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

    4 Years

    Electronics

    Balwant Singh Mukhiya Bsm College Of Polytechnic
    Duration
    4 Years
    Electronics UG OFFLINE

    Duration

    4 Years

    Electronics

    Balwant Singh Mukhiya Bsm College Of Polytechnic
    Duration
    Apply

    Fees

    ₹8,50,000

    Placement

    93.0%

    Avg Package

    ₹4,80,000

    Highest Package

    ₹9,50,000

    OverviewAdmissionsCurriculumFeesPlacements
    4 Years
    Electronics
    UG
    OFFLINE

    Fees

    ₹8,50,000

    Placement

    93.0%

    Avg Package

    ₹4,80,000

    Highest Package

    ₹9,50,000

    Seats

    250

    Students

    250

    ApplyCollege

    Seats

    250

    Students

    250

    Curriculum

    Comprehensive Course Structure

    SemesterCourse CodeCourse TitleCredit Structure (L-T-P-C)Prerequisites
    1EG101Engineering Mathematics I3-1-0-4-
    1EG102Physics for Electronics3-1-0-4-
    1EG103Basic Electrical Circuits3-1-0-4-
    1EG104Introduction to Programming2-0-2-3-
    1EG105Engineering Drawing1-0-2-2-
    1EG106Workshop Practice0-0-3-1-
    2EG201Engineering Mathematics II3-1-0-4EG101
    2EG202Electromagnetic Fields3-1-0-4EG102
    2EG203Analog Electronic Circuits3-1-0-4EG103
    2EG204Digital Logic Design3-1-0-4-
    2EG205Signals and Systems3-1-0-4EG101
    2EG206Computer Organization & Architecture3-1-0-4EG204
    3EG301Microprocessor and Microcontroller3-1-0-4EG206
    3EG302Control Systems3-1-0-4EG205
    3EG303Communication Systems3-1-0-4EG205
    3EG304VLSI Design3-1-0-4EG203
    3EG305Power Electronics3-1-0-4EG203
    3EG306Embedded Systems3-1-0-4EG301
    4EG401Digital Signal Processing3-1-0-4EG205
    4EG402Computer Networks3-1-0-4EG303
    4EG403Wireless Communication3-1-0-4EG303
    4EG404Internet of Things3-1-0-4EG306
    4EG405Renewable Energy Systems3-1-0-4EG203
    4EG406Project Management3-1-0-4-
    5EG501Artificial Intelligence in Electronics3-1-0-4EG401
    5EG502Advanced Microprocessor Design3-1-0-4EG301
    5EG503Signal Processing Applications3-1-0-4EG401
    5EG504RF and Microwave Engineering3-1-0-4EG202
    5EG505Computer Vision3-1-0-4EG401
    5EG506Capstone Project I0-0-6-6-
    6EG601Advanced VLSI Design3-1-0-4EG304
    6EG602Neural Networks and Deep Learning3-1-0-4EG501
    6EG603Smart Sensors and Actuators3-1-0-4EG305
    6EG604Power System Analysis3-1-0-4EG203
    6EG605Capstone Project II0-0-6-6-
    7EG701Emerging Technologies in Electronics3-1-0-4EG501
    7EG702Quantum Computing Fundamentals3-1-0-4EG202
    7EG703Advanced Wireless Technologies3-1-0-4EG403
    7EG704Data Analytics in Electronics3-1-0-4EG401
    7EG705Entrepreneurship in Tech3-1-0-4-
    8EG801Industry Internship0-0-12-12-

    Advanced Departmental Elective Courses

    The department offers several advanced elective courses designed to provide specialized knowledge and practical skills in emerging areas of electronics. These courses are developed in consultation with industry experts and are aligned with global trends.

    One such course is 'Artificial Intelligence in Electronics,' which explores the integration of AI algorithms into electronic systems. Students learn about neural networks, deep learning frameworks, and how these technologies can be applied to improve performance in various domains like robotics, healthcare, and smart manufacturing.

    'Advanced VLSI Design' delves into advanced fabrication techniques, layout design, and optimization strategies for integrated circuits. The course includes hands-on projects using industry-standard tools such as Cadence and Synopsys, preparing students for roles in semiconductor design companies.

    'Smart Sensors and Actuators' focuses on the development and implementation of sensor technologies used in IoT applications. Students explore topics such as MEMS sensors, wireless sensor networks, and data fusion techniques to build intelligent sensing systems.

    'Power System Analysis' introduces students to the analysis and design of electrical power systems. The course covers fundamental concepts like load flow analysis, fault analysis, and stability studies, which are essential for careers in energy sector companies.

    'Neural Networks and Deep Learning' is a comprehensive course that covers theoretical foundations and practical applications of neural networks. Students gain experience in building and training deep learning models using frameworks like TensorFlow and PyTorch, enabling them to pursue roles in AI research and development.

    'Quantum Computing Fundamentals' explores the principles of quantum mechanics and their application in computing. This cutting-edge course provides insights into quantum algorithms, quantum error correction, and the potential impact of quantum computing on electronics.

    'Advanced Wireless Technologies' examines current and future wireless communication standards, including 5G, Wi-Fi 6, and satellite communications. Students study modulation techniques, antenna design, and network protocols to understand how modern wireless systems function.

    'Data Analytics in Electronics' integrates statistical methods with electronic engineering principles. Students learn how to extract meaningful insights from large datasets using tools like Python and R, preparing them for roles in data-driven electronics companies.

    'Entrepreneurship in Tech' teaches students how to identify market opportunities, develop business plans, and launch startups in the tech sector. The course includes guest lectures from successful entrepreneurs and mentorship support for developing innovative ideas.

    Project-Based Learning Philosophy

    Our department strongly believes in project-based learning as a means of fostering innovation and practical application. This philosophy is reflected throughout the curriculum, with mandatory mini-projects in early semesters and a comprehensive capstone project in the final year.

    The structure of these projects involves selecting a topic relevant to current industry needs or emerging technologies. Students form teams and work under the guidance of faculty mentors who provide expertise and support. The evaluation criteria include innovation, technical execution, presentation quality, and impact potential.

    Mini-projects in the first two years are typically focused on applying basic concepts learned in lectures to real-world scenarios. For example, students might design a simple microcontroller-based system or analyze circuit performance using simulation software.

    The final-year capstone project is a significant undertaking that allows students to demonstrate their mastery of the subject. Projects often involve collaboration with industry partners, resulting in solutions that address actual problems faced by organizations. These projects are evaluated by both faculty members and external reviewers from the industry.