Comprehensive Course List and Structure

Semester	Course Code	Full Course Title	Credit (L-T-P-C)	Prerequisite
Semester I	EE101	Engineering Mathematics I	3-1-0-4	-
	EE102	Physics for Electrical Engineering	3-1-0-4	-
	EE103	Chemistry for Engineers	3-1-0-4	-
	EE104	Introduction to Electrical Engineering	2-0-0-2	-
	EE105	Programming for Engineers	2-0-2-3	-
	EE106	Engineering Drawing & Graphics	1-0-2-2	-
	EE107	Workshop Practices	0-0-3-2	-
	EE108	Physical Education & Sports	0-0-0-2	-
	EE109	English Communication Skills	2-0-0-2	-
	EE110	Engineering Ethics & Professionalism	2-0-0-2	-
Semester II	EE201	Engineering Mathematics II	3-1-0-4	EE101
	EE202	Circuit Analysis	3-1-0-4	EE102
	EE203	Electromagnetic Fields	3-1-0-4	EE102
	EE204	Digital Logic Design	3-1-0-4	EE105
	EE205	Analog Electronics	3-1-0-4	EE202
	EE206	Data Structures & Algorithms	3-1-0-4	EE105
	EE207	Signals and Systems	3-1-0-4	EE201
	EE208	Electrical Measurements	2-0-2-3	EE202
	EE209	Workshop II	0-0-3-2	-
	EE210	Human Values & Professional Ethics	2-0-0-2	-
Semester III	EE301	Engineering Mathematics III	3-1-0-4	EE201
	EE302	Network Theory	3-1-0-4	EE202
	EE303	Control Systems	3-1-0-4	EE207
	EE304	Digital Signal Processing	3-1-0-4	EE207
	EE305	Microprocessors & Microcontrollers	3-1-0-4	EE204
	EE306	Electromagnetic Waves & Transmission Lines	3-1-0-4	EE203
	EE307	Probability & Statistics for Engineers	3-1-0-4	EE201
	EE308	Electrical Machines I	3-1-0-4	EE202
	EE309	Computer Organization & Architecture	3-1-0-4	EE206
	EE310	Communication Systems	3-1-0-4	EE207
Semester IV	EE401	Power System Analysis	3-1-0-4	EE302
	EE402	Electrical Machines II	3-1-0-4	EE308
	EE403	Power Electronics	3-1-0-4	EE305
	EE404	Measurement & Instrumentation	3-1-0-4	EE208
	EE405	Power System Protection	3-1-0-4	EE401
	EE406	Renewable Energy Sources	3-1-0-4	EE207
	EE407	Industrial Drives & Control	3-1-0-4	EE303
	EE408	Embedded Systems	3-1-0-4	EE305
	EE409	Advanced Control Theory	3-1-0-4	EE303
	EE410	Optimization Techniques	3-1-0-4	EE207
Semester V	EE501	Advanced Power System Protection	3-1-0-4	EE405
	EE502	Smart Grid Technologies	3-1-0-4	EE401
	EE503	Modern Control Systems	3-1-0-4	EE409
	EE504	Signal Processing Applications	3-1-0-4	EE404
	EE505	Artificial Intelligence in Electrical Engineering	3-1-0-4	EE206
	EE506	Power Quality and Harmonics	3-1-0-4	EE401
	EE507	Research Methodology	2-0-2-3	-
	EE508	Electrical Engineering Project I	0-0-6-4	-
Semester VI	EE601	Advanced Power Electronics	3-1-0-4	EE403
	EE602	Renewable Energy Systems Design	3-1-0-4	EE406
	EE603	Power System Dynamics & Stability	3-1-0-4	EE401
	EE604	Industrial Automation & PLC	3-1-0-4	EE307
	EE605	Machine Learning for Electrical Applications	3-1-0-4	EE505
	EE606	IoT & Wireless Networks	3-1-0-4	EE410
	EE607	Electrical Engineering Project II	0-0-6-4	EE508
	EE608	Electrical Engineering Lab I	0-0-3-2	-
Semester VII	EE701	Capstone Project Preparation	2-0-4-3	EE508
	EE702	Advanced Control Systems	3-1-0-4	EE503
	EE703	Energy Storage Systems	3-1-0-4	EE602
	EE704	Industrial Robotics	3-1-0-4	EE503
	EE705	Research Paper Writing & Presentation	2-0-2-3	-
	EE706	Electrical Engineering Lab II	0-0-3-2	EE608
Semester VIII	EE801	Final Year Thesis/Capstone Project	0-0-12-8	EE701
	EE802	Electrical Engineering Internship	0-0-6-4	-
	EE803	Professional Practices & Project Management	2-0-2-3	-
	EE804	Entrepreneurship in Electrical Engineering	2-0-2-3	-
	EE805	Electrical Engineering Workshop	0-0-6-4	-
	EE806	Final Project Defense & Evaluation	0-0-3-2	EE801

Detailed Departmental Elective Courses

The following are advanced departmental elective courses offered in the Electrical Engineering program, each with specific learning objectives and relevance to industry needs.

• Advanced Power Electronics: This course covers advanced topics in power electronic converters, including three-phase inverters, resonant converters, and wide-bandgap semiconductor devices. It aims to provide students with a deep understanding of modern power conversion techniques used in renewable energy systems and electric vehicles.
• Renewable Energy Systems Design: Designed to equip students with the knowledge required for designing and optimizing renewable energy systems such as solar photovoltaic arrays, wind turbines, and hydroelectric plants. Students will learn about system integration, performance evaluation, and economic analysis of different technologies.
• Power System Dynamics & Stability: Focuses on modeling and analyzing dynamic behavior of power systems under disturbances. Topics include small-signal stability analysis, transient stability, and control strategies for maintaining grid stability during contingencies.
• Industrial Automation & PLC: Introduces students to programmable logic controllers (PLCs) and industrial automation principles. The course includes hands-on training on ladder logic programming, HMI design, and integration of sensors and actuators in automated systems.
• Machine Learning for Electrical Applications: Combines machine learning techniques with electrical engineering concepts to solve complex problems in power systems, signal processing, and control theory. Students will learn how to apply neural networks, decision trees, and clustering algorithms to real-world scenarios.
• IoT & Wireless Networks: Explores the design and implementation of wireless communication protocols for IoT applications. The course covers sensor networks, wireless standards (WiFi, Bluetooth, LoRaWAN), and network security aspects relevant to smart cities and industrial IoT deployments.
• Energy Storage Systems: Focuses on the fundamentals of energy storage technologies including batteries, supercapacitors, and compressed air systems. Students will analyze their performance characteristics, design considerations, and integration strategies within power grids and electric vehicle charging infrastructure.
• Industrial Robotics: Provides an overview of robotics technology used in manufacturing and automation environments. Students will study robot kinematics, control systems, sensor integration, and programming techniques for industrial applications.
• Smart Grid Technologies: Covers the evolution of traditional power grids into smart grids using advanced communication and control technologies. The course explores topics like demand response programs, grid automation, cybersecurity in smart grids, and distributed energy resources management.
• Power Quality and Harmonics: Investigates issues related to power quality degradation caused by nonlinear loads and disturbances in electrical systems. Students will learn methods for analyzing harmonic distortion, designing filters, and implementing corrective measures.

Project-Based Learning Philosophy

The Electrical Engineering program at The Aryavart International University North Tripura places a strong emphasis on project-based learning as a core pedagogical strategy. This approach is designed to foster creativity, innovation, and practical problem-solving skills among students.

From the very first semester, students are introduced to small-scale projects that reinforce classroom concepts through hands-on experience. These mini-projects are carefully structured to allow students to explore different aspects of electrical engineering while developing essential teamwork and communication skills.

The final-year thesis/capstone project represents the culmination of the student's academic journey. Students are expected to identify a real-world problem, conduct literature review, propose a solution using appropriate tools and methodologies, implement it in a laboratory setting, and present their findings professionally.

Project selection is facilitated through faculty mentorship sessions where students can discuss their interests and capabilities with potential advisors. Each student is assigned a faculty mentor who guides them throughout the project lifecycle, providing technical support, feedback, and professional development advice.

The evaluation criteria for these projects are comprehensive and include aspects such as innovation, feasibility, technical depth, presentation quality, and impact assessment. Students are encouraged to publish their work in journals or present at conferences, thereby enhancing their visibility in the academic and industrial communities.