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Pune, Maharashtra, India

Duration

4 Years

Electrical Engineering

Pannadhay University Sikkim
Duration
4 Years
Electrical Engineering UG OFFLINE

Duration

4 Years

Electrical Engineering

Pannadhay University Sikkim
Duration
Apply

Fees

₹8,00,000

Placement

94.5%

Avg Package

₹8,50,000

Highest Package

₹25,00,000

OverviewAdmissionsCurriculumFeesPlacements
4 Years
Electrical Engineering
UG
OFFLINE

Fees

₹8,00,000

Placement

94.5%

Avg Package

₹8,50,000

Highest Package

₹25,00,000

Seats

300

Students

1,200

ApplyCollege

Seats

300

Students

1,200

Curriculum

Curriculum Overview

The Electrical Engineering program at Pannadhay University Sikkim is structured over 8 semesters, providing a comprehensive and progressive learning experience. The curriculum is carefully designed to build foundational knowledge in the first two years, followed by specialization in later semesters.

Year 1 Semesters

In the first year, students are introduced to essential mathematical and scientific concepts that form the basis of engineering education. Courses include Mathematics I & II, Physics I & II, Chemistry, English Communication, and Introduction to Engineering. These foundational courses ensure a strong academic base for advanced studies.

Year 2 Semesters

The second year builds upon this foundation with core engineering subjects such as Circuit Analysis, Electronics I & II, Signals and Systems, Computer Programming, and Basic Electrical Machines. Laboratory sessions complement these theoretical teachings, allowing students to apply concepts practically.

Year 3 Semesters

During the third year, students begin specializing in core electrical engineering topics including Power Systems, Control Systems, Digital Electronics, Electromagnetic Fields, and Communication Systems. Advanced laboratory work and small-scale projects further develop practical skills.

Year 4 Semesters

The fourth year focuses on advanced specializations and capstone preparation. Students choose from various elective tracks such as Renewable Energy, Embedded Systems, Machine Learning, and Smart Grid Technologies. Final-year thesis or capstone projects provide an opportunity to integrate all learned knowledge into real-world solutions.

Course List by Semester

Semester Course Code Full Course Title Credit Structure (L-T-P-C) Prerequisites
1 MATH101 Calculus I 3-1-0-4 None
1 MATH102 Calculus II 3-1-0-4 MATH101
1 PHYS101 Physics I 3-1-0-4 None
1 PHYS102 Physics II 3-1-0-4 PHYS101
1 CHEM101 Chemistry I 3-1-0-4 None
1 ENG101 English Communication 3-0-0-3 None
1 INTRO101 Introduction to Engineering 2-0-0-2 None
2 MATH201 Differential Equations 3-1-0-4 MATH102
2 PHYS201 Electromagnetic Fields 3-1-0-4 PHYS102
2 ELEC201 Circuit Analysis I 3-1-0-4 MATH102
2 ELEC202 Electronics I 3-1-0-4 ELEC201
2 SIGN201 Signals and Systems 3-1-0-4 MATH201
2 PROG201 Computer Programming 3-0-2-4 None
2 ELEC203 Basic Electrical Machines 3-1-0-4 ELEC201
2 LAB201 Circuit Analysis Lab 0-0-3-2 ELEC201
3 ELEC301 Power Systems I 3-1-0-4 ELEC203
3 ELEC302 Control Systems I 3-1-0-4 SIGN201
3 ELEC303 Digital Electronics 3-1-0-4 ELEC202
3 ELEC304 Electromagnetic Fields II 3-1-0-4 PHYS201
3 ELEC305 Communication Systems I 3-1-0-4 SIGN201
3 LAB301 Power Systems Lab 0-0-3-2 ELEC301
3 LAB302 Control Systems Lab 0-0-3-2 ELEC302
4 ELEC401 Power Systems II 3-1-0-4 ELEC301
4 ELEC402 Control Systems II 3-1-0-4 ELEC302
4 ELEC403 Digital Signal Processing 3-1-0-4 SIGN201
4 ELEC404 Microprocessors and Microcontrollers 3-1-0-4 ELEC303
4 ELEC405 Electromagnetic Wave Propagation 3-1-0-4 ELEC304
4 LAB401 Digital Electronics Lab 0-0-3-2 ELEC303
5 ELEC501 Renewable Energy Systems 3-1-0-4 ELEC401
5 ELEC502 Embedded Systems 3-1-0-4 ELEC404
5 ELEC503 Machine Learning Applications 3-1-0-4 ELEC403
5 ELEC504 Smart Grid Technologies 3-1-0-4 ELEC401
5 ELEC505 Antenna Design and Analysis 3-1-0-4 ELEC405
5 LAB501 Renewable Energy Lab 0-0-3-2 ELEC501
6 ELEC601 Advanced Power Electronics 3-1-0-4 ELEC401
6 ELEC602 Robotics and Automation 3-1-0-4 ELEC402
6 ELEC603 Advanced Communication Systems 3-1-0-4 ELEC405
6 ELEC604 Industrial Drives and Control 3-1-0-4 ELEC402
6 ELEC605 Energy Storage Systems 3-1-0-4 ELEC501
6 LAB601 Power Electronics Lab 0-0-3-2 ELEC601
7 ELEC701 Research Methodology 2-0-0-2 None
7 ELEC702 Advanced Project I 3-1-0-4 ELEC601
7 ELEC703 Mini Project I 0-0-6-3 None
8 ELEC801 Advanced Project II 3-1-0-4 ELEC702
8 ELEC802 Final Year Thesis 0-0-12-6 ELEC702
8 ELEC803 Mini Project II 0-0-6-3 ELEC703

Advanced Departmental Electives

Advanced departmental electives are offered in the fifth and sixth semesters to allow students to specialize in areas of interest. These courses provide in-depth knowledge and practical skills required for specific engineering applications.

Renewable Energy Systems (ELEC501)

This course introduces students to various renewable energy sources, including solar, wind, hydroelectric, and geothermal power generation systems. Students learn about system design, efficiency optimization, grid integration challenges, and environmental impacts associated with renewable technologies.

Embedded Systems (ELEC502)

This elective focuses on designing and implementing embedded systems using microcontrollers, real-time operating systems, and communication protocols. Students gain hands-on experience in hardware-software co-design, firmware development, and sensor integration.

Machine Learning Applications (ELEC503)

Students explore how machine learning algorithms can be applied to solve complex problems in electrical engineering domains such as pattern recognition, predictive maintenance, and intelligent control systems. The course includes practical implementation using Python-based libraries like TensorFlow and scikit-learn.

Smart Grid Technologies (ELEC504)

This course covers the principles of smart grid operation, including demand response systems, energy storage integration, distributed generation management, and cybersecurity in power systems. Students study advanced topics like blockchain-based energy trading platforms and microgrid coordination strategies.

Antenna Design and Analysis (ELEC505)

Focused on electromagnetic wave propagation and antenna fundamentals, this course teaches students how to design, simulate, and test different types of antennas for various applications including wireless communication, radar systems, and satellite communications.

Advanced Power Electronics (ELEC601)

This advanced course delves into high-efficiency power conversion techniques, switching loss reduction, thermal management, and modulation strategies. Students examine practical implementations in electric vehicle charging stations, solar inverters, and industrial motor drives.

Robotics and Automation (ELEC602)

Students learn about robotic system design, control algorithms, sensor integration, and automation technologies used in manufacturing and service industries. Practical sessions include building and programming robots using ROS (Robot Operating System).

Advanced Communication Systems (ELEC603)

This course explores modern communication techniques including spread spectrum modulation, multiple access protocols, error correction codes, and wireless channel modeling. Students work on designing and simulating advanced communication systems using MATLAB and Simulink.

Industrial Drives and Control (ELEC604)

Designed for students interested in industrial applications, this course covers motor drives, variable frequency drives, servo control systems, and process automation technologies. Emphasis is placed on practical design and troubleshooting techniques.

Energy Storage Systems (ELEC605)

This elective focuses on batteries, supercapacitors, fuel cells, and other energy storage technologies used in renewable energy systems and electric vehicles. Students study performance characteristics, safety considerations, and system integration strategies.

Project-Based Learning Philosophy

The Electrical Engineering program at Pannadhay University Sikkim emphasizes project-based learning as a cornerstone of engineering education. This approach fosters innovation, teamwork, and practical problem-solving skills essential for success in the professional world.

Mini-Projects Structure

Mini-projects are introduced starting from the third semester and continue through the fifth semester. Each project spans 12 weeks and involves a team of 4-6 students working under faculty supervision. Projects are selected based on real-world applications, industry trends, or research initiatives.

Students must submit project proposals outlining objectives, methodology, timeline, and expected outcomes. Midway through the project period, they present progress reports to their mentors and peers. The final deliverables include a detailed report, demonstration videos, and presentation slides.

Final Year Thesis/Capstone Project

The capstone project in the eighth semester is an intensive, year-long endeavor that integrates all learned knowledge and skills. Students choose their projects from faculty research areas or industry collaborations, ensuring relevance and impact.

Each student works closely with a designated mentor who guides them through research planning, experimental design, data analysis, and final documentation. The project culminates in a public defense session where students present their work to faculty members, industry experts, and peers.

Evaluation Criteria

Projects are evaluated based on multiple criteria including technical merit, creativity, adherence to deadlines, team collaboration, presentation quality, and innovation potential. Peer evaluations and mentor assessments contribute to the overall grade.

Project Selection Process

Students select projects from a pool of pre-approved proposals generated by faculty members or industry partners. The selection process involves submitting preferences, attending briefings, and meeting with mentors to finalize project topics.

Mentorship Opportunities

Faculty mentors play a crucial role in guiding students throughout their projects. Mentors are assigned based on expertise alignment, availability, and student interest. Regular meetings, progress tracking, and feedback sessions ensure continuous improvement and learning outcomes.