Comprehensive Course Structure
| Semester | Course Code | Course Title | Credits (L-T-P-C) | Prerequisites |
|---|---|---|---|---|
| 1 | ENG101 | English for Engineering | 3-0-0-3 | - |
| 1 | MAT101 | Mathematics I | 4-0-0-4 | - |
| 1 | PHY101 | Physics for Engineers | 3-0-0-3 | - |
| 1 | CHE101 | Chemistry for Engineers | 3-0-0-3 | - |
| 1 | ECO101 | Introduction to Economics | 3-0-0-3 | - |
| 1 | LAB101 | Physics Lab | 0-0-2-1 | - |
| 1 | LAB102 | Chemistry Lab | 0-0-2-1 | - |
| 2 | MAT201 | Mathematics II | 4-0-0-4 | MAT101 |
| 2 | ENG201 | Technical Communication | 3-0-0-3 | - |
| 2 | PHY201 | Electromagnetic Fields and Waves | 3-0-0-3 | PHY101 |
| 2 | BIO201 | Biology for Engineers | 3-0-0-3 | - |
| 2 | CSE201 | Introduction to Computer Science | 3-0-0-3 | - |
| 2 | LAB201 | Engineering Drawing | 0-0-4-2 | - |
| 3 | MAT301 | Mathematics III | 4-0-0-4 | MAT201 |
| 3 | ECE301 | Electrical Circuits and Networks | 3-0-0-3 | - |
| 3 | MECH301 | Engineering Mechanics | 3-0-0-3 | - |
| 3 | CSE301 | Data Structures and Algorithms | 3-0-0-3 | CSE201 |
| 3 | STAT301 | Probability and Statistics | 3-0-0-3 | MAT201 |
| 3 | LAB301 | Computer Lab | 0-0-2-1 | - |
| 4 | MAT401 | Mathematics IV | 4-0-0-4 | MAT301 |
| 4 | ECE401 | Signals and Systems | 3-0-0-3 | ECE301 |
| 4 | MECH401 | Mechanics of Materials | 3-0-0-3 | MECH301 |
| 4 | CSE401 | Database Management Systems | 3-0-0-3 | CSE301 |
| 4 | STAT401 | Statistical Inference | 3-0-0-3 | STAT301 |
| 4 | LAB401 | Electronics Lab | 0-0-2-1 | - |
| 5 | MAT501 | Advanced Mathematics | 4-0-0-4 | MAT401 |
| 5 | ECE501 | Digital Electronics | 3-0-0-3 | ECE401 |
| 5 | MECH501 | Thermodynamics | 3-0-0-3 | - |
| 5 | CSE501 | Software Engineering | 3-0-0-3 | CSE401 |
| 5 | STAT501 | Operations Research | 3-0-0-3 | STAT401 |
| 5 | LAB501 | Advanced Lab | 0-0-2-1 | - |
| 6 | MAT601 | Mathematical Modeling | 4-0-0-4 | MAT501 |
| 6 | ECE601 | Control Systems | 3-0-0-3 | ECE501 |
| 6 | MECH601 | Mechatronics | 3-0-0-3 | - |
| 6 | CSE601 | Machine Learning | 3-0-0-3 | CSE501 |
| 6 | STAT601 | Design of Experiments | 3-0-0-3 | STAT501 |
| 6 | LAB601 | Research Lab | 0-0-2-1 | - |
| 7 | MAT701 | Optimization Techniques | 4-0-0-4 | MAT601 |
| 7 | ECE701 | Signal Processing | 3-0-0-3 | ECE601 |
| 7 | MECH701 | Manufacturing Processes | 3-0-0-3 | - |
| 7 | CSE701 | Big Data Analytics | 3-0-0-3 | CSE601 |
| 7 | STAT701 | Time Series Analysis | 3-0-0-3 | STAT601 |
| 7 | LAB701 | Simulation Lab | 0-0-2-1 | - |
| 8 | MAT801 | Advanced Statistical Methods | 4-0-0-4 | MAT701 |
| 8 | ECE801 | Embedded Systems | 3-0-0-3 | ECE701 |
| 8 | MECH801 | Industrial Automation | 3-0-0-3 | - |
| 8 | CSE801 | Artificial Intelligence | 3-0-0-3 | CSE701 |
| 8 | STAT801 | Bayesian Inference | 3-0-0-3 | STAT701 |
| 8 | LAB801 | Capstone Lab | 0-0-2-1 | - |
Advanced Departmental Electives
These courses are designed to deepen students' understanding of specialized areas within operations:
- Operations Research and Optimization: This course introduces students to mathematical models used in decision-making, including linear programming, network flows, and integer programming. Students learn how to apply these techniques to solve complex operational problems.
- Supply Chain Analytics: Focused on analyzing data from supply chains using statistical tools and machine learning algorithms, this course prepares students for roles in logistics and procurement analytics.
- Lean Manufacturing Systems: Students explore the principles of lean thinking, waste elimination, and continuous improvement. The course includes practical applications through case studies and simulations.
- Digital Twin Technology: This elective covers the concept of digital twins—virtual replicas of physical systems—and their application in monitoring and optimizing operations across industries.
- Sustainable Operations Management: This course explores sustainable practices in operations, including circular economy principles, green logistics, and environmental impact assessments.
- Project Management for Engineers: Designed to train students in managing engineering projects effectively, this course covers project planning, risk management, budgeting, and team coordination.
- Data Visualization and Business Intelligence: Students learn how to present complex data clearly using visualization tools like Tableau and Power BI, enabling better decision-making in operational contexts.
- Service Operations Design: This course focuses on designing efficient service delivery systems for sectors such as healthcare, hospitality, and finance.
- Process Simulation and Modeling: Using software like Arena and AnyLogic, students simulate real-world operations to predict outcomes and optimize performance.
- Risk Management in Operations: This course teaches methods for identifying, assessing, and mitigating risks in operational environments, particularly in global supply chains.
Project-Based Learning Philosophy
Our approach emphasizes experiential learning through project-based assignments that mirror real-world challenges. Students begin with mini-projects in the second year, which scale up to full-scale capstone projects in their final year. These projects are selected based on industry needs or faculty research interests.
The structure involves:
- Mini Projects (Year 2): Small-scale, team-based tasks that introduce students to problem-solving frameworks.
- Capstone Projects (Year 4): Large-scale, interdisciplinary initiatives supervised by faculty mentors and often involving industry partners.
Evaluation criteria include innovation, feasibility, impact, teamwork, and documentation. Students also present their work at annual symposiums and competitions, fostering communication and leadership skills.