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

    Duration

    4 Years

    Electronics

    Government Polytechnic Satpuli
    Duration
    4 Years
    Electronics UG OFFLINE

    Duration

    4 Years

    Electronics

    Government Polytechnic Satpuli
    Duration
    Apply

    Fees

    ₹1,20,000

    Placement

    94.0%

    Avg Package

    ₹6,20,000

    Highest Package

    ₹9,50,000

    OverviewAdmissionsCurriculumFeesPlacements
    4 Years
    Electronics
    UG
    OFFLINE

    Fees

    ₹1,20,000

    Placement

    94.0%

    Avg Package

    ₹6,20,000

    Highest Package

    ₹9,50,000

    Seats

    120

    Students

    180

    ApplyCollege

    Seats

    120

    Students

    180

    Curriculum

    Course Structure Overview

    The Electronics Engineering program at Govt Polytechnic Satpuli is structured into 8 semesters over four years. The curriculum is carefully designed to build upon foundational knowledge and progressively introduce advanced concepts. Students are exposed to both theoretical principles and practical applications through lectures, tutorials, laboratory sessions, and hands-on projects.

    Year 1 Semesters

    Semester Course Code Course Title Credit (L-T-P-C) Prerequisites
    I EG101 Engineering Graphics & Design 3-0-0-3 -
    I MAT101 Applied Mathematics I 3-1-0-4 -
    I PHY101 Physics for Electronics 3-1-0-4 -
    I CHE101 Chemistry for Engineers 3-1-0-4 -
    I EC101 Introduction to Electronics 3-1-0-4 -
    I ECE101 Basics of Electrical Circuits 3-1-0-4 -
    I L101 Basic Electronics Lab 0-0-3-2 -
    I L102 Physics Lab 0-0-3-2 -
    II MAT102 Applied Mathematics II 3-1-0-4 MAT101
    II PHY102 Modern Physics & Optics 3-1-0-4 PHY101
    II CHE102 Chemistry of Materials 3-1-0-4 CHE101
    II EC201 Electrical Circuits & Networks 3-1-0-4 EC101
    II ECE201 Digital Logic & Design 3-1-0-4 ECE101
    II L201 Circuit Analysis Lab 0-0-3-2 ECE101
    II L202 Digital Logic Lab 0-0-3-2 ECE101

    Year 2 Semesters

    Semester Course Code Course Title Credit (L-T-P-C) Prerequisites
    III MAT201 Applied Mathematics III 3-1-0-4 MAT102
    III EC301 Analog Electronics I 3-1-0-4 EC201
    III ECE301 Microprocessors & Microcontrollers 3-1-0-4 ECE201
    III EC302 Signals & Systems 3-1-0-4 MAT201
    III EC303 Electromagnetic Fields & Waves 3-1-0-4 PHY102
    III L301 Analog Electronics Lab 0-0-3-2 EC301
    III L302 Microprocessor Lab 0-0-3-2 ECE301
    IV MAT202 Applied Mathematics IV 3-1-0-4 MAT201
    IV EC401 Analog Electronics II 3-1-0-4 EC301
    IV ECE401 Digital Signal Processing 3-1-0-4 EC302
    IV EC402 Control Systems 3-1-0-4 EC302
    IV EC403 Electronics Devices & Circuits 3-1-0-4 EC303
    IV L401 DSP Lab 0-0-3-2 ECE401
    IV L402 Control Systems Lab 0-0-3-2 EC402

    Year 3 Semesters

    Semester Course Code Course Title Credit (L-T-P-C) Prerequisites
    V EC501 Power Electronics 3-1-0-4 EC401
    V ECE501 Communication Systems 3-1-0-4 EC302
    V EC502 Microelectronic Circuits 3-1-0-4 EC403
    V EC503 Embedded Systems 3-1-0-4 ECE301
    V EC504 Antennas & Wave Propagation 3-1-0-4 EC303
    V L501 Power Electronics Lab 0-0-3-2 EC501
    V L502 Communication Systems Lab 0-0-3-2 ECE501
    VI EC601 VLSI Design 3-1-0-4 EC502
    VI ECE601 Wireless Networks 3-1-0-4 ECE501
    VI EC602 Digital Image Processing 3-1-0-4 EC401
    VI EC603 Robotics & Control 3-1-0-4 EC402
    VI L601 VLSI Lab 0-0-3-2 EC601
    VI L602 Robotics Lab 0-0-3-2 EC603

    Year 4 Semesters

    Semester Course Code Course Title Credit (L-T-P-C) Prerequisites
    VII EC701 Advanced Embedded Systems 3-1-0-4 EC503
    VII ECE701 Machine Learning for Electronics 3-1-0-4 EC401
    VII EC702 Internet of Things (IoT) 3-1-0-4 EC503
    VII EC703 Signal Processing Applications 3-1-0-4 EC401
    VII EC704 Capstone Project I 0-0-6-6 EC603
    VIII EC801 Advanced VLSI Design 3-1-0-4 EC601
    VIII ECE801 Artificial Intelligence in Electronics 3-1-0-4 ECE701
    VIII EC802 Capstone Project II 0-0-6-6 EC704
    VIII EC803 Research Methodology 3-1-0-4 -

    Advanced Departmental Electives

    Departmental electives in the Electronics program are designed to give students exposure to cutting-edge technologies and specialized domains. These courses are taught by faculty members who are experts in their fields and have extensive industry experience.

    Elective Course Descriptions

    • Machine Learning for Electronics: This course introduces students to machine learning algorithms and their applications in electronics. It covers supervised and unsupervised learning techniques, neural networks, deep learning frameworks like TensorFlow and PyTorch, and how these are used in signal processing, sensor data analysis, and predictive maintenance systems.
    • Internet of Things (IoT): The IoT course explores the architecture, protocols, and applications of interconnected devices. Students learn about wireless communication, embedded systems, cloud integration, security considerations, and real-time data analytics in IoT ecosystems.
    • Advanced VLSI Design: This elective focuses on advanced topics in Very Large Scale Integration (VLSI) design including ASIC design flow, synthesis, verification, and testing. Students work with industry-standard tools like Cadence and Mentor Graphics to design complex integrated circuits.
    • Signal Processing Applications: Students study practical applications of digital signal processing such as audio processing, image enhancement, biomedical signal analysis, and speech recognition systems. Hands-on labs involve MATLAB-based simulations and real-time implementation using DSP processors.
    • Power Electronics and Drives: This course covers power electronic converters, motor drives, renewable energy integration, and smart grid technologies. Students gain hands-on experience in designing and simulating power conversion circuits for various applications.
    • Wireless Communication Systems: The course delves into modern wireless communication standards including 5G, LTE, Wi-Fi, Bluetooth, and satellite communications. It includes both theoretical aspects and practical implementation of modulation schemes, error correction techniques, and network optimization strategies.
    • Robotics and Automation: This elective teaches the principles of robotics including kinematics, dynamics, control systems, sensor integration, and autonomous navigation. Students build and program robots using microcontrollers, actuators, sensors, and AI-based decision-making systems.
    • Digital Image Processing: Covering fundamental concepts of image enhancement, restoration, segmentation, feature extraction, and pattern recognition, this course prepares students for careers in computer vision, medical imaging, and multimedia applications.
    • Microelectronic Circuits: Designed to deepen understanding of semiconductor device physics and circuit design, this course covers MOSFET modeling, amplifier design, oscillators, and analog integrated circuits. Students gain proficiency in designing low-power, high-efficiency circuits for modern electronics.
    • Embedded Systems Programming: This course provides practical training in embedded C programming, real-time operating systems (RTOS), ARM Cortex-M architecture, and hardware-software co-design techniques. It emphasizes building responsive, efficient systems for IoT and automation applications.

    Project-Based Learning Philosophy

    The Electronics program at Govt Polytechnic Satpuli embraces a robust project-based learning (PBL) approach to foster innovation, critical thinking, and collaborative skills. The philosophy behind PBL is to provide students with authentic learning experiences that mirror real-world engineering challenges.

    Mini Projects

    In the second year, students undertake mini-projects under faculty supervision. These projects typically last 2-3 months and are designed to reinforce classroom learning while encouraging creativity and problem-solving. Topics may include designing a simple electronic device, implementing a control system, or developing a basic IoT solution.

    Final Year Thesis/Capstone Project

    The final year capstone project is the most significant component of the program. Students are required to complete an original research or development project that demonstrates their ability to apply advanced concepts and technologies. Projects are selected in consultation with faculty mentors and often involve collaboration with industry partners.

    Project Selection Process

    The selection process for capstone projects involves a proposal submission phase where students identify potential topics based on their interests and career goals. Faculty mentors guide students through literature review, methodology planning, and feasibility assessment. Projects are evaluated based on innovation, technical depth, and practical relevance.

    Evaluation Criteria

    Projects are assessed based on several criteria including technical execution, documentation quality, presentation skills, peer evaluation, and final deliverables. Students must submit detailed reports, conduct presentations, and defend their work in front of a panel of experts.