Collegese

Welcome to Collegese! Sign in →

Collegese

    Search colleges and courses

    Search and navigate to colleges and courses

    Start your journey

    Ready to find your dream college?

    Join thousands of students making smarter education decisions.

    Watch How It WorksGet Started

    Discover

    Browse & filter colleges

    Compare

    Side-by-side analysis

    Explore

    Detailed course info

    Collegese

    India's education marketplace helping students discover the right colleges, compare courses, and build careers they deserve.

    © 2026 Collegese. All rights reserved. A product of Nxthub Consulting Pvt. Ltd.

    Apply

    Scholarships & exams

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

    Duration

    3 Years

    Electronics

    Gaura Devi Government Polytechnic Joshimath
    Duration
    3 Years
    Electronics DIPLOMA OFFLINE

    Duration

    3 Years

    Electronics

    Gaura Devi Government Polytechnic Joshimath
    Duration
    Apply

    Fees

    ₹75,000

    Placement

    92.0%

    Avg Package

    ₹4,00,000

    Highest Package

    ₹8,00,000

    OverviewAdmissionsCurriculumFeesPlacements
    3 Years
    Electronics
    DIPLOMA
    OFFLINE

    Fees

    ₹75,000

    Placement

    92.0%

    Avg Package

    ₹4,00,000

    Highest Package

    ₹8,00,000

    Seats

    40

    Students

    120

    ApplyCollege

    Seats

    40

    Students

    120

    Curriculum

    Electronics Curriculum Overview

    The Electronics program at Gaura Devi Government Polytechnic Joshimath is structured to provide a comprehensive education that blends theoretical knowledge with practical application. The curriculum is divided into three years, with each year consisting of two semesters, totaling eight semesters.

    SemesterCourse CodeCourse TitleCredit Structure (L-T-P-C)Pre-requisite
    IELN101Basic Electrical Engineering3-1-0-4None
    IELN102Basic Electronics3-1-0-4None
    IELN103Mathematics I3-0-0-3None
    IELN104Physics I3-0-0-3None
    IELN105Chemistry3-0-0-3None
    IELN106Engineering Graphics2-1-0-3None
    IELN107Computer Fundamentals2-1-0-3None
    IIELN201Electrical Circuits3-1-0-4ELN101
    IIELN202Digital Electronics3-1-0-4ELN102
    IIELN203Mathematics II3-0-0-3ELN103
    IIELN204Physics II3-0-0-3ELN104
    IIELN205Environmental Studies2-0-0-2None
    IIELN206Engineering Mechanics3-1-0-4None
    IIIELN301Analog Electronics3-1-0-4ELN201, ELN202
    IIIELN302Signals and Systems3-1-0-4ELN203
    IIIELN303Microprocessor Architecture3-1-0-4ELN202
    IIIELN304Mathematics III3-0-0-3ELN203
    IIIELN305Computer Organization3-1-0-4ELN206
    IIIELN306Electronics Lab I0-0-3-2ELN201, ELN202
    IVELN401Digital Communication3-1-0-4ELN302
    IVELN402Control Systems3-1-0-4ELN302
    IVELN403Power Electronics3-1-0-4ELN201
    IVELN404Mathematics IV3-0-0-3ELN304
    IVELN405Microcontroller Applications3-1-0-4ELN303
    IVELN406Electronics Lab II0-0-3-2ELN301, ELN305
    VELN501VLSI Design3-1-0-4ELN301, ELN302
    VELN502Embedded Systems3-1-0-4ELN405
    VELN503Communication Systems3-1-0-4ELN401
    VELN504Signal Processing3-1-0-4ELN302
    VELN505Renewable Energy Systems3-1-0-4ELN303, ELN304
    VELN506Electronics Lab III0-0-3-2ELN401, ELN402
    VIELN601Artificial Intelligence & Machine Learning3-1-0-4ELN504
    VIELN602Internet of Things (IoT)3-1-0-4ELN502
    VIELN603Robotics & Control Systems3-1-0-4ELN402
    VIELN604Project Work I0-0-3-4None
    VIELN605Mini Project0-0-3-2None
    VIIELN701Project Work II0-0-6-8ELN604
    VIIIELN801Capstone Project0-0-6-8ELN701

    Advanced departmental elective courses are offered to deepen student expertise in specialized areas. Here are descriptions of key courses:

    Advanced Microcontroller Applications

    This course builds upon foundational knowledge in microcontrollers and introduces students to advanced programming techniques, sensor integration, real-time operating systems, and embedded networking protocols. Students will work on projects involving smart home automation, robotics control, and industrial monitoring systems.

    Advanced Power Electronics

    Students explore advanced topics such as switching power supplies, inverters, motor drives, and grid integration of renewable energy systems. The course includes hands-on labs using simulation software like MATLAB/Simulink and hardware testing equipment.

    VLSI Design and Verification

    This course focuses on the design and verification of integrated circuits using HDLs such as Verilog and VHDL. Students learn about design flow, synthesis, simulation, and layout design. Projects involve designing simple digital blocks like adders, multiplexers, and finite state machines.

    Wireless Communication Systems

    The course covers modern wireless communication technologies including cellular networks, Wi-Fi, Bluetooth, and satellite systems. Students learn about modulation techniques, channel coding, antenna design, and network protocols. Practical sessions involve simulation of wireless channels and performance analysis.

    Image Processing and Pattern Recognition

    This elective introduces students to image processing algorithms using MATLAB and Python libraries. Topics include image enhancement, segmentation, feature extraction, and machine learning techniques for pattern recognition. Projects focus on facial recognition, object detection, and medical image analysis.

    Control Systems with MATLAB

    This course emphasizes practical implementation of control systems using MATLAB/Simulink. Students model and simulate various control systems, including PID controllers, state-space models, and transfer functions. The curriculum includes laboratory sessions on system identification and controller design.

    Robotics Engineering

    Students learn about robot kinematics, dynamics, sensors, actuators, and control algorithms. Projects involve building autonomous robots capable of navigation, object manipulation, and task completion in simulated environments.

    Smart Grid Technologies

    This course explores the integration of renewable energy sources into power grids. Students study grid stability, demand response systems, energy storage solutions, and smart metering technologies. Hands-on sessions include simulation of smart grid components and real-time monitoring systems.

    Internet of Things (IoT) Security

    The course covers security challenges in IoT devices and networks. Topics include cryptographic algorithms, secure communication protocols, authentication mechanisms, and privacy protection strategies. Students implement security solutions using hardware platforms like Raspberry Pi and Arduino.

    Advanced Signal Processing

    This course delves into advanced signal processing techniques including wavelet transforms, adaptive filtering, and spectral estimation. Students work on projects involving audio processing, biomedical signal analysis, and radar signal processing using specialized software tools.

    The program's philosophy on project-based learning is centered around fostering innovation and practical application of knowledge. Mini-projects are assigned throughout the curriculum to reinforce classroom learning and encourage creative problem-solving.

    Mini-projects typically span 1-2 months and involve small teams of 3-5 students working under faculty supervision. Each project must address a real-world challenge or demonstrate mastery of specific technical skills. Evaluation criteria include design documentation, implementation quality, presentation skills, and peer review feedback.

    The final-year thesis/capstone project is a significant component of the program. Students select a topic aligned with their interests and career goals, working closely with faculty mentors throughout the process. The project involves extensive research, system design, prototype development, testing, and documentation. It culminates in a public presentation and a detailed written report.

    Students can choose projects from a wide range of areas including embedded systems, IoT applications, renewable energy systems, AI/ML implementations, and robotics. Faculty mentors are selected based on their expertise in relevant domains to ensure proper guidance and support.