3 | EE305 | Control Systems | 3-1-0-4 | EE201 |
| 3 | EE306 | Lab: Electrical Machines | 0-0-3-1 | EE202 |
| 4 | EE401 | Electrical Machines II | 3-1-0-4 | EE302 |
| 4 | EE402 | Power System Analysis | 3-1-0-4 | EE302 |
| 4 | EE403 | Digital Electronics & Microprocessors | 3-1-0-4 | EE204 |
| 4 | EE404 | Electrical Measurements & Instrumentation | 3-1-0-4 | EE202 |
| 4 | EE405 | Lab: Power System Analysis | 0-0-3-1 | EE302 |
| 5 | EE501 | Industrial Automation & PLC | 3-1-0-4 | EE305 |
| 5 | EE502 | Embedded Systems | 3-1-0-4 | EE403 |
| 5 | EE503 | Power Electronics & Applications | 3-1-0-4 | EE303 |
| 5 | EE504 | Renewable Energy Systems | 3-1-0-4 | EE302 |
| 5 | EE505 | Lab: Embedded Systems | 0-0-3-1 | EE403 |
| 6 | EE601 | Advanced Control Systems | 3-1-0-4 | EE305 |
| 6 | EE602 | Smart Grid Technologies | 3-1-0-4 | EE402 |
| 6 | EE603 | Signal Processing | 3-1-0-4 | EE304 |
| 6 | EE604 | VLSI Design | 3-1-0-4 | EE204 |
| 6 | EE605 | Lab: Smart Grid Technologies | 0-0-3-1 | EE402 |
| 7 | EE701 | Research Methodology | 3-0-0-3 | - |
| 7 | EE702 | Mini Project I | 0-0-6-3 | - |
| 8 | EE801 | Mini Project II | 0-0-6-3 | - |
| 8 | EE802 | Final Year Project / Thesis | 0-0-12-6 | - |
Advanced departmental electives are offered in the latter semesters to provide students with deeper insights into specialized areas of electrical engineering. These courses are designed to build upon foundational knowledge and prepare students for advanced research or industry roles.
This course explores the design, implementation, and optimization of renewable energy technologies. Students learn about solar photovoltaic systems, wind turbines, hydroelectric plants, and geothermal systems. The curriculum includes practical sessions on system sizing, performance modeling, and integration with existing power grids.
Smart grid technologies represent the next generation of power distribution networks that use digital communication to improve reliability, efficiency, and sustainability. This course covers topics such as demand response systems, energy storage integration, grid automation, and cybersecurity in power systems.
Embedded systems are specialized computing systems integrated into larger mechanical or electrical systems. This elective teaches students how to design, develop, and debug embedded applications using microcontrollers, real-time operating systems, and communication protocols like CAN, UART, and SPI.
Very Large Scale Integration (VLSI) design involves creating integrated circuits that contain thousands of transistors on a single chip. Students learn about logic synthesis, physical design, testing methodologies, and CAD tools used in modern semiconductor manufacturing.
This course focuses on the application of power electronics in various domains including motor drives, renewable energy systems, and industrial automation. Topics include rectifiers, inverters, DC-DC converters, and power factor correction techniques.
Advanced control systems explore modern control theory including state-space methods, optimal control, robust control, and nonlinear systems. Students apply these concepts to real-world problems in robotics, aerospace, and industrial processes.
Signal processing is crucial for analyzing and manipulating signals in various fields such as communications, audio engineering, and biomedical applications. This course covers digital signal processing techniques, filter design, spectral analysis, and MATLAB-based simulations.
This elective introduces students to Programmable Logic Controllers (PLCs) and industrial automation systems. Students learn how to program PLCs, interface with sensors and actuators, and implement control strategies in manufacturing environments.
As the world transitions towards clean energy, understanding energy storage technologies becomes essential. This course covers battery technologies, supercapacitors, compressed air energy storage, and grid-scale storage solutions.
This course delves into the principles of power system protection, including fault analysis, relay coordination, and protective device selection. Students learn how to design and implement protection schemes for different types of electrical equipment.
The department strongly advocates for project-based learning as a core component of the educational experience. Projects are designed to simulate real-world engineering challenges and encourage students to apply theoretical knowledge in practical scenarios.
Mini-projects are undertaken during the seventh semester and involve working on specific technical problems under faculty supervision. Students select a project topic from a list provided by the department or propose their own idea after consultation with mentors. These projects typically last 6-8 weeks and require students to conduct literature reviews, perform experiments, and present findings.
The final year project is a comprehensive endeavor that spans the entire eighth semester. Students work individually or in small teams on an advanced research or design problem related to their specialization. The project must include a literature review, methodology, implementation, testing, and documentation. A formal presentation is required at the end of the semester.
Projects are evaluated based on multiple criteria including technical depth, innovation, teamwork, presentation quality, and adherence to deadlines. Regular progress reports are submitted throughout the project period, and faculty members provide feedback to ensure continuous improvement. The final evaluation is conducted by a panel of experts from academia and industry.
Students are encouraged to select projects that align with their interests and career goals. Faculty mentors guide students through the selection process, ensuring that chosen topics are feasible and have sufficient research support. Projects may also be proposed by external organizations seeking collaboration opportunities with the department.
