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    Collegese

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    Scholarships & exams

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

    Duration

    4 Years

    Operations

    Beehive College Of Management And Technology
    Duration
    4 Years
    Operations UG OFFLINE

    Duration

    4 Years

    Operations

    Beehive College Of Management And Technology
    Duration
    Apply

    Fees

    ₹8,00,000

    Placement

    92.5%

    Avg Package

    ₹6,00,000

    Highest Package

    ₹18,00,000

    OverviewAdmissionsCurriculumFeesPlacements
    4 Years
    Operations
    UG
    OFFLINE

    Fees

    ₹8,00,000

    Placement

    92.5%

    Avg Package

    ₹6,00,000

    Highest Package

    ₹18,00,000

    Seats

    120

    Students

    1,200

    ApplyCollege

    Seats

    120

    Students

    1,200

    Curriculum

    Comprehensive Course Listing

    SemesterCourse CodeCourse TitleCredit Structure (L-T-P-C)Prerequisites
    1MATH101Calculus and Linear Algebra3-1-0-4None
    1PHYS101Physics for Engineers3-1-0-4None
    1CSE101Introduction to Programming2-1-0-3None
    1ENG101English Communication Skills2-0-0-2None
    1HSS101Humanities and Social Sciences2-0-0-2None
    2MATH201Statistics and Probability3-1-0-4MATH101
    2PHYS201Thermodynamics and Heat Transfer3-1-0-4PHYS101
    2CSE201Data Structures and Algorithms3-1-0-4CSE101
    2ENG201Technical Writing and Presentation Skills2-0-0-2ENG101
    2HSS201Philosophy of Science and Technology2-0-0-2None
    3MATH301Operations Research3-1-0-4MATH201
    3MECH301Engineering Mechanics3-1-0-4PHYS201
    3CSE301Database Management Systems3-1-0-4CSE201
    3ECON301Microeconomics3-0-0-3MATH201
    3HSS301Business Ethics and Social Responsibility2-0-0-2None
    4MATH401Advanced Probability Theory3-1-0-4MATH301
    4MECH401Materials Science and Engineering3-1-0-4MECH301
    4CSE401Software Engineering Principles3-1-0-4CSE301
    4ECON401Macroeconomics3-0-0-3ECON301
    4HSS401Leadership and Team Dynamics2-0-0-2None
    5MATH501Linear Programming and Optimization3-1-0-4MATH401
    5MECH501Manufacturing Processes3-1-0-4MECH401
    5CSE501Machine Learning Fundamentals3-1-0-4CSE401
    5ECON501Industrial Organization3-0-0-3ECON401
    5HSS501Globalization and Its Impact on Operations2-0-0-2None
    6MATH601Stochastic Processes and Queueing Theory3-1-0-4MATH501
    6MECH601Quality Control and Reliability Engineering3-1-0-4MECH501
    6CSE601Big Data Analytics3-1-0-4CSE501
    6ECON601Economic Policy and Regulation3-0-0-3ECON501
    6HSS601Change Management in Organizations2-0-0-2None
    7MATH701Decision Analysis and Risk Modeling3-1-0-4MATH601
    7MECH701Supply Chain Management3-1-0-4MECH601
    7CSE701Deep Learning and Neural Networks3-1-0-4CSE601
    7ECON701International Trade and Investment3-0-0-3ECON601
    7HSS701Cross-Cultural Leadership in Operations2-0-0-2None
    8MATH801Operations Research Applications3-1-0-4MATH701
    8MECH801Advanced Manufacturing Systems3-1-0-4MECH701
    8CSE801AI in Operations and Robotics3-1-0-4CSE701
    8ECON801Development Economics and Policy3-0-0-3ECON701
    8HSS801Strategic Operations Management2-0-0-2None

    Detailed Departmental Elective Courses

    The department offers a rich selection of advanced elective courses that allow students to specialize and deepen their expertise in specific areas. These courses are designed to reflect the dynamic nature of operations management and incorporate cutting-edge research and industry practices.

    Advanced Operations Research

    This course delves into complex optimization models, simulation techniques, and decision-making frameworks used in real-world applications. Students learn to develop mathematical models for complex operational problems and apply them using specialized software tools. The course emphasizes practical implementation through case studies and hands-on projects.

    Supply Chain Analytics

    Supply chain analytics is a rapidly evolving field that combines data science, logistics, and business strategy. This course explores how predictive modeling, network optimization, and demand forecasting can enhance supply chain efficiency. Students work with real datasets from global companies to gain practical experience in analytical problem-solving.

    Lean Manufacturing Systems

    Lean manufacturing principles are central to modern operational excellence. This course covers the fundamental concepts of lean methodology, including value stream mapping, 5S, and continuous improvement. Students engage in simulations and workshops to implement lean practices in simulated environments before applying them to real projects.

    Sustainable Operations Management

    With increasing awareness about environmental sustainability, this course explores how organizations can integrate green practices into their operational strategies. Topics include life cycle assessment, carbon footprint reduction, circular economy principles, and sustainable sourcing practices. Students are encouraged to propose innovative solutions for reducing environmental impact in various industries.

    Project Management for Complex Systems

    This elective focuses on managing large-scale projects involving cross-functional teams and multiple stakeholders. Students learn project planning methodologies, risk assessment techniques, resource allocation strategies, and stakeholder engagement approaches. The course includes group projects that mirror real-world challenges faced by organizations.

    Financial Operations and Risk Modeling

    This interdisciplinary course bridges the gap between finance and operations. Students study financial metrics used in operational decision-making, risk modeling frameworks, and valuation techniques for operational assets. Practical sessions involve analyzing financial reports of companies and developing models for evaluating operational investments.

    Digital Transformation in Operations

    As digital technologies reshape industries, this course examines how companies leverage IoT, cloud computing, and AI to transform their operations. Students explore emerging trends, evaluate implementation strategies, and develop digital transformation plans for hypothetical organizations. Case studies from leading firms provide insights into successful adoption practices.

    Data-Driven Decision Making

    Students learn to extract meaningful insights from large datasets using statistical tools and machine learning algorithms. The course emphasizes the importance of data quality, visualization techniques, and communication of findings to decision-makers. Practical assignments involve working with real-world data sets and presenting actionable recommendations.

    Quality Assurance and Control

    This course covers quality control methodologies, Six Sigma principles, and process improvement techniques. Students gain hands-on experience with statistical process control tools, design of experiments, and quality management systems. The curriculum includes guest lectures from quality assurance experts in manufacturing and service industries.

    Global Operations Strategy

    Organizations operate in increasingly interconnected global markets, necessitating strategic approaches to managing operations across borders. This course examines multinational supply chains, international logistics, cultural considerations in operations, and geopolitical risks. Students engage in simulations that reflect the complexities of global operations management.

    Project-Based Learning Philosophy

    Our department strongly believes in experiential learning as a means to bridge theory and practice. Project-based learning is central to our program structure, with students engaging in both mini-projects throughout their academic journey and a final-year capstone project.

    The mini-projects, undertaken during the second and third years, are designed to reinforce classroom learning while introducing students to collaborative work environments. These projects are often sponsored by industry partners, ensuring relevance to current challenges faced by organizations.

    The final-year thesis/capstone project is a significant component of the program. Students select topics aligned with their interests and career goals, working closely with faculty mentors from across disciplines. The project typically involves identifying a real-world problem, proposing a solution, and presenting findings to stakeholders including industry professionals and academic experts.

    Students are encouraged to form interdisciplinary teams, fostering collaboration between different departments and encouraging innovation. The evaluation criteria for these projects include technical depth, creativity, presentation quality, and impact potential.