Course Structure Overview
The Electrical Engineering curriculum at TRINITY INSTITUTE OF TECHNOLOGY AND RESEARCH is meticulously structured across eight semesters, ensuring a progressive and comprehensive educational journey. The program integrates foundational science subjects with advanced engineering principles and practical application through laboratory sessions and project work.
| Semester | Course Code | Course Title | Credit Structure (L-T-P-C) | Pre-requisites |
|---|---|---|---|---|
| 1 | MA101 | Calculus I | 3-1-0-4 | None |
| 1 | PH101 | Physics I | 3-1-0-4 | None |
| 1 | CH101 | Chemistry I | 3-1-0-4 | None |
| 1 | EE101 | Introduction to Electrical Engineering | 2-1-0-3 | None |
| 1 | CS101 | Programming Fundamentals | 2-0-2-3 | None |
| 2 | MA201 | Calculus II | 3-1-0-4 | MA101 |
| 2 | PH201 | Physics II | 3-1-0-4 | PH101 |
| 2 | EE201 | Circuit Analysis | 3-1-0-4 | EE101 |
| 2 | EE202 | Digital Electronics | 3-1-0-4 | EE101 |
| 2 | CS201 | Data Structures and Algorithms | 2-0-2-3 | CS101 |
| 3 | EE301 | Electrical Machines I | 3-1-0-4 | EE201 |
| 3 | EE302 | Signals and Systems | 3-1-0-4 | MA201 |
| 3 | EE303 | Control Systems | 3-1-0-4 | EE201 |
| 3 | EE304 | Electromagnetic Fields | 3-1-0-4 | PH201 |
| 3 | EE305 | Departmental Elective I | 3-1-0-4 | None |
| 4 | EE401 | Power Systems | 3-1-0-4 | EE301 |
| 4 | EE402 | Communication Systems | 3-1-0-4 | EE302 |
| 4 | EE403 | Microprocessors and Microcontrollers | 3-1-0-4 | EE202 |
| 4 | EE404 | Electronics Devices | 3-1-0-4 | EE304 |
| 4 | EE405 | Departmental Elective II | 3-1-0-4 | None |
| 5 | EE501 | Power Electronics | 3-1-0-4 | EE401 |
| 5 | EE502 | Digital Signal Processing | 3-1-0-4 | EE302 |
| 5 | EE503 | Embedded Systems | 3-1-0-4 | EE403 |
| 5 | EE504 | Departmental Elective III | 3-1-0-4 | None |
| 5 | EE505 | Project I (Mini) | 2-0-0-2 | None |
| 6 | EE601 | Renewable Energy Systems | 3-1-0-4 | EE501 |
| 6 | EE602 | Artificial Intelligence in Electrical Engineering | 3-1-0-4 | EE502 |
| 6 | EE603 | Advanced Control Systems | 3-1-0-4 | EE303 |
| 6 | EE604 | Departmental Elective IV | 3-1-0-4 | None |
| 6 | EE605 | Project II (Mini) | 2-0-0-2 | None |
| 7 | EE701 | Capstone Project | 3-0-0-3 | EE601, EE602 |
| 7 | EE702 | Advanced Topics in Electrical Engineering | 3-1-0-4 | EE504 |
| 7 | EE703 | Elective V (Industry Specialization) | 3-1-0-4 | None |
| 8 | EE801 | Final Year Thesis | 3-0-0-3 | EE701 |
| 8 | EE802 | Elective VI (Research Track) | 3-1-0-4 | None |
| 8 | EE803 | Professional Development | 2-0-0-2 | None |
Advanced Departmental Elective Courses
Departmental electives form a crucial component of the curriculum, enabling students to explore niche areas within electrical engineering. These courses are designed by leading faculty members and often incorporate current industry trends and research breakthroughs.
Power Electronics and Drives: This course explores the design and analysis of power electronic converters, including DC-DC, AC-DC, and inverters. Students gain hands-on experience with MATLAB/Simulink simulations and real-time implementation using FPGA platforms. The course emphasizes applications in renewable energy systems, electric vehicle charging infrastructure, and industrial automation.
Wireless Communication Systems: Delving into modern wireless technologies such as 5G, LTE Advanced, and satellite communications, this course covers propagation models, modulation techniques, multiple access schemes, and network protocols. Students engage in lab-based projects involving software-defined radios and channel estimation algorithms.
Biomedical Instrumentation: Bridging electrical engineering with healthcare, this course focuses on medical device design, biosensors, and signal processing for physiological data acquisition. Projects involve developing wearable health monitors and analyzing ECG signals using advanced filtering techniques.
VLSI Design: Covering the complete flow of integrated circuit design from specification to layout, this course teaches Verilog HDL, CAD tools like Cadence, and physical design concepts including floorplanning, routing, and timing closure. Students complete a full custom ASIC design project.
Smart Grid Technologies: Exploring the transformation of traditional power grids into smart systems, this course addresses topics such as demand response management, grid stability analysis, and integration of distributed energy resources. Practical components include modeling microgrids using PowerWorld Simulator and implementing control algorithms in MATLAB.
Machine Learning for Signal Processing: Integrating machine learning with signal processing, this course introduces neural networks, deep learning architectures, and optimization techniques applied to audio, image, and biomedical signals. Students implement classifiers using TensorFlow and PyTorch frameworks.
Embedded Systems Design: This course emphasizes real-time system design for embedded platforms such as ARM Cortex-M series microcontrollers. Students develop applications involving sensor interfacing, real-time operating systems (RTOS), and communication protocols like I2C, SPI, and UART.
Advanced Control Theory: Going beyond classical control methods, this course introduces robust control, optimal control, and nonlinear control strategies. Using tools like MATLAB's Control System Toolbox, students design controllers for complex dynamic systems and analyze stability conditions.
Optical Fiber Communication: Focusing on the principles of optical transmission, this course covers fiber optic components, dispersion management, and wavelength division multiplexing (WDM) techniques. Practical sessions involve designing and testing fiber optic links using OTDRs and spectrum analyzers.
Electromagnetic Compatibility: This course addresses EMI/EMC design principles, shielding techniques, and regulatory compliance standards. Students perform EMC measurements, simulate interference scenarios, and apply filtering strategies to ensure system performance under electromagnetic conditions.
Project-Based Learning Philosophy
Our department champions project-based learning as a cornerstone of the educational experience. Mini-projects are integrated throughout the curriculum to reinforce theoretical concepts through practical application. These projects typically span 4-6 weeks and involve small teams working under faculty supervision.
The final-year thesis/capstone project is a multi-month endeavor that allows students to tackle significant real-world problems. Students select projects based on their interests, faculty expertise, and industry relevance. Each student works closely with a designated mentor who provides guidance throughout the research and implementation phases.
Evaluation criteria for projects include technical depth, innovation, presentation quality, peer review scores, and final deliverables such as reports and demonstrations. Projects are often showcased at annual symposiums where students present their work to faculty, industry partners, and visiting scholars.