Curriculum Overview
The curriculum of the Operations program at Doon Business School is designed to provide a comprehensive understanding of operational principles, methodologies, and applications across various industries. The program spans four years with a carefully structured sequence of core subjects, departmental electives, science electives, and laboratory sessions that build upon each other to create a robust foundation for future careers.
Students begin their academic journey in the first semester with foundational courses such as Engineering Mathematics I, Physics for Engineers, Chemistry for Engineers, Calculus and Differential Equations, Introduction to Programming, Computer Science Fundamentals, Engineering Drawing, and Workshop Practice. These courses lay the groundwork for more advanced topics that follow.
In the second semester, students delve deeper into technical subjects including Engineering Mathematics II, Modern Physics and Applications, Linear Algebra and Numerical Methods, Data Structures and Algorithms, Basic Electrical Engineering, Engineering Mechanics, and Engineering Ethics and Professionalism. These courses help students develop analytical thinking and problem-solving skills essential for understanding complex operational challenges.
The third year introduces core operational subjects such as Materials Science, Thermodynamics, Manufacturing Processes, Probability and Statistics, Operations Research, Quality Assurance and Control, and Process Control. These foundational courses prepare students to apply theoretical knowledge in real-world scenarios through practical applications and case studies.
By the fourth year, students explore specialized areas such as Supply Chain Management, Digital Transformation in Operations, Project Management, Lean Six Sigma Fundamentals, Service Operations Design, and Risk Assessment and Mitigation. These advanced subjects provide students with a competitive edge in the job market by equipping them with cutting-edge tools and frameworks used by leading organizations.
Departmental electives in the fifth and sixth years offer students opportunities to specialize further based on their interests. Courses such as Advanced Operations Analytics, Operations Simulation and Modeling, Strategic Operations Planning, Human Factors in Operations, Sustainable Operations and Green Manufacturing, and Operations in Healthcare Systems allow students to tailor their education according to their career aspirations.
The final two semesters are dedicated to capstone projects and internships. Students engage in Capstone Project I, Research Methodology, and Operations Innovation Lab during the seventh semester, followed by Capstone Project II and Internship in the eighth semester. These experiences provide students with hands-on exposure to real-world challenges and enable them to apply their knowledge creatively.
Course Details
| Semester | Course Code | Course Title | Credit Structure (L-T-P-C) | Prerequisites |
| 1 | ENG101 | Engineering Mathematics I | 3-1-0-4 | - |
| 1 | PHY101 | Physics for Engineers | 3-1-0-4 | - |
| 1 | CHE101 | Chemistry for Engineers | 3-1-0-4 | - |
| 1 | MAT101 | Calculus and Differential Equations | 3-1-0-4 | - |
| 1 | ENG102 | Introduction to Programming | 2-1-0-3 | - |
| 1 | CS101 | Computer Science Fundamentals | 2-1-0-3 | - |
| 1 | ENG103 | Engineering Drawing | 2-1-0-3 | - |
| 1 | ENG104 | Workshop Practice | 0-0-1-1 | - |
| 2 | ENG105 | Engineering Mathematics II | 3-1-0-4 | ENG101 |
| 2 | PHY102 | Modern Physics and Applications | 3-1-0-4 | PHY101 |
| 2 | MAT102 | Linear Algebra and Numerical Methods | 3-1-0-4 | MAT101 |
| 2 | CS102 | Data Structures and Algorithms | 2-1-0-3 | ENG102 |
| 2 | ENG106 | Basic Electrical Engineering | 3-1-0-4 | - |
| 2 | ENG107 | Engineering Mechanics | 3-1-0-4 | - |
| 2 | ENG108 | Engineering Ethics and Professionalism | 2-0-0-2 | - |
| 3 | ENG201 | Materials Science | 3-1-0-4 | - |
| 3 | ENG202 | Thermodynamics | 3-1-0-4 | - |
| 3 | ENG203 | Manufacturing Processes | 3-1-0-4 | - |
| 3 | ENG204 | Probability and Statistics | 3-1-0-4 | MAT102 |
| 3 | ENG205 | Operations Research | 3-1-0-4 | MAT102 |
| 3 | ENG206 | Quality Assurance and Control | 3-1-0-4 | - |
| 3 | ENG207 | Process Control | 3-1-0-4 | - |
| 4 | ENG208 | Supply Chain Management | 3-1-0-4 | - |
| 4 | ENG209 | Digital Transformation in Operations | 3-1-0-4 | - |
| 4 | ENG210 | Project Management | 3-1-0-4 | - |
| 4 | ENG211 | Lean Six Sigma Fundamentals | 3-1-0-4 | - |
| 4 | ENG212 | Service Operations Design | 3-1-0-4 | - |
| 4 | ENG213 | Risk Assessment and Mitigation | 3-1-0-4 | - |
| 5 | ENG301 | Advanced Operations Analytics | 3-1-0-4 | ENG204 |
| 5 | ENG302 | Operations Simulation and Modeling | 3-1-0-4 | - |
| 5 | ENG303 | Strategic Operations Planning | 3-1-0-4 | - |
| 5 | ENG304 | Human Factors in Operations | 3-1-0-4 | - |
| 5 | ENG305 | Sustainable Operations and Green Manufacturing | 3-1-0-4 | - |
| 5 | ENG306 | Operations in Healthcare Systems | 3-1-0-4 | - |
| 6 | ENG307 | Advanced Supply Chain Optimization | 3-1-0-4 | ENG208 |
| 6 | ENG308 | Data Science for Operations | 3-1-0-4 | - |
| 6 | ENG309 | Industry 4.0 Technologies | 3-1-0-4 | - |
| 6 | ENG310 | Operations in Public Sector | 3-1-0-4 | - |
| 6 | ENG311 | Leadership and Change Management | 3-1-0-4 | - |
| 7 | ENG401 | Capstone Project I | 0-0-2-2 | - |
| 7 | ENG402 | Research Methodology | 3-1-0-4 | - |
| 7 | ENG403 | Operations Innovation Lab | 0-0-2-2 | - |
| 8 | ENG404 | Capstone Project II | 0-0-2-2 | - |
| 8 | ENG405 | Internship | 0-0-0-6 | - |
Advanced Departmental Electives
Departmental electives in the fifth and sixth semesters provide students with opportunities to specialize further based on their interests and career goals. These courses are designed to offer depth and relevance in specific areas of operations management, ensuring that students graduate with both breadth and specialization.
- Operations Analytics and Data Science: This course integrates statistical methods, machine learning algorithms, and data visualization techniques to enhance operational decision-making. Students learn how to extract actionable insights from large datasets using tools like Python, R, and SQL. The course emphasizes real-world applications through case studies and hands-on projects.
- Digital Transformation in Operations: Focused on understanding how digital technologies such as IoT, AI, and blockchain are revolutionizing traditional operational models across industries. Students explore topics including automation, digital twin technology, smart manufacturing systems, and data-driven decision-making processes.
- Lean Six Sigma Fundamentals: Introduces students to the principles of Lean manufacturing and Six Sigma quality improvement methodologies. Practical applications include process mapping, root cause analysis, and continuous improvement projects. Students gain hands-on experience through simulations and real-world case studies.
- Supply Chain Optimization: Covers advanced techniques for managing global supply chains, including demand forecasting, inventory management, transportation planning, and supplier relationship management. The course emphasizes strategic thinking and analytical tools used by leading organizations to optimize their supply chain operations.
- Service Operations Design: Explores the design and delivery of high-quality services across various sectors, emphasizing customer experience, service blueprinting, and service recovery strategies. Students learn how to apply operational principles to service industries such as hospitality, healthcare, finance, and telecommunications.
- Risk Assessment and Mitigation: Teaches students how to identify, assess, and manage operational risks through quantitative and qualitative risk modeling techniques. The course includes case studies from different industries, enabling students to develop a comprehensive understanding of risk management frameworks.
- Human Factors in Operations: Examines the role of human behavior in operational systems, focusing on ergonomics, team dynamics, organizational culture, and leadership effectiveness. Students learn how to design systems that account for human capabilities and limitations to improve operational efficiency.
- Sustainable Operations and Green Manufacturing: Addresses environmental sustainability issues in manufacturing processes, including waste minimization, energy efficiency, life cycle assessment, and green supply chain management. The course emphasizes best practices and emerging trends in sustainable operations.
- Operations in Healthcare Systems: Analyzes operational challenges within healthcare environments, covering patient flow optimization, resource allocation, quality improvement strategies, and regulatory compliance. Students gain insights into how operational principles can be applied to improve healthcare delivery systems.
- Leadership and Change Management: Develops leadership skills necessary for managing change in complex operational environments, including stakeholder engagement, communication strategies, transformational leadership, and organizational development techniques.
Project-Based Learning Philosophy
The department's philosophy on project-based learning emphasizes the integration of theory and practice. Students begin with mini-projects in their second year, focusing on solving real-world problems related to process optimization or system design. As they progress, these projects scale up to include larger-scale initiatives that often involve collaboration with industry partners.
The mandatory mini-projects are designed to help students apply theoretical concepts learned in class to practical situations. These projects typically last for 4-6 weeks and involve small groups of 3-5 students working under the supervision of faculty mentors. The scope and complexity of these projects increase progressively each year, allowing students to build upon their previous experiences.
The final-year thesis/capstone project allows students to explore a topic of personal interest within the broader scope of operations. Students are encouraged to propose innovative solutions or conduct research that contributes to the field. Projects can range from developing a new operational framework for a specific industry to implementing an AI-based system for predictive maintenance.
Project selection is done through a structured process involving faculty mentorship and student interest alignment. Students are paired with mentors based on project relevance and faculty expertise, ensuring that each student receives personalized guidance throughout the development phase. The evaluation criteria for these projects include creativity, technical depth, presentation quality, and contribution to the field.