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

    Duration

    4 Years

    Bachelor of Electrical Engineering

    Patel College of Science and Technology
    Duration
    4 Years
    Bachelor of Electrical Engineering UG OFFLINE

    Duration

    4 Years

    Bachelor of Electrical Engineering

    Patel College of Science and Technology
    Duration
    Apply

    Fees

    ₹2,50,000

    Placement

    92.0%

    Avg Package

    ₹4,50,000

    Highest Package

    ₹9,00,000

    OverviewAdmissionsCurriculumFeesPlacements
    4 Years
    Bachelor of Electrical Engineering
    UG
    OFFLINE

    Fees

    ₹2,50,000

    Placement

    92.0%

    Avg Package

    ₹4,50,000

    Highest Package

    ₹9,00,000

    Seats

    180

    Students

    1,200

    ApplyCollege

    Seats

    180

    Students

    1,200

    Curriculum

    Comprehensive Course List Across 8 Semesters

    SemesterCourse CodeCourse TitleCredits (L-T-P-C)Prerequisites
    1EE101Engineering Mathematics I3-1-0-4-
    1EE102Physics for Electrical Engineering3-1-0-4-
    1EE103Introduction to Programming2-0-2-4-
    1EE104Basic Electrical Engineering3-1-0-4-
    1EE105Chemistry for Engineers3-1-0-4-
    1EE106English Communication Skills2-0-0-2-
    2EE201Engineering Mathematics II3-1-0-4EE101
    2EE202Electromagnetic Fields3-1-0-4EE102
    2EE203Digital Logic Design3-1-0-4EE104
    2EE204Circuit Analysis3-1-0-4EE104
    2EE205Signals and Systems3-1-0-4EE201
    2EE206Engineering Graphics2-0-2-4-
    3EE301Electronics Devices and Circuits3-1-0-4EE204
    3EE302Power Electronics3-1-0-4EE204
    3EE303Control Systems3-1-0-4EE205
    3EE304Microprocessor and Microcontroller3-1-0-4EE203
    3EE305Electrical Machines3-1-0-4EE204
    3EE306Probability and Statistics for Engineers3-1-0-4EE201
    4EE401Power Systems3-1-0-4EE305
    4EE402Communication Systems3-1-0-4EE205
    4EE403Embedded Systems3-1-0-4EE304
    4EE404Computer Architecture3-1-0-4EE203
    4EE405Advanced Control Systems3-1-0-4EE303
    4EE406Digital Signal Processing3-1-0-4EE205
    5EE501Renewable Energy Systems3-1-0-4EE401
    5EE502Artificial Intelligence & Machine Learning3-1-0-4EE406
    5EE503Smart Grid Technologies3-1-0-4EE401
    5EE504VLSI Design3-1-0-4EE301
    5EE505Signal Processing3-1-0-4EE406
    5EE506Robotics and Automation3-1-0-4EE303
    6EE601Advanced Power Electronics3-1-0-4EE302
    6EE602Wireless Communication3-1-0-4EE402
    6EE603Network Security3-1-0-4EE402
    6EE604Internet of Things (IoT)3-1-0-4EE403
    6EE605Energy Storage Systems3-1-0-4EE501
    6EE606Project Management2-0-0-2-
    7EE701Research Methodology2-0-0-2-
    7EE702Advanced Embedded Systems3-1-0-4EE403
    7EE703Advanced AI Applications3-1-0-4EE502
    7EE704Industrial Internship6-0-0-6-
    8EE801Final Year Project / Thesis8-0-0-8-

    Advanced Departmental Electives

    These courses are designed to deepen understanding in specialized areas of electrical engineering:

    • Renewable Energy Systems: This course explores the principles and technologies behind solar, wind, hydroelectric, and geothermal power generation. Students learn about grid integration, energy storage systems, and policy frameworks supporting renewable energy adoption.
    • Artificial Intelligence & Machine Learning: An intensive study of algorithms used in AI, including neural networks, deep learning, reinforcement learning, and natural language processing. The course emphasizes practical implementation using Python and TensorFlow.
    • Smart Grid Technologies: Focuses on modernizing electrical grids with smart sensors, automation, and communication systems. Topics include demand response management, grid stability, and cybersecurity in power systems.
    • VLSI Design: Covers the design and implementation of Very Large Scale Integration (VLSI) circuits. Students learn about logic synthesis, layout design, testing, and verification techniques using industry-standard tools like Cadence and Synopsys.
    • Signal Processing: A comprehensive exploration of digital signal processing concepts including filtering, spectral analysis, and transform methods. Applications include audio and image processing, biomedical signal analysis, and telecommunications.
    • Robotics and Automation: Integrates mechanical engineering with electrical systems to design autonomous robots. The course includes topics like sensor integration, control algorithms, path planning, and machine vision.
    • Advanced Power Electronics: Delves into advanced topologies in power conversion such as resonant converters, multilevel inverters, and high-frequency switching circuits. Practical applications include electric vehicle charging systems and renewable energy inverters.
    • Wireless Communication: Examines modern wireless communication standards including 5G, Wi-Fi, Bluetooth, and satellite communications. Students gain hands-on experience with RF design tools and protocols used in cellular networks.
    • Network Security: Addresses the challenges of securing networked systems against cyber threats. Topics include cryptography, firewall implementation, intrusion detection, and secure protocol design.
    • Internet of Things (IoT): Explores the architecture and applications of IoT devices in smart cities, healthcare, agriculture, and industrial automation. Students work on real-world projects involving microcontrollers, sensors, and cloud connectivity.

    Project-Based Learning Philosophy

    The department strongly believes in project-based learning as a core component of engineering education. Projects are integrated throughout the curriculum to reinforce theoretical concepts with practical applications:

    • Mini-Projects: Conducted in second and third years, these projects allow students to apply learned concepts to real-world problems under faculty supervision.
    • Final-Year Thesis/Capstone Project: Students undertake a major project that contributes to their academic profile and industry readiness. Projects are selected based on student interest, faculty expertise, and alignment with current trends in electrical engineering.

    Students select their projects in consultation with faculty mentors who guide them through the research process, data collection, analysis, and documentation. Evaluation criteria include innovation, technical depth, presentation quality, and team collaboration.