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    Scholarships & exams

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

    Duration

    4 Years

    Bachelor of Technology in Engineering

    Lnct Vidhyapeeth University Indore
    Duration
    4 Years
    Engineering UG OFFLINE

    Duration

    4 Years

    Bachelor of Technology in Engineering

    Lnct Vidhyapeeth University Indore
    Duration
    Apply

    Fees

    ₹12,00,000

    Placement

    94.0%

    Avg Package

    ₹5,80,000

    Highest Package

    ₹8,50,000

    OverviewAdmissionsCurriculumFeesPlacements
    4 Years
    Engineering
    UG
    OFFLINE

    Fees

    ₹12,00,000

    Placement

    94.0%

    Avg Package

    ₹5,80,000

    Highest Package

    ₹8,50,000

    Seats

    120

    Students

    800

    ApplyCollege

    Seats

    120

    Students

    800

    Curriculum

    Comprehensive Curriculum Overview

    The curriculum of the B.Tech Engineering program at Lnct Vidhyapeeth University Indore is meticulously designed to provide a balanced blend of theoretical knowledge and practical application. It follows a structured approach that ensures students gain comprehensive understanding of core engineering principles while also allowing them to explore specialized areas of interest.

    SemesterCourse CodeCourse TitleCredit Structure (L-T-P-C)Pre-requisites
    1ENG101Mathematics I3-1-0-4-
    1ENG102Physics I3-1-0-4-
    1ENG103Chemistry I3-1-0-4-
    1ENG104Engineering Graphics2-1-0-3-
    1ENG105Basic Electrical Engineering3-1-0-4-
    1ENG106Computer Programming2-1-0-3-
    1ENG107Technical English2-0-0-2-
    1ENG108Workshop Practice0-2-0-2-
    2ENG201Mathematics II3-1-0-4ENG101
    2ENG202Physics II3-1-0-4ENG102
    2ENG203Chemistry II3-1-0-4ENG103
    2ENG204Engineering Mechanics3-1-0-4-
    2ENG205Digital Electronics3-1-0-4-
    2ENG206Data Structures & Algorithms3-1-0-4ENG106
    2ENG207Engineering Drawing2-1-0-3-
    2ENG208Workshop Practice II0-2-0-2ENG108
    3ENG301Mathematics III3-1-0-4ENG201
    3ENG302Thermodynamics3-1-0-4ENG202
    3ENG303Materials Science3-1-0-4-
    3ENG304Mechanics of Solids3-1-0-4ENG204
    3ENG305Signals & Systems3-1-0-4-
    3ENG306Object-Oriented Programming3-1-0-4ENG206
    3ENG307Engineering Economics3-0-0-3-
    3ENG308Workshop Practice III0-2-0-2ENG208
    4ENG401Mathematics IV3-1-0-4ENG301
    4ENG402Fluid Mechanics3-1-0-4ENG302
    4ENG403Electrical Machines3-1-0-4-
    4ENG404Strength of Materials3-1-0-4ENG304
    4ENG405Digital Signal Processing3-1-0-4ENG305
    4ENG406Database Management Systems3-1-0-4ENG306
    4ENG407Project Management3-0-0-3-
    4ENG408Workshop Practice IV0-2-0-2ENG308
    5ENG501Advanced Mathematics3-1-0-4ENG401
    5ENG502Heat Transfer3-1-0-4ENG402
    5ENG503Control Systems3-1-0-4-
    5ENG504Structural Analysis3-1-0-4ENG404
    5ENG505Computer Networks3-1-0-4ENG406
    5ENG506Artificial Intelligence3-1-0-4ENG406
    5ENG507Operations Research3-0-0-3-
    5ENG508Workshop Practice V0-2-0-2ENG408
    6ENG601Statistical Methods3-1-0-4ENG501
    6ENG602Refrigeration & Air Conditioning3-1-0-4-
    6ENG603Power Systems3-1-0-4-
    6ENG604Design of Experiments3-1-0-4-
    6ENG605Software Engineering3-1-0-4ENG506
    6ENG606Mechatronics3-1-0-4-
    6ENG607Industrial Management3-0-0-3-
    6ENG608Workshop Practice VI0-2-0-2ENG508
    7ENG701Advanced Control Systems3-1-0-4ENG503
    7ENG702Environmental Engineering3-1-0-4-
    7ENG703Advanced Power Electronics3-1-0-4-
    7ENG704Finite Element Analysis3-1-0-4ENG504
    7ENG705Machine Learning3-1-0-4ENG506
    7ENG706Robotics & Automation3-1-0-4-
    7ENG707Economic Analysis3-0-0-3-
    7ENG708Workshop Practice VII0-2-0-2ENG608
    8ENG801Capstone Project I0-0-4-4-
    8ENG802Capstone Project II0-0-4-4ENG801
    8ENG803Special Topics in Engineering3-1-0-4-
    8ENG804Internship0-0-0-6-
    8ENG805Professional Ethics & Social Responsibility2-0-0-2-
    8ENG806Workshop Practice VIII0-2-0-2ENG708

    Detailed Course Descriptions for Departmental Electives

    Advanced departmental electives form a crucial part of the program, allowing students to specialize in areas of personal interest and professional relevance. These courses are designed to be challenging yet accessible, encouraging critical thinking and innovation.

    • Artificial Intelligence (AI) - This course introduces students to machine learning algorithms, neural networks, deep learning architectures, and natural language processing. Students learn to develop intelligent systems that can adapt and improve over time.
    • Cybersecurity - Focuses on protecting digital assets from threats and vulnerabilities. Topics include network security protocols, encryption techniques, risk management strategies, and ethical hacking practices.
    • Renewable Energy Systems - Explores the design and implementation of solar, wind, hydroelectric, and geothermal power systems. Students study energy conversion technologies and sustainable development practices.
    • Structural Engineering - Teaches students how to analyze and design buildings and infrastructure under various loads and conditions. Emphasis is placed on seismic resistance, material behavior, and construction planning.
    • Biomedical Engineering - Combines engineering principles with medical sciences to create innovative healthcare solutions. Students explore prosthetics, diagnostic tools, bioinformatics, and regulatory compliance in medical device development.
    • Robotics & Automation - Covers the design and implementation of robotic systems in manufacturing, healthcare, and service industries. Students gain hands-on experience with sensors, actuators, control systems, and AI integration.
    • Chemical Engineering - Focuses on chemical reactions, process optimization, and industrial production methods. Students learn about catalysis, polymer science, and environmental impact assessment in manufacturing processes.
    • Electrical Power Systems - Studies power generation, transmission, and distribution. Students explore renewable energy integration, smart grids, electrical machine design, and grid stability.
    • Computer Vision - Introduces students to image processing techniques, pattern recognition algorithms, and computer vision applications in autonomous vehicles, surveillance systems, and medical imaging.
    • Data Analytics - Teaches students how to collect, process, and interpret large datasets using statistical methods and machine learning. Applications include business intelligence, predictive analytics, and data-driven decision-making.

    Project-Based Learning Philosophy

    Our department strongly believes in the value of project-based learning as a means to enhance student engagement, foster creativity, and prepare them for real-world challenges. Projects are assigned at different levels throughout the program to progressively build skills and confidence.

    The mandatory mini-projects in the early semesters focus on reinforcing fundamental concepts through practical application. These projects are designed to be manageable yet impactful, giving students a taste of what it means to work on engineering problems from start to finish.

    As students advance, they engage in more complex and interdisciplinary capstone projects that often involve collaboration with industry partners or government agencies. The final-year thesis/capstone project is the culmination of their learning journey, requiring extensive research, design, implementation, and presentation skills.

    Students select their projects based on personal interest, career goals, and faculty expertise. They are paired with mentors who guide them through each stage of the project lifecycle, from initial concept development to final evaluation. Evaluation criteria include technical proficiency, innovation, teamwork, documentation quality, and oral presentation skills.