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    +91 88943 57155
    Pune, Maharashtra, India

    Duration

    4 Years

    Electrical Engineering

    Get Group Of Institution Faculty Of Technology
    Duration
    4 Years
    Electrical UG OFFLINE

    Duration

    4 Years

    Electrical Engineering

    Get Group Of Institution Faculty Of Technology
    Duration
    Apply

    Fees

    ₹8,50,000

    Placement

    94.0%

    Avg Package

    ₹6,50,000

    Highest Package

    ₹12,00,000

    OverviewAdmissionsCurriculumFeesPlacements
    4 Years
    Electrical
    UG
    OFFLINE

    Fees

    ₹8,50,000

    Placement

    94.0%

    Avg Package

    ₹6,50,000

    Highest Package

    ₹12,00,000

    Seats

    120

    Students

    320

    ApplyCollege

    Seats

    120

    Students

    320

    Curriculum

    Course Schedule Overview

    The Electrical Engineering curriculum at Get Group Of Institution Faculty Of Technology is designed to provide a robust foundation in core principles followed by advanced specializations tailored to individual interests and career goals. The program spans eight semesters, with each semester carrying a specific credit load and structured around core subjects, departmental electives, science electives, and laboratory components.

    SemesterCourse CodeCourse TitleCredit Structure (L-T-P-C)Prerequisites
    1EE101Engineering Mathematics I3-1-0-4-
    1EE102Physics for Electrical Engineering3-1-0-4-
    1EE103Basic Electrical Circuits3-1-0-4-
    1EE104Introduction to Programming2-0-2-3-
    1EE105Engineering Drawing and Graphics1-0-2-2-
    2EE201Engineering Mathematics II3-1-0-4EE101
    2EE202Electromagnetic Fields and Waves3-1-0-4EE102
    2EE203Digital Logic Design3-1-0-4EE103
    2EE204Circuit Analysis3-1-0-4EE103
    2EE205Signals and Systems3-1-0-4EE101
    3EE301Power Electronics3-1-0-4EE203, EE204
    3EE302Control Systems3-1-0-4EE205
    3EE303Communication Systems3-1-0-4EE205
    3EE304Microprocessors and Microcontrollers3-1-0-4EE203, EE204
    3EE305Electrical Machines3-1-0-4EE204
    4EE401Advanced Power Systems3-1-0-4EE305
    4EE402Renewable Energy Sources3-1-0-4EE305
    4EE403Digital Signal Processing3-1-0-4EE205
    4EE404Embedded Systems3-1-0-4EE304
    4EE405Electromagnetic Compatibility3-1-0-4EE202
    5EE501Power System Protection3-1-0-4EE401
    5EE502Industrial Automation3-1-0-4EE302
    5EE503VLSI Design3-1-0-4EE304
    5EE504Wireless Communication3-1-0-4EE303
    5EE505Antenna Theory and Design3-1-0-4EE202
    6EE601Smart Grid Technologies3-1-0-4EE501
    6EE602Robotics and Control3-1-0-4EE302
    6EE603Image Processing3-1-0-4EE403
    6EE604Machine Learning for Electrical Systems3-1-0-4EE403
    6EE605Energy Storage Technologies3-1-0-4EE402
    7EE701Thesis Research I0-0-6-6-
    7EE702Capstone Project Planning0-0-4-4-
    8EE801Thesis Research II0-0-6-6-
    8EE802Final Capstone Project0-0-8-8-

    Advanced Departmental Electives

    Departmental electives in the Electrical Engineering program offer students the opportunity to specialize in emerging fields that are increasingly relevant to industry demands. Below are detailed descriptions of some advanced elective courses:

    1. Power System Protection

    This course delves into the principles and practices of protecting power systems from faults and abnormal conditions. Students learn about relay settings, fault analysis, protective relaying schemes, and modern digital protection technologies. The course includes simulations using software like ETAP and PSCAD to model real-world scenarios.

    2. Industrial Automation

    Industrial automation explores the integration of control systems, sensors, actuators, and programmable logic controllers (PLCs) in manufacturing environments. Topics include SCADA systems, industrial networks, and process control methodologies. Students gain hands-on experience through lab sessions involving PLC programming and simulation tools like MATLAB/Simulink.

    3. VLSI Design

    VLSI (Very Large Scale Integration) design focuses on the design and implementation of integrated circuits using CAD tools such as Cadence and Synopsys. The course covers CMOS technology, logic synthesis, floorplanning, and physical design aspects. Students work on real chip designs and learn to optimize performance, power consumption, and area efficiency.

    4. Wireless Communication

    This elective introduces students to the fundamentals of wireless communication systems including modulation techniques, channel coding, multiple access schemes, and network architectures. It also covers modern standards like 5G, LTE, and Wi-Fi protocols with emphasis on practical implementation through lab exercises using software-defined radios.

    5. Antenna Theory and Design

    This course covers the theory and design of various types of antennas including dipole, patch, helical, and array antennas. Students learn about radiation patterns, impedance matching, and antenna measurement techniques. Practical sessions involve designing and testing physical antennas using simulation tools like CST Studio Suite.

    6. Smart Grid Technologies

    Smart grids integrate renewable energy sources, demand response systems, and advanced metering infrastructure to enhance grid reliability and efficiency. The course addresses topics such as distributed generation, microgrids, energy storage, and smart grid communication protocols. Students explore real-time grid management systems using simulation tools like OpenDSS.

    7. Robotics and Control

    This course integrates control theory with robotics applications, focusing on mobile robots, manipulators, and autonomous systems. Students learn about kinematics, dynamics, sensor fusion, and control algorithms such as PID, state-space models, and model predictive control. Practical sessions involve building and programming robotic platforms using ROS (Robot Operating System).

    8. Image Processing

    Image processing involves the analysis and manipulation of digital images using mathematical operations and algorithms. This course covers topics like filtering, edge detection, image segmentation, feature extraction, and object recognition. Students implement algorithms in Python using libraries such as OpenCV and scikit-image.

    9. Machine Learning for Electrical Systems

    This elective applies machine learning techniques to solve problems in electrical engineering domains including power systems, signal processing, and control systems. Topics include neural networks, deep learning, reinforcement learning, and data analytics. Students develop projects involving predictive modeling, anomaly detection, and intelligent system design.

    10. Energy Storage Technologies

    This course explores various energy storage technologies including batteries, supercapacitors, compressed air systems, and pumped hydro storage. It discusses energy storage economics, system integration challenges, and future trends in the sector. Students analyze real-world case studies and conduct simulations using tools like MATLAB/Simulink.

    Project-Based Learning Philosophy

    The Electrical Engineering program at Get Group Of Institution Faculty Of Technology emphasizes project-based learning as a cornerstone of its educational approach. This philosophy is rooted in the belief that students learn best when they engage with real-world problems and apply theoretical knowledge to practical solutions.

    Mini-projects are introduced starting from the second year, where students work in small groups on specific technical challenges related to their coursework. These projects typically span 4-6 weeks and are evaluated based on innovation, feasibility, presentation quality, and peer review. Examples include designing a simple DC motor controller, implementing a basic wireless communication system, or analyzing power consumption in residential buildings.

    The final-year thesis/capstone project is a significant component of the program's academic experience. Students select a topic aligned with their specialization track and work under the guidance of a faculty mentor for 8-10 months. The project culminates in a comprehensive report, oral presentation, and demonstration of the developed solution.

    Project selection occurs through a formal process involving proposal submission, faculty review, and final approval by the departmental committee. Students can propose their own ideas or choose from pre-defined topics provided by faculty members. The program encourages interdisciplinary collaboration with other departments such as Computer Science, Mechanical Engineering, and Materials Science to enrich project outcomes.