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    +91 88943 57155
    Pune, Maharashtra, India

    Duration

    4 Years

    Vocational Training

    G H Raisoni International Skill Tech University Pune
    Duration
    4 Years
    Vocational Training UG OFFLINE

    Duration

    4 Years

    Vocational Training

    G H Raisoni International Skill Tech University Pune
    Duration
    Apply

    Fees

    ₹12,00,000

    Placement

    92.0%

    Avg Package

    ₹4,50,000

    Highest Package

    ₹9,00,000

    OverviewAdmissionsCurriculumFeesPlacements
    4 Years
    Vocational Training
    UG
    OFFLINE

    Fees

    ₹12,00,000

    Placement

    92.0%

    Avg Package

    ₹4,50,000

    Highest Package

    ₹9,00,000

    Seats

    150

    Students

    800

    ApplyCollege

    Seats

    150

    Students

    800

    Curriculum

    Comprehensive Course Structure

    The vocational training program at G H Raisoni International Skill Tech University Pune is structured across eight semesters, with a balanced mix of core subjects, departmental electives, science electives, and laboratory sessions. The curriculum is designed to provide a robust foundation in technical concepts while encouraging specialization through elective courses.

    SemesterCourse CodeCourse TitleCredit Structure (L-T-P-C)Prerequisites
    1MATH101Mathematics I3-1-0-4-
    1PHYS101Physics I3-1-0-4-
    1CHM101Chemistry I3-1-0-4-
    1EG101Engineering Graphics2-1-0-3-
    1CP101Introduction to Programming3-1-0-4-
    2MATH201Mathematics II3-1-0-4MATH101
    2PHYS201Physics II3-1-0-4PHYS101
    2CHM201Chemistry II3-1-0-4CHM101
    2EG201Engineering Mechanics3-1-0-4EG101
    2CP201Data Structures and Algorithms3-1-0-4CP101
    3MATH301Mathematics III3-1-0-4MATH201
    3PHYS301Physics III3-1-0-4PHYS201
    3CHM301Chemistry III3-1-0-4CHM201
    3EG301Dynamics of Machines3-1-0-4EG201
    3CP301Database Management Systems3-1-0-4CP201
    4MATH401Mathematics IV3-1-0-4MATH301
    4PHYS401Physics IV3-1-0-4PHYS301
    4CHM401Chemistry IV3-1-0-4CHM301
    4EG401Thermodynamics3-1-0-4EG301
    4CP401Computer Networks3-1-0-4CP301
    5MATH501Mathematics V3-1-0-4MATH401
    5PHYS501Physics V3-1-0-4PHYS401
    5CHM501Chemistry V3-1-0-4CHM401
    5EG501Machine Design3-1-0-4EG401
    5CP501Operating Systems3-1-0-4CP401
    6MATH601Mathematics VI3-1-0-4MATH501
    6PHYS601Physics VI3-1-0-4PHYS501
    6CHM601Chemistry VI3-1-0-4CHM501
    6EG601Industrial Engineering3-1-0-4EG501
    6CP601Software Engineering3-1-0-4CP501
    7MATH701Mathematics VII3-1-0-4MATH601
    7PHYS701Physics VII3-1-0-4PHYS601
    7CHM701Chemistry VII3-1-0-4CHM601
    7EG701Project Management3-1-0-4EG601
    7CP701Advanced Topics in Computer Science3-1-0-4CP601
    8MATH801Mathematics VIII3-1-0-4MATH701
    8PHYS801Physics VIII3-1-0-4PHYS701
    8CHM801Chemistry VIII3-1-0-4CHM701
    8EG801Capstone Project3-1-0-4EG701
    8CP801Final Year Thesis3-1-0-4CP701

    Advanced Departmental Electives

    The department offers a wide array of advanced elective courses designed to deepen students' understanding of specialized areas within their field. These courses are structured to align with industry trends and academic research, ensuring that students are well-prepared for both professional roles and higher education.

    One such course is 'Deep Learning and Neural Networks,' which delves into the mathematical foundations of neural networks and their applications in image recognition, natural language processing, and reinforcement learning. Students engage in hands-on projects using frameworks like TensorFlow and PyTorch, developing models that can be deployed in real-world scenarios.

    Another advanced elective is 'Cybersecurity and Network Defense,' which explores the principles of network security, cryptographic protocols, and incident response strategies. Through simulations and case studies, students learn to detect and mitigate cyber threats, preparing them for roles in cybersecurity analysis and protection.

    The course 'Data Science and Analytics' focuses on statistical methods, machine learning algorithms, and data visualization techniques. Students work with real datasets from various industries, applying analytical tools to extract insights and support decision-making processes.

    'Internet of Things (IoT) and Embedded Systems' teaches students how to design and implement smart devices that can communicate with each other and respond to environmental changes. This course covers hardware programming, sensor integration, and network protocols, providing a comprehensive understanding of IoT ecosystems.

    'Software Engineering and Application Development' emphasizes the entire software development lifecycle, from requirements gathering to deployment and maintenance. Students work in teams on large-scale projects, applying agile methodologies and tools like Git for version control and Jira for project tracking.

    'Robotics and Automation' combines mechanical engineering with computer science to create intelligent machines capable of performing complex tasks. Students learn about robot kinematics, sensor integration, control systems, and programming languages used in robotics.

    'Environmental Engineering and Sustainable Technologies' addresses the challenges of environmental pollution and resource depletion through sustainable solutions. Topics include water treatment, waste management, and renewable energy systems, preparing students to contribute to global sustainability efforts.

    Each elective course includes practical components such as laboratory sessions, workshops, and project-based assessments. These elements ensure that students gain both theoretical knowledge and hands-on experience necessary for success in their chosen fields.

    Project-Based Learning Philosophy

    The department strongly believes in the power of project-based learning as a means to enhance student engagement and deepen understanding of complex concepts. Projects are designed to simulate real-world scenarios, requiring students to apply theoretical knowledge to practical challenges.

    The structure of projects begins with problem identification, followed by literature review, design planning, implementation, testing, and documentation. Students work in teams, fostering collaboration and communication skills essential for professional environments.

    Mini-projects are assigned throughout the academic year, allowing students to experiment with new ideas and technologies without the pressure of high-stakes outcomes. These projects serve as stepping stones towards the final capstone project, which is a significant component of the curriculum.

    The evaluation criteria for projects include technical competency, innovation, teamwork, presentation skills, and adherence to deadlines. Faculty mentors guide students through each stage, providing feedback and support necessary for successful completion.

    For the final-year thesis/capstone project, students select topics aligned with their interests and career goals. They are paired with faculty members who provide expertise and supervision throughout the process. The project culminates in a public presentation and defense before a panel of experts, ensuring that students can articulate their work effectively.

    The department also encourages participation in external competitions and hackathons, where students can showcase their projects and gain recognition from industry professionals. These events provide valuable networking opportunities and enhance the visibility of student achievements.