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Fees
₹2,50,000
Placement
95.0%
Avg Package
₹6,50,000
Highest Package
₹15,00,000
Fees
₹2,50,000
Placement
95.0%
Avg Package
₹6,50,000
Highest Package
₹15,00,000
Seats
180
Students
1,800
Seats
180
Students
1,800
The Electrical Engineering program at Maharishi Mahesh Yogi Vedic Vishwavidyalaya Katni is designed to provide a comprehensive education that balances theoretical knowledge with practical application. The curriculum spans eight semesters, with each semester carrying a specific set of courses tailored to build upon previously acquired skills and knowledge.
| Semester | Course Code | Course Title | Credit Structure (L-T-P-C) | Prerequisites |
|---|---|---|---|---|
| Semester I | PHYS101 | Physics for Engineers | 3-1-0-4 | - |
| MATH101 | Calculus and Analytical Geometry | 3-1-0-4 | - | |
| CHM101 | Chemistry for Engineers | 3-1-0-4 | - | |
| ENGG101 | Engineering Drawing and Graphics | 2-0-2-3 | - | |
| ENGG102 | Introduction to Engineering | 2-0-0-2 | - | |
| COM101 | Communication Skills | 2-0-0-2 | - | |
| CS101 | Programming in C | 3-0-2-4 | - | |
| PHY101 | Physics Laboratory | 0-0-3-2 | - | |
| MAT101 | Mathematics Laboratory | 0-0-3-2 | - | |
| CHM101 | Chemistry Laboratory | 0-0-3-2 | - | |
| ENG101 | Engineering Workshop | 0-0-6-3 | - | |
| ENG102 | Introduction to Engineering Project | 0-0-4-2 | - | |
| Semester II | MATH201 | Linear Algebra and Differential Equations | 3-1-0-4 | MATH101 |
| PHYS201 | Electromagnetic Fields and Waves | 3-1-0-4 | PHYS101 | |
| ENGG201 | Basic Electrical Engineering | 3-1-0-4 | - | |
| ENGG202 | Electronic Devices and Circuits | 3-1-0-4 | - | |
| COM201 | English for Engineers | 2-0-0-2 | - | |
| CS201 | Data Structures and Algorithms | 3-0-2-4 | CS101 | |
| MATH201 | Linear Algebra Laboratory | 0-0-3-2 | - | |
| PHYS201 | Electromagnetic Fields Laboratory | 0-0-3-2 | - | |
| ENGG201 | Basic Electrical Engineering Laboratory | 0-0-3-2 | - | |
| ENGG202 | Electronic Devices and Circuits Laboratory | 0-0-3-2 | - | |
| CS201 | Data Structures Laboratory | 0-0-3-2 | - | |
| ENGG203 | Engineering Ethics and Professionalism | 2-0-0-2 | - | |
| Semester III | MATH301 | Numerical Methods and Optimization | 3-1-0-4 | MATH201 |
| ENGG301 | Circuit Analysis | 3-1-0-4 | ENGG201 | |
| ENGG302 | Signals and Systems | 3-1-0-4 | MATH201, ENGG202 | |
| ENGG303 | Electromagnetic Field Theory | 3-1-0-4 | PHYS201 | |
| ENGG304 | Power Electronics | 3-1-0-4 | ENGG202 | |
| CS301 | Computer Organization and Architecture | 3-1-0-4 | CS201 | |
| MATH301 | Numerical Methods Laboratory | 0-0-3-2 | - | |
| ENGG301 | Circuit Analysis Laboratory | 0-0-3-2 | - | |
| ENGG302 | Signals and Systems Laboratory | 0-0-3-2 | - | |
| ENGG303 | Electromagnetic Field Theory Laboratory | 0-0-3-2 | - | |
| ENGG304 | Power Electronics Laboratory | 0-0-3-2 | - | |
| ENGG305 | Mini Project I | 0-0-6-3 | - | |
| Semester IV | MATH401 | Probability and Statistics | 3-1-0-4 | MATH201 |
| ENGG401 | Control Systems | 3-1-0-4 | ENGG301, ENGG302 | |
| ENGG402 | Digital Logic Design | 3-1-0-4 | ENGG202 | |
| ENGG403 | Microprocessors and Microcontrollers | 3-1-0-4 | ENGG202, CS301 | |
| ENGG404 | Communication Systems | 3-1-0-4 | ENGG302 | |
| ENGG405 | Electrical Machines | 3-1-0-4 | ENGG301 | |
| MATH401 | Probability and Statistics Laboratory | 0-0-3-2 | - | |
| ENGG401 | Control Systems Laboratory | 0-0-3-2 | - | |
| ENGG402 | Digital Logic Design Laboratory | 0-0-3-2 | - | |
| ENGG403 | Microprocessors and Microcontrollers Laboratory | 0-0-3-2 | - | |
| ENGG404 | Communication Systems Laboratory | 0-0-3-2 | - | |
| ENGG405 | Electrical Machines Laboratory | 0-0-3-2 | - | |
| Semester V | ENGG501 | Power Systems Analysis | 3-1-0-4 | ENGG301, ENGG305 |
| ENGG502 | Renewable Energy Sources | 3-1-0-4 | ENGG301 | |
| ENGG503 | Embedded Systems | 3-1-0-4 | ENGG403, CS301 | |
| ENGG504 | Advanced Control Systems | 3-1-0-4 | ENGG401 | |
| ENGG505 | Signal Processing | 3-1-0-4 | ENGG302 | |
| ENGG506 | Power Electronics and Drives | 3-1-0-4 | ENGG304, ENGG405 | |
| ENGG507 | Mini Project II | 0-0-6-3 | - | |
| ENGG508 | Advanced Electrical Machines | 3-1-0-4 | ENGG405 | |
| ENGG509 | Electronics and Instrumentation | 3-1-0-4 | ENGG202 | |
| ENGG510 | Project Management and Entrepreneurship | 2-0-0-2 | - | |
| ENGG511 | Research Methodology | 2-0-0-2 | - | |
| ENGG512 | Professional Communication and Ethics | 2-0-0-2 | - | |
| Semester VI | ENGG601 | Smart Grid Technologies | 3-1-0-4 | ENGG501 |
| ENGG602 | Artificial Intelligence in Electrical Engineering | 3-1-0-4 | ENGG505 | |
| ENGG603 | Industrial Automation and Control | 3-1-0-4 | ENGG401, ENGG504 | |
| ENGG604 | Communication Networks | 3-1-0-4 | ENGG404 | |
| ENGG605 | Power System Protection | 3-1-0-4 | ENGG501 | |
| ENGG606 | Advanced Power Electronics | 3-1-0-4 | ENGG304, ENGG506 | |
| ENGG607 | Mini Project III | 0-0-6-3 | - | |
| ENGG608 | Research and Development in Power Systems | 3-1-0-4 | ENGG501 | |
| ENGG609 | Energy Storage Technologies | 3-1-0-4 | ENGG502 | |
| ENGG610 | Renewable Energy Integration | 3-1-0-4 | ENGG502 | |
| ENGG611 | Digital Image Processing | 3-1-0-4 | ENGG505 | |
| ENGG612 | Capstone Project Preparation | 0-0-6-3 | - | |
| Semester VII | ENGG701 | Advanced Embedded Systems Design | 3-1-0-4 | ENGG503 |
| ENGG702 | Advanced Control System Design | 3-1-0-4 | ENGG504, ENGG603 | |
| ENGG703 | Power System Planning and Operation | 3-1-0-4 | ENGG501 | |
| ENGG704 | Signal Processing Applications | 3-1-0-4 | ENGG505 | |
| ENGG705 | Wireless Power Transmission | 3-1-0-4 | ENGG303, ENGG404 | |
| ENGG706 | Renewable Energy Systems Engineering | 3-1-0-4 | ENGG502, ENGG609 | |
| ENGG707 | Research Internship | 0-0-12-6 | - | |
| ENGG708 | Capstone Project I | 0-0-12-6 | - | |
| ENGG709 | Advanced Power Electronics Applications | 3-1-0-4 | ENGG506, ENGG606 | |
| ENGG710 | Industrial Visits and Seminars | 2-0-0-2 | - | |
| ENGG711 | Professional Development Workshop | 2-0-0-2 | - | |
| ENGG712 | Final Thesis Proposal | 0-0-6-3 | - | |
| Semester VIII | ENGG801 | Advanced Renewable Energy Systems | 3-1-0-4 | ENGG706 |
| ENGG802 | Smart Grid Integration | 3-1-0-4 | ENGG601, ENGG703 | |
| ENGG803 | Artificial Intelligence in Control Systems | 3-1-0-4 | ENGG602, ENGG702 | |
| ENGG804 | Capstone Project II | 0-0-12-6 | - | |
| ENGG805 | Research and Development in Electrical Engineering | 3-1-0-4 | ENGG708 | |
| ENGG806 | Final Thesis Defense | 0-0-12-6 | - | |
| ENGG807 | Entrepreneurship and Innovation | 2-0-0-2 | - | |
| ENGG808 | Final Industry Project | 0-0-12-6 | - | |
| ENGG809 | Graduation Ceremony and Alumni Meet | 2-0-0-2 | - | |
| ENGG810 | Internship Completion Report | 0-0-6-3 | - | |
| ENGG811 | Final Project Presentation | 0-0-6-3 | - | |
| ENGG812 | Placement Preparation Workshop | 2-0-0-2 | - |
The department offers a rich variety of advanced elective courses designed to deepen students' understanding and provide specialized skills in emerging areas. These courses are taught by faculty members who are experts in their respective fields and have extensive industry experience.
This course delves into the intricacies of power system planning, including load forecasting, generation scheduling, transmission expansion planning, and economic dispatch. Students learn about operational constraints, reliability analysis, and optimization techniques used in modern power systems. The course includes practical sessions using industry-standard software tools such as PowerWorld Simulator and ETAP.
Building upon foundational control theory, this course covers advanced topics including state-space representation, robust control, optimal control, and nonlinear control systems. Students study design methodologies for complex systems with multiple inputs and outputs, and learn to implement controllers using MATLAB/Simulink and other simulation environments.
This elective explores practical applications of signal processing techniques in areas such as audio and video compression, biomedical signal analysis, radar systems, and speech recognition. Students work on real-world projects involving data acquisition, filtering, spectral analysis, and pattern recognition using tools like MATLAB, Python, and specialized libraries.
This course focuses on the principles and applications of wireless power transfer technologies, including inductive coupling, resonant power transfer, and electromagnetic wave propagation. Students study efficiency optimization techniques, safety standards, and emerging applications in electric vehicles, medical devices, and IoT networks.
This interdisciplinary course integrates AI concepts with electrical engineering principles, covering machine learning algorithms, neural networks, deep learning architectures, and their implementation in power systems, signal processing, and control systems. Students gain hands-on experience through projects involving predictive modeling, anomaly detection, and automated decision-making systems.
This course addresses the challenges and opportunities associated with integrating renewable energy sources into existing power grids. Topics include grid stability, demand response management, energy storage systems, microgrids, and distributed generation. Students engage in case studies and simulations to understand real-world scenarios and policy implications.
This advanced course explores cutting-edge technologies in renewable energy, including floating solar panels, offshore wind turbines, perovskite solar cells, and advanced battery storage solutions. Students study the technical aspects, economic viability, and environmental impact of these systems while working on research-oriented projects.
This course focuses on automation technologies used in industrial environments, including programmable logic controllers (PLCs), human-machine interfaces (HMIs), sensor networks, and distributed control systems. Students gain practical experience through laboratory exercises and project-based learning involving real-world automation scenarios.
This elective provides an in-depth look at embedded system architecture, design methodologies, and implementation techniques. Students learn to develop firmware for microcontrollers, interface with sensors and actuators, and create real-time applications using programming languages such as C/C++ and assembly. The course includes hands-on labs involving ARM Cortex-M processors and Arduino platforms.
This course examines various energy storage technologies including lithium-ion batteries, supercapacitors, compressed air systems, pumped hydro storage, and hydrogen fuel cells. Students study the physics, chemistry, economics, and applications of each technology, with special emphasis on integration into power grids and electric vehicle charging infrastructure.
This mandatory course provides students with an opportunity to work on research projects under faculty supervision. It involves literature review, experimental design, data collection, analysis, and report writing. Students gain exposure to current research trends and contribute to ongoing projects within the department or collaborating institutions.
Our department strongly believes in project-based learning as a means of fostering innovation, creativity, and practical skills among students. The curriculum includes several mini-projects and a final-year thesis/capstone project that allow students to apply theoretical knowledge to real-world problems.
Mini projects are introduced starting from the third semester and continue through the sixth semester. Each project lasts for approximately two months and involves working in small teams of 3-5 students. Projects are selected based on student interests, faculty availability, and industry relevance. The evaluation criteria include project proposal, progress reports, final presentation, and documentation.
The final-year thesis is a significant component of the program, typically lasting for eight months. Students work closely with a faculty advisor to select a topic, conduct research, and develop a comprehensive solution or innovation. The project must demonstrate originality, technical depth, and practical applicability. Students are required to present their findings at departmental symposiums and submit a detailed report.
Projects are selected through a combination of faculty recommendations, student interest, and industry needs. Students participate in project proposal presentations where they pitch ideas to faculty members who then assign mentors based on expertise alignment. The selection process ensures that students work on projects that challenge them intellectually while providing meaningful learning experiences.
