Comprehensive Course Structure
| Semester | Course Code | Course Title | Credit (L-T-P-C) | Prerequisites |
|---|---|---|---|---|
| 1 | ENG101 | English for Technical Communication | 2-0-0-2 | - |
| 1 | MAT101 | Calculus I | 4-0-0-4 | - |
| 1 | MAT102 | Linear Algebra and Differential Equations | 3-0-0-3 | MAT101 |
| 1 | PHY101 | Physics for Engineers | 4-0-0-4 | - |
| 1 | CHE101 | Chemistry | 3-0-0-3 | - |
| 1 | ECE101 | Introduction to Electrical Engineering | 2-0-0-2 | - |
| 1 | CSE101 | Programming for Engineers | 2-0-2-3 | - |
| 2 | MAT201 | Calculus II | 4-0-0-4 | MAT101 |
| 2 | MAT202 | Probability and Statistics | 3-0-0-3 | MAT101 |
| 2 | PHY201 | Electromagnetic Fields | 4-0-0-4 | PHY101 |
| 2 | ECE201 | Circuit Analysis | 3-0-0-3 | ECE101 |
| 2 | ECE202 | Electromagnetic Waves and Transmission Lines | 3-0-0-3 | PHY201 |
| 2 | CSE201 | Data Structures and Algorithms | 2-0-2-3 | CSE101 |
| 3 | ECE301 | Signals and Systems | 3-0-0-3 | MAT201, ECE201 |
| 3 | ECE302 | Electronics Devices and Circuits | 3-0-0-3 | ECE201 |
| 3 | ECE303 | Power Systems Fundamentals | 3-0-0-3 | ECE201 |
| 3 | ECE304 | Digital Logic Design | 3-0-0-3 | CSE201 |
| 3 | ECE305 | Control Systems | 3-0-0-3 | MAT202, ECE301 |
| 4 | ECE401 | Power Electronics | 3-0-0-3 | ECE302 |
| 4 | ECE402 | Communication Systems | 3-0-0-3 | ECE301 |
| 4 | ECE403 | Embedded Systems | 3-0-0-3 | CSE201, ECE304 |
| 4 | ECE404 | Microprocessor and Microcontroller Applications | 3-0-0-3 | ECE304 |
| 4 | ECE405 | Renewable Energy Systems | 3-0-0-3 | ECE303 |
| 5 | ECE501 | Advanced Power Electronics | 3-0-0-3 | ECE401 |
| 5 | ECE502 | Power System Protection | 3-0-0-3 | ECE303 |
| 5 | ECE503 | Signal Processing Techniques | 3-0-0-3 | ECE301 |
| 5 | ECE504 | Control System Design | 3-0-0-3 | ECE305 |
| 5 | ECE505 | Industrial Automation and Robotics | 3-0-0-3 | ECE305 |
| 6 | ECE601 | Advanced Control Systems | 3-0-0-3 | ECE504 |
| 6 | ECE602 | Wireless Communication | 3-0-0-3 | ECE402 |
| 6 | ECE603 | Energy Storage Technologies | 3-0-0-3 | ECE501 |
| 6 | ECE604 | Smart Grid Technologies | 3-0-0-3 | ECE303 |
| 7 | ECE701 | Capstone Project I | 2-0-4-5 | - |
| 7 | ECE702 | Research Methodology | 2-0-0-2 | - |
| 7 | ECE703 | Advanced VLSI Design | 3-0-0-3 | ECE304 |
| 8 | ECE801 | Capstone Project II | 2-0-4-5 | - |
| 8 | ECE802 | Elective Departmental Course 1 | 3-0-0-3 | - |
| 8 | ECE803 | Elective Departmental Course 2 | 3-0-0-3 | - |
Advanced Departmental Elective Courses
These advanced courses are designed to provide in-depth knowledge and specialized skills required for cutting-edge applications in electrical engineering.
Advanced Power Electronics
This course delves into the principles of modern power electronics converters, including DC-DC, AC-DC, and DC-AC conversion techniques. Students explore advanced topics such as resonant converters, soft-switching techniques, and wide bandgap semiconductor applications. The course emphasizes practical implementation through laboratory sessions using IGBTs, MOSFETs, and SiC devices.
Power System Protection
Students learn about various protection schemes used in power systems, including relaying principles, fault analysis, and protective device coordination. The course covers both traditional and modern protection technologies, such as distance relays, pilot protection systems, and digital relays. Laboratory work includes simulation of protection algorithms using MATLAB/Simulink.
Signal Processing Techniques
This course explores advanced signal processing methods including filter design, spectral estimation, and adaptive filtering. Students gain hands-on experience with digital signal processors (DSPs) and software tools like MATLAB and Python for implementing real-time signal processing algorithms.
Control System Design
The focus of this course is on designing control systems for complex industrial processes. Topics include state-space methods, PID controller tuning, robust control design, and optimal control theory. Practical implementation involves designing controllers using Simulink and testing them on physical systems.
Industrial Automation and Robotics
This elective provides an overview of automation technologies used in manufacturing environments. Students study programmable logic controllers (PLCs), SCADA systems, sensor integration, and robotic motion control. The course includes lab sessions with industrial robots and simulation software like Siemens PLCs and ROS.
Advanced Control Systems
This course introduces students to advanced control methodologies such as nonlinear control, model predictive control (MPC), and fuzzy logic control. Emphasis is placed on applying these techniques to real-world systems including autonomous vehicles and industrial processes. Students engage in project-based learning involving system modeling and simulation.
Wireless Communication
This course covers wireless communication fundamentals including modulation schemes, channel coding, multiple access protocols, and mobile network architectures. Practical components involve building wireless communication modules using software-defined radios (SDRs) and MATLAB simulations.
Energy Storage Technologies
Students explore various energy storage technologies including batteries, supercapacitors, flywheels, and pumped hydro systems. The course discusses charging strategies, efficiency optimization, and integration with renewable energy sources. Laboratory sessions include testing battery performance under different conditions.
Smart Grid Technologies
This course examines smart grid concepts including demand response, distributed generation, grid stability, and cyber security. Students analyze smart grid architectures using simulation tools like PowerWorld and PSCAD/EMTDC, focusing on integrating renewable energy sources into existing power grids.
Advanced VLSI Design
This course provides an in-depth look at very large-scale integration (VLSI) design methodologies. Topics include logic synthesis, layout design, timing closure, and testability. Students utilize industry-standard tools like Cadence and Synopsys for designing digital circuits.
Project-Based Learning Philosophy
The Electrical Engineering department at Maya Institute Of Technology And Management believes in experiential learning as a cornerstone of education. Our project-based approach ensures that students not only understand theoretical concepts but also apply them practically in solving real-world problems.
Mini-projects are introduced starting from the second year, allowing students to explore specific topics in depth and develop hands-on skills. These projects typically involve designing and implementing small-scale systems such as LED controllers, sensor networks, or basic power electronics circuits. Each project is mentored by faculty members with industry experience, ensuring relevance and quality.
The final-year thesis/capstone project is a significant component of the program. Students work individually or in teams on an advanced engineering problem selected based on their interests and academic strengths. The project must demonstrate innovation, technical depth, and practical applicability. Faculty mentors guide students throughout the process, providing feedback on methodology, analysis, and presentation skills.
Project selection is done through a formal proposal process where students submit ideas aligned with faculty research areas or industry trends. This ensures that projects are meaningful, challenging, and relevant to current technological needs. The evaluation criteria include technical feasibility, innovation level, project documentation, and oral presentation quality.