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Scholarships & exams

support@collegese.com
+91 88943 57155
Pune, Maharashtra, India

Duration

4 Years

Electrical Engineering

Goel Group of Institutions
Duration
4 Years
Electrical Engineering UG OFFLINE

Duration

4 Years

Electrical Engineering

Goel Group of Institutions
Duration
Apply

Fees

₹1,50,000

Placement

92.0%

Avg Package

₹7,50,000

Highest Package

₹12,00,000

OverviewAdmissionsCurriculumFeesPlacements
4 Years
Electrical Engineering
UG
OFFLINE

Fees

₹1,50,000

Placement

92.0%

Avg Package

₹7,50,000

Highest Package

₹12,00,000

Seats

150

Students

1,200

ApplyCollege

Seats

150

Students

1,200

Curriculum

Electrical Engineering Curriculum Overview

The Electrical Engineering curriculum at Goel Group of Institutions is designed to provide a balanced blend of theoretical knowledge and practical skills. The program spans eight semesters, with each semester carefully structured to build upon previous learning experiences.

SemesterCourse CodeCourse TitleCredit Structure (L-T-P-C)Pre-Requisites
1ENGL101English Communication Skills3-0-0-3-
1MATH101Mathematics I4-0-0-4-
1PHYS101Physics3-0-0-3-
1CHEM101Chemistry3-0-0-3-
1EC101Introduction to Electrical Engineering3-0-0-3-
1EG101Engineering Graphics2-0-0-2-
1COMPS101Introduction to Programming3-0-0-3-
1L101Lab: Introduction to Electrical Engineering0-0-3-1-
2MATH102Mathematics II4-0-0-4MATH101
2CIRCUIT201Circuit Analysis3-0-0-3-
2DIGITAL201Digital Logic Design3-0-0-3-
2ANALOG201Analog Electronics3-0-0-3-
2PHYS201Physics Lab0-0-3-1-
2L201Lab: Circuit Analysis0-0-3-1-
3MATH201Mathematics III4-0-0-4MATH102
3EMF201Electromagnetic Fields3-0-0-3-
3SIGNALS201Signals and Systems3-0-0-3-
3CONTROL201Control Systems3-0-0-3-
3MACHINES201Electrical Machines3-0-0-3-
3L301Lab: Electrical Machines0-0-3-1-
4MATH202Mathematics IV4-0-0-4MATH201
4POWER201Power Systems3-0-0-3-
4ELECTRO201Power Electronics3-0-0-3-
4DRIVES201Motor Drives3-0-0-3-
4L401Lab: Power Electronics0-0-3-1-
5ELEC501Electronics and Instrumentation3-0-0-3-
5COMMUNICATION501Communication Systems3-0-0-3-
5EMBEDDED501Embedded Systems3-0-0-3-
5L501Lab: Embedded Systems0-0-3-1-
6AI501Artificial Intelligence3-0-0-3-
6ML501Machine Learning3-0-0-3-
6RF501Radar and RF Systems3-0-0-3-
6L601Lab: AI & ML Projects0-0-3-1-
7RENEWABLE701Renewable Energy Systems3-0-0-3-
7GRID701Smart Grid Technologies3-0-0-3-
7ENERGY701Energy Storage Systems3-0-0-3
7L701Lab: Renewable Energy Systems0-0-3-1-
8THESIS801Final Year Project/Thesis0-0-6-6-

Advanced Departmental Electives

The department offers several advanced elective courses to deepen students' understanding of specialized areas within electrical engineering. These courses are tailored to provide depth in emerging technologies and applications.

Power Electronics and Drives

This course explores the design and implementation of power conversion systems, including DC-DC converters, inverters, and motor drives. Students gain hands-on experience with power electronics circuits and learn to optimize efficiency in energy conversion systems.

Embedded Systems Design

This elective focuses on designing embedded platforms using microcontrollers and FPGAs. Students develop projects involving real-time systems, sensor integration, and communication protocols, preparing them for careers in IoT and automation.

Artificial Intelligence and Machine Learning

This course introduces students to AI algorithms and ML techniques used in signal processing, pattern recognition, and predictive analytics. Practical applications include image classification, natural language processing, and robotics control systems.

Signal Processing Techniques

This advanced elective covers digital signal processing methods for audio, video, and biomedical signals. Students learn to implement filters, perform spectral analysis, and apply DSP techniques in practical engineering scenarios.

Radar and RF Systems

This course explores the principles of radar systems, radio frequency design, and wireless communication technologies. Students study antenna design, propagation models, and modern radar architectures used in defense and civilian applications.

Smart Grid Technologies

This course delves into smart grid concepts, including demand response systems, distributed energy resources, and grid stability management. It prepares students for careers in energy infrastructure development and policy planning.

Renewable Energy Integration

This elective examines renewable energy technologies such as solar, wind, and hydroelectric power. Students learn to integrate these sources into existing power systems and develop strategies for sustainable energy management.

Electromagnetic Compatibility and EMI

This course focuses on electromagnetic interference and compatibility issues in electronic devices. Students explore shielding techniques, filtering methods, and regulatory compliance standards for modern electronics.

Control Systems for Robotics

This elective integrates control theory with robotics applications, teaching students to design controllers for autonomous systems. Topics include PID control, state-space modeling, and motion planning algorithms.

Digital Image Processing

This course introduces digital image processing techniques used in medical imaging, computer vision, and multimedia applications. Students learn to implement filters, enhance images, and extract features using MATLAB and Python.

Project-Based Learning Philosophy

The department emphasizes project-based learning as a core component of the curriculum. From first-year mini-projects to final-year capstone projects, students are encouraged to apply theoretical knowledge to real-world problems. Projects are assigned based on student interests and faculty expertise, ensuring relevance and engagement.

Mini-projects span two semesters and involve small teams working on specific engineering challenges. These projects are evaluated through presentations, documentation, and peer reviews, fostering collaboration and communication skills.

The final-year thesis project is a comprehensive endeavor that allows students to explore advanced topics in depth. Students work closely with faculty mentors to select projects aligned with their career goals and research interests. The evaluation process includes a proposal presentation, progress reports, and a final defense, providing a platform for showcasing technical capabilities and innovation.