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    Scholarships & exams

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

    Duration

    4 Years

    Vocational Training

    Universal Skilltech University, Maharashtra
    Duration
    4 Years
    Vocational Training UG OFFLINE

    Duration

    4 Years

    Vocational Training

    Universal Skilltech University, Maharashtra
    Duration
    Apply

    Fees

    ₹18,00,000

    Placement

    92.5%

    Avg Package

    ₹6,50,000

    Highest Package

    ₹12,00,000

    OverviewAdmissionsCurriculumFeesPlacements
    4 Years
    Vocational Training
    UG
    OFFLINE

    Fees

    ₹18,00,000

    Placement

    92.5%

    Avg Package

    ₹6,50,000

    Highest Package

    ₹12,00,000

    Seats

    400

    Students

    350

    ApplyCollege

    Seats

    400

    Students

    350

    Curriculum

    Curriculum Overview

    The vocational training program at Universal Skilltech University Maharashtra is meticulously designed to provide students with a balanced blend of theoretical knowledge and practical application. The curriculum spans eight semesters, each structured to progressively build upon the previous ones while offering flexibility through elective options.

    YearSemesterCourse CodeCourse TitleCredit Structure (L-T-P-C)Prerequisites
    First YearIENG101English for Technical Communication3-0-0-2-
    First YearIMAT101Calculus and Analytical Geometry4-0-0-2-
    First YearIPHY101Physics for Engineers3-0-0-2-
    First YearICHE101Chemistry for Engineers3-0-0-2-
    First YearIECE101Introduction to Electrical Engineering3-0-0-2-
    First YearIMAT102Linear Algebra and Differential Equations4-0-0-2MAT101
    First YearICS101Introduction to Programming3-0-0-2-
    First YearIENG102Technical Writing and Presentation Skills2-0-0-1-
    First YearIPHY102Practical Physics Laboratory0-0-3-1PHY101
    First YearIIMAT201Probability and Statistics4-0-0-2MAT101
    First YearIIPHY201Thermodynamics and Heat Transfer3-0-0-2PHY101
    First YearIICHE201Organic Chemistry3-0-0-2CHE101
    First YearIIECE201Electrical Circuits and Networks3-0-0-2ECE101
    First YearIICS201Data Structures and Algorithms3-0-0-2CS101
    First YearIIMAT202Vector Calculus and Complex Analysis4-0-0-2MAT102
    First YearIICHE202Physical Chemistry3-0-0-2CHE201
    First YearIIPHY202Practical Physics Laboratory0-0-3-1PHY102
    Second YearIIIEC301Digital Electronics and Logic Design3-0-0-2ECE201
    Second YearIIICS301Database Management Systems3-0-0-2CS201
    Second YearIIIMAT301Numerical Methods3-0-0-2MAT201
    Second YearIIIECE301Signals and Systems3-0-0-2ECE201
    Second YearIIIMAT302Operations Research3-0-0-2MAT201
    Second YearIIICS302Object-Oriented Programming3-0-0-2CS201
    Second YearIIIEC302Control Systems3-0-0-2ECE301
    Second YearIIICS303Computer Architecture3-0-0-2CS201
    Second YearIVEC401Communication Systems3-0-0-2ECE301
    Second YearIVCS401Software Engineering3-0-0-2CS302
    Second YearIVMAT401Advanced Mathematics4-0-0-2MAT301
    Second YearIVECE401Electromagnetic Fields and Waves3-0-0-2ECE301
    Second YearIVCS402Operating Systems3-0-0-2CS301
    Second YearIVEC402Microprocessors and Microcontrollers3-0-0-2ECE301
    Third YearVEC501Wireless Communication3-0-0-2EC401
    Third YearVCS501Machine Learning Fundamentals3-0-0-2CS301
    Third YearVEC502Power Electronics3-0-0-2ECE401
    Third YearVCS502Web Technologies3-0-0-2CS301
    Third YearVMAT501Statistical Inference3-0-0-2MAT201
    Third YearVEC503Antenna and Wave Propagation3-0-0-2ECE401
    Third YearVCS503Cloud Computing3-0-0-2CS301
    Third YearVIEC601Optical Fiber Communication3-0-0-2EC501
    Third YearVICS601Deep Learning3-0-0-2CS501
    Third YearVIEC602Embedded Systems3-0-0-2ECE502
    Third YearVICS602DevOps and CI/CD3-0-0-2CS401
    Third YearVIMAT601Mathematical Modeling3-0-0-2MAT501
    Third YearVIEC603RF and Microwave Engineering3-0-0-2ECE503
    Fourth YearVIIEC701Advanced VLSI Design3-0-0-2EC602
    Fourth YearVIICS701Big Data Analytics3-0-0-2CS501
    Fourth YearVIIEC702Power System Analysis3-0-0-2ECE502
    Fourth YearVIICS702Artificial Intelligence3-0-0-2CS601
    Fourth YearVIIMAT701Stochastic Processes3-0-0-2MAT601
    Fourth YearVIIEC703Signal Processing3-0-0-2ECE503
    Fourth YearVIIIEC801Capstone Project0-0-6-4All Previous Courses
    Fourth YearVIIICS801Research Thesis0-0-6-4All Previous Courses
    Fourth YearVIIIEC802Internship0-0-0-4All Previous Courses
    Fourth YearVIIICS802Internship0-0-0-4All Previous Courses

    Advanced Departmental Electives

    The department offers a rich selection of advanced elective courses that allow students to explore specialized areas in depth. These courses are designed to align with industry trends and prepare students for advanced roles in their chosen fields.

    • Advanced Machine Learning Algorithms: This course explores state-of-the-art techniques in machine learning, including reinforcement learning, generative adversarial networks, and deep learning architectures. Students work on research projects using real-world datasets to enhance their practical skills.
    • Cybersecurity and Ethical Hacking: Focused on defending against cyber threats, this course covers network security protocols, cryptography, intrusion detection systems, and penetration testing methodologies. Real-time simulations and labs provide hands-on experience with industry-standard tools.
    • Renewable Energy Technologies: This course delves into solar, wind, hydroelectric, and geothermal energy conversion systems. Students gain insights into energy storage technologies, grid integration, and policy frameworks supporting sustainable development.
    • Smart Manufacturing Systems: Designed for those interested in Industry 4.0, this course explores automation technologies, IoT integration, and smart factory design principles. Students engage in projects involving robotics, process control, and digital twins to simulate real-world manufacturing environments.
    • Data Visualization and Business Intelligence: This elective focuses on transforming complex data into actionable insights using visualization tools such as Tableau, Power BI, and Python libraries. Students learn how to build dashboards and reports that support decision-making in business contexts.
    • Biomedical Signal Processing: Combining engineering principles with medical sciences, this course teaches students how to process signals from physiological systems like ECG, EEG, and EMG. Applications include medical device design and healthcare data analysis.
    • Environmental Impact Assessment: This course provides tools for evaluating the environmental consequences of engineering projects. Students learn how to conduct lifecycle assessments, perform risk analysis, and develop mitigation strategies for industrial activities.
    • Robotics and Autonomous Systems: Covering sensor integration, navigation algorithms, and control systems, this course prepares students for careers in robotics engineering. Projects involve designing and programming mobile robots for various applications including search and rescue missions.
    • Internet of Things (IoT) Architecture: This course explores the architecture and protocols used in IoT networks. Students learn about microcontrollers, wireless communication standards, edge computing, and data security in connected environments.
    • Software Testing and Quality Assurance: Emphasizing software quality management, this course teaches testing methodologies, automation frameworks, and compliance standards. Students gain experience with tools like Selenium, JUnit, and TestNG to ensure robust software delivery.

    Project-Based Learning Philosophy

    The department's approach to project-based learning emphasizes real-world problem-solving, collaboration, and innovation. From the first year, students are encouraged to engage in mini-projects that reinforce classroom concepts and develop critical thinking skills.

    Mini-projects are assigned in groups of 3-5 students and span across multiple semesters. Each group selects a topic aligned with their interests and career goals, guided by faculty mentors who provide academic supervision throughout the process.

    The final-year capstone project is a significant component of the curriculum, allowing students to demonstrate mastery over advanced concepts through an original research or development initiative. Projects are often sponsored by industry partners, providing students with direct exposure to professional challenges and opportunities for commercialization.

    Assessment criteria include technical execution, innovation, teamwork, presentation quality, and documentation standards. Faculty members evaluate student performance based on these parameters, ensuring that projects meet both academic rigor and industry relevance.