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

    Duration

    4 Years

    Bachelor of Technology in Engineering

    Rai University Ahmedabad
    Duration
    4 Years
    Engineering UG OFFLINE

    Duration

    4 Years

    Bachelor of Technology in Engineering

    Rai University Ahmedabad
    Duration
    Apply

    Fees

    ₹8,00,000

    Placement

    92.0%

    Avg Package

    ₹6,00,000

    Highest Package

    ₹15,00,000

    OverviewAdmissionsCurriculumFeesPlacements
    4 Years
    Engineering
    UG
    OFFLINE

    Fees

    ₹8,00,000

    Placement

    92.0%

    Avg Package

    ₹6,00,000

    Highest Package

    ₹15,00,000

    Seats

    150

    Students

    1,200

    ApplyCollege

    Seats

    150

    Students

    1,200

    Curriculum

    Course Structure Overview

    The engineering program at Rai University Ahmedabad is structured over 8 semesters, with a balanced mix of core engineering subjects, departmental electives, science electives, and laboratory courses. The curriculum is designed to provide students with a strong foundation in engineering principles, followed by specialization in their chosen field. The program emphasizes hands-on learning, project-based assignments, and real-world applications to ensure that students are well-prepared for their future careers.

    SemesterCourse CodeCourse TitleCredit Structure (L-T-P-C)Prerequisites
    1ENG101Engineering Graphics2-0-0-2None
    1MAT101Mathematics I4-0-0-4None
    1PHY101Physics I3-0-0-3None
    1CHM101Chemistry I3-0-0-3None
    1ECO101Engineering Economics2-0-0-2None
    1INT101Introduction to Programming2-0-2-3None
    2MAT102Mathematics II4-0-0-4MAT101
    2PHY102Physics II3-0-0-3PHY101
    2CHM102Chemistry II3-0-0-3CHM101
    2ENG102Engineering Mechanics3-0-0-3ENG101
    2ECO102Business Fundamentals2-0-0-2ECO101
    2INT102Object-Oriented Programming2-0-2-3INT101
    3MAT103Mathematics III4-0-0-4MAT102
    3PHY103Physics III3-0-0-3PHY102
    3CHM103Chemistry III3-0-0-3CHM102
    3ENG103Thermodynamics3-0-0-3ENG102
    3ECO103Financial Management2-0-0-2ECO102
    3INT103Data Structures2-0-2-3INT102
    4MAT104Mathematics IV4-0-0-4MAT103
    4PHY104Physics IV3-0-0-3PHY103
    4CHM104Chemistry IV3-0-0-3CHM103
    4ENG104Electrical Circuits3-0-0-3ENG103
    4ECO104Marketing Management2-0-0-2ECO103
    4INT104Database Management Systems2-0-2-3INT103
    5MAT201Mathematics V4-0-0-4MAT104
    5PHY201Physics V3-0-0-3PHY104
    5CHM201Chemistry V3-0-0-3CHM104
    5ENG201Materials Science3-0-0-3ENG104
    5ECO201Organizational Behavior2-0-0-2ECO104
    5INT201Algorithms2-0-2-3INT104
    6MAT202Mathematics VI4-0-0-4MAT201
    6PHY202Physics VI3-0-0-3PHY201
    6CHM202Chemistry VI3-0-0-3CHM201
    6ENG202Fluid Mechanics3-0-0-3ENG201
    6ECO202Human Resource Management2-0-0-2ECO201
    6INT202Software Engineering2-0-2-3INT201
    7MAT203Mathematics VII4-0-0-4MAT202
    7PHY203Physics VII3-0-0-3PHY202
    7CHM203Chemistry VII3-0-0-3CHM202
    7ENG203Control Systems3-0-0-3ENG202
    7ECO203Strategic Management2-0-0-2ECO202
    7INT203Machine Learning2-0-2-3INT202
    8MAT204Mathematics VIII4-0-0-4MAT203
    8PHY204Physics VIII3-0-0-3PHY203
    8CHM204Chemistry VIII3-0-0-3CHM203
    8ENG204Project Design2-0-4-4ENG203
    8ECO204Entrepreneurship2-0-0-2ECO203
    8INT204Capstone Project2-0-6-6INT203

    Advanced Departmental Electives

    Advanced departmental electives provide students with the opportunity to explore specialized topics in their chosen field. These courses are designed to deepen students' understanding of specific areas within engineering and prepare them for advanced research or industry roles.

    Machine Learning is a core elective that focuses on the principles and applications of machine learning algorithms. Students learn about supervised and unsupervised learning, neural networks, and deep learning techniques. The course includes hands-on projects involving data analysis and model development.

    Deep Learning builds upon the concepts introduced in Machine Learning and delves into advanced topics such as convolutional neural networks, recurrent neural networks, and generative adversarial networks. Students work on real-world projects involving image recognition, natural language processing, and computer vision.

    Natural Language Processing explores the intersection of computer science and linguistics to develop systems that can understand, interpret, and generate human language. Students learn about text processing, sentiment analysis, and language modeling techniques.

    Computer Vision focuses on enabling computers to interpret and understand visual information from the world. Students study image processing, object detection, and recognition algorithms, and work on projects involving real-world applications such as autonomous vehicles and medical imaging.

    Network Security provides students with a comprehensive understanding of cybersecurity principles and practices. The course covers topics such as encryption, authentication, and intrusion detection systems. Students engage in hands-on labs involving network security tools and techniques.

    Cryptography introduces students to the mathematical foundations of encryption and decryption. The course covers symmetric and asymmetric encryption, hash functions, and digital signatures. Students work on projects involving secure communication protocols and cryptographic implementations.

    Signal Processing focuses on the analysis and manipulation of signals in various domains. Students learn about Fourier transforms, filtering, and spectral analysis. The course includes practical applications in audio and image processing.

    Control Systems provides an in-depth understanding of control theory and its applications in engineering systems. Students study feedback control, system stability, and design techniques. The course includes laboratory work involving real-time control systems.

    Power Electronics explores the design and application of power electronic circuits and systems. Students learn about rectifiers, inverters, and power converters. The course includes hands-on projects involving power electronics applications.

    Renewable Energy Systems focuses on the design and implementation of renewable energy technologies. Students study solar, wind, and hydroelectric power systems. The course includes projects involving renewable energy integration and optimization.

    Biomedical Instrumentation introduces students to the design and application of medical devices and systems. The course covers topics such as sensors, signal processing, and medical imaging. Students work on projects involving biomedical device development and testing.

    Environmental Impact Assessment provides students with tools and techniques for evaluating the environmental effects of engineering projects. The course covers environmental regulations, impact mitigation strategies, and sustainability practices. Students engage in case studies involving real-world environmental projects.

    Industrial Robotics focuses on the design and application of robotic systems in manufacturing environments. Students learn about robot kinematics, control systems, and automation technologies. The course includes hands-on projects involving robotic programming and simulation.

    Lean Manufacturing introduces students to lean principles and practices for optimizing manufacturing processes. The course covers topics such as value stream mapping, waste reduction, and continuous improvement. Students work on projects involving process optimization and efficiency improvements.

    Advanced Materials explores the properties and applications of advanced materials in engineering systems. Students study nanomaterials, composites, and smart materials. The course includes laboratory work involving materials characterization and testing.

    Project-Based Learning Philosophy

    The engineering program at Rai University Ahmedabad places a strong emphasis on project-based learning to ensure that students gain practical experience and develop critical problem-solving skills. The curriculum includes mandatory mini-projects in the first and second years, followed by a final-year thesis or capstone project.

    Mini-projects are designed to help students apply theoretical concepts to real-world problems. These projects are typically completed in teams and involve multiple stages, including problem identification, research, design, implementation, and presentation. Students work under the guidance of faculty mentors and receive regular feedback throughout the process.

    The final-year thesis or capstone project is a comprehensive endeavor that allows students to demonstrate their mastery of engineering principles and their ability to tackle complex, interdisciplinary challenges. Students select a project topic in consultation with faculty mentors and work on it for the entire academic year. The project is evaluated based on technical merit, innovation, teamwork, and presentation skills.

    Faculty mentors play a crucial role in guiding students through the project process. They provide expertise, resources, and support to ensure that students can successfully complete their projects. The university also offers specialized workshops and training sessions to help students develop project management and presentation skills.