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    Scholarships & exams

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

    Duration

    4 Years

    Engineering

    Mind Power University Nanital
    Duration
    4 Years
    Engineering UG OFFLINE

    Duration

    4 Years

    Engineering

    Mind Power University Nanital
    Duration
    Apply

    Fees

    ₹12,00,000

    Placement

    95.0%

    Avg Package

    ₹8,00,000

    Highest Package

    ₹15,00,000

    OverviewAdmissionsCurriculumFeesPlacements
    4 Years
    Engineering
    UG
    OFFLINE

    Fees

    ₹12,00,000

    Placement

    95.0%

    Avg Package

    ₹8,00,000

    Highest Package

    ₹15,00,000

    Seats

    120

    Students

    1,200

    ApplyCollege

    Seats

    120

    Students

    1,200

    Curriculum

    Curriculum Overview

    The engineering program at Mind Power University Nanital is structured to provide students with a comprehensive and rigorous academic experience that prepares them for successful careers in various engineering disciplines. The curriculum is designed to balance theoretical knowledge with practical application, ensuring that students are well-equipped to tackle real-world challenges.

    The program is divided into 8 semesters, with each semester comprising a mix of core engineering courses, departmental electives, science electives, and laboratory sessions. The curriculum is regularly updated based on industry feedback and technological advancements, ensuring that students are exposed to the latest trends and developments in their field.

    Course Structure

    SemesterCourse CodeCourse TitleCredit Structure (L-T-P-C)Prerequisites
    1ENG101Engineering Mathematics I3-1-0-4-
    1ENG102Engineering Physics3-1-0-4-
    1ENG103Engineering Chemistry3-1-0-4-
    1ENG104Engineering Graphics2-1-0-3-
    1ENG105Basic Electrical Engineering3-1-0-4-
    1ENG106Introduction to Programming2-1-0-3-
    1ENG107Workshop Practice0-0-2-1-
    1ENG108Communication Skills2-0-0-2-
    2ENG201Engineering Mathematics II3-1-0-4ENG101
    2ENG202Engineering Mechanics3-1-0-4ENG102
    2ENG203Thermodynamics3-1-0-4ENG102
    2ENG204Electrical Circuits3-1-0-4ENG105
    2ENG205Materials Science3-1-0-4ENG103
    2ENG206Computer Programming3-1-0-4ENG106
    2ENG207Engineering Workshop0-0-2-1ENG107
    2ENG208Engineering Ethics2-0-0-2-
    3ENG301Engineering Mathematics III3-1-0-4ENG201
    3ENG302Fluid Mechanics3-1-0-4ENG202
    3ENG303Strength of Materials3-1-0-4ENG202
    3ENG304Signals and Systems3-1-0-4ENG201
    3ENG305Control Systems3-1-0-4ENG204
    3ENG306Computer Architecture3-1-0-4ENG206
    3ENG307Engineering Lab I0-0-3-1ENG207
    3ENG308Project Management2-0-0-2-
    4ENG401Engineering Mathematics IV3-1-0-4ENG301
    4ENG402Heat Transfer3-1-0-4ENG203
    4ENG403Design of Machine Elements3-1-0-4ENG303
    4ENG404Electromagnetic Fields3-1-0-4ENG204
    4ENG405Digital Signal Processing3-1-0-4ENG304
    4ENG406Operating Systems3-1-0-4ENG306
    4ENG407Engineering Lab II0-0-3-1ENG307
    4ENG408Entrepreneurship2-0-0-2-
    5ENG501Advanced Mathematics3-1-0-4ENG401
    5ENG502Advanced Fluid Mechanics3-1-0-4ENG302
    5ENG503Advanced Strength of Materials3-1-0-4ENG303
    5ENG504Advanced Control Systems3-1-0-4ENG305
    5ENG505Advanced Computer Architecture3-1-0-4ENG306
    5ENG506Advanced Digital Signal Processing3-1-0-4ENG405
    5ENG507Engineering Lab III0-0-3-1ENG407
    5ENG508Research Methodology2-0-0-2-
    6ENG601Research Project I0-0-6-3ENG508
    6ENG602Research Project II0-0-6-3ENG601
    6ENG603Research Project III0-0-6-3ENG602
    6ENG604Research Project IV0-0-6-3ENG603
    6ENG605Research Project V0-0-6-3ENG604
    6ENG606Research Project VI0-0-6-3ENG605
    6ENG607Research Project VII0-0-6-3ENG606
    6ENG608Research Project VIII0-0-6-3ENG607
    7ENG701Capstone Project I0-0-6-3ENG608
    7ENG702Capstone Project II0-0-6-3ENG701
    7ENG703Capstone Project III0-0-6-3ENG702
    7ENG704Capstone Project IV0-0-6-3ENG703
    7ENG705Capstone Project V0-0-6-3ENG704
    7ENG706Capstone Project VI0-0-6-3ENG705
    7ENG707Capstone Project VII0-0-6-3ENG706
    7ENG708Capstone Project VIII0-0-6-3ENG707
    8ENG801Final Project0-0-6-3ENG708
    8ENG802Final Project0-0-6-3ENG801
    8ENG803Final Project0-0-6-3ENG802
    8ENG804Final Project0-0-6-3ENG803
    8ENG805Final Project0-0-6-3ENG804
    8ENG806Final Project0-0-6-3ENG805
    8ENG807Final Project0-0-6-3ENG806
    8ENG808Final Project0-0-6-3ENG807

    Advanced Departmental Elective Courses

    Advanced departmental elective courses are designed to provide students with in-depth knowledge and skills in specialized areas of engineering. These courses are offered in the later semesters of the program and are tailored to meet the evolving demands of the industry and the interests of students.

    The course on Artificial Intelligence and Machine Learning provides students with a comprehensive understanding of algorithms, data structures, and neural networks. Students learn to develop and implement machine learning models for various applications, including natural language processing, computer vision, and predictive analytics. The course emphasizes both theoretical concepts and practical implementation, with students working on real-world projects that involve data analysis and model development.

    The course on Cybersecurity covers fundamental concepts in network security, cryptography, and ethical hacking. Students learn to identify and mitigate security vulnerabilities in computer systems and networks, and to develop secure software applications. The course includes hands-on laboratory sessions where students practice security testing and penetration testing techniques, preparing them for careers in cybersecurity consulting and research.

    The course on Data Science and Analytics provides students with a multidisciplinary approach to data analysis and modeling. Students learn to use statistical methods, machine learning, and data visualization tools to extract insights from complex datasets. The course emphasizes practical applications, with students working on projects that involve data cleaning, exploratory data analysis, and predictive modeling.

    The course on Renewable Energy Systems covers topics such as solar energy, wind power, and energy storage systems. Students learn to design and analyze renewable energy systems, and to evaluate their environmental and economic impact. The course includes laboratory sessions where students work on projects involving solar panel testing, wind turbine design, and energy storage system optimization.

    The course on Biomedical Engineering focuses on the intersection of engineering principles and medical applications. Students learn to design and develop medical devices, and to apply engineering concepts to solve healthcare challenges. The course includes laboratory sessions where students work on projects involving medical imaging, biomechanics, and bioinformatics.

    The course on Automation and Robotics covers topics such as control systems, sensor networks, and robotic design. Students learn to develop and implement automated systems, and to design robotic solutions for various applications. The course includes laboratory sessions where students work on projects involving embedded systems, machine learning, and human-robot interaction.

    The course on Environmental Engineering focuses on the design and implementation of sustainable solutions to environmental challenges. Students learn to analyze and solve problems related to water treatment, waste management, and environmental impact assessment. The course includes laboratory sessions where students work on projects involving water quality testing, waste characterization, and environmental monitoring.

    The course on Materials Science and Engineering covers topics such as materials characterization, nanotechnology, and advanced manufacturing processes. Students learn to design and develop new materials, and to analyze their properties and applications. The course includes laboratory sessions where students work on projects involving materials testing, nanomaterial synthesis, and manufacturing process optimization.

    The course on Transportation Engineering focuses on the design and optimization of transportation systems. Students learn to model and analyze traffic flow, and to design transportation infrastructure for urban and rural environments. The course includes laboratory sessions where students work on projects involving traffic simulation, urban planning, and sustainable transportation solutions.

    The course on Structural Engineering covers topics such as structural dynamics, earthquake engineering, and sustainable construction practices. Students learn to design and analyze structures for various applications, and to evaluate their performance under different loading conditions. The course includes laboratory sessions where students work on projects involving structural testing, finite element analysis, and design optimization.

    The course on Control Systems and Signal Processing provides students with a comprehensive understanding of control theory and signal processing techniques. Students learn to design and analyze control systems, and to process and analyze signals in various applications. The course includes laboratory sessions where students work on projects involving system modeling, controller design, and signal processing algorithms.

    Project-Based Learning Philosophy

    The department's philosophy on project-based learning is rooted in the belief that students learn best when they are actively engaged in solving real-world problems. This approach emphasizes hands-on experience, collaboration, and the application of theoretical knowledge to practical situations.

    The structure of project-based learning in the engineering program is designed to provide students with a comprehensive experience that spans multiple semesters. Students begin with mini-projects in the early semesters, which are designed to build foundational skills and knowledge. These projects are typically small-scale and focus on specific aspects of engineering principles.

    As students progress through the program, they engage in more complex projects that require advanced skills and knowledge. These projects often involve collaboration with industry partners, providing students with exposure to real-world challenges and solutions.

    The final-year thesis/capstone project is the culmination of the project-based learning experience. Students work on a significant research or design project that addresses a complex problem in their field. The project is typically supervised by a faculty member and involves extensive research, design, and implementation.

    The evaluation criteria for project-based learning are designed to assess both the technical skills and the soft skills of students. Technical skills are evaluated based on the quality of the project deliverables, while soft skills are assessed based on the student's ability to work in teams, communicate effectively, and demonstrate leadership.

    Students select their projects and faculty mentors based on their interests and career goals. The department provides guidance and support throughout the project selection process, ensuring that students choose projects that align with their academic and professional objectives.