Course Overview Table
Semester | Course Code | Course Title | Credit Structure (L-T-P-C) | Prerequisites |
---|---|---|---|---|
1 | LOG-101 | Introduction to Logistics | 3-0-0-3 | - |
1 | LOG-102 | Engineering Mathematics I | 3-0-0-3 | - |
1 | LOG-103 | Physics for Engineers | 3-0-0-3 | - |
1 | LOG-104 | Chemistry for Engineers | 3-0-0-3 | - |
1 | LOG-105 | Computer Programming | 2-0-2-4 | - |
1 | LOG-106 | English Communication Skills | 2-0-0-2 | - |
2 | LOG-201 | Operations Research | 3-0-0-3 | LOG-102 |
2 | LOG-202 | Transportation Systems | 3-0-0-3 | - |
2 | LOG-203 | Supply Chain Management | 3-0-0-3 | - |
2 | LOG-204 | Introduction to Data Science | 3-0-0-3 | LOG-102 |
2 | LOG-205 | Engineering Drawing | 2-0-2-4 | - |
2 | LOG-206 | Workshop Practices | 0-0-4-2 | - |
3 | LOG-301 | Inventory Management | 3-0-0-3 | LOG-201 |
3 | LOG-302 | Warehouse Design and Operations | 3-0-0-3 | - |
3 | LOG-303 | E-commerce Logistics | 3-0-0-3 | - |
3 | LOG-304 | Logistics Information Systems | 3-0-0-3 | LOG-204 |
3 | LOG-305 | Data Analytics for Supply Chains | 3-0-0-3 | LOG-204 |
3 | LOG-306 | Project Management | 2-0-0-2 | - |
4 | LOG-401 | Sustainable Logistics | 3-0-0-3 | LOG-301 |
4 | LOG-402 | International Trade and Customs | 3-0-0-3 | - |
4 | LOG-403 | Humanitarian Logistics | 3-0-0-3 | - |
4 | LOG-404 | Supply Chain Risk Management | 3-0-0-3 | - |
4 | LOG-405 | Smart Cities and Urban Logistics | 3-0-0-3 | - |
4 | LOG-406 | Capstone Project | 0-0-8-8 | LOG-301, LOG-302 |
5 | LOG-501 | Advanced Data Analytics in Logistics | 3-0-0-3 | LOG-305 |
5 | LOG-502 | Blockchain and Supply Chain | 3-0-0-3 | - |
5 | LOG-503 | AI in Logistics | 3-0-0-3 | - |
5 | LOG-504 | Logistics Forecasting Techniques | 3-0-0-3 | - |
5 | LOG-505 | Industry Internship | 0-0-4-4 | - |
6 | LOG-601 | Advanced Logistics Systems | 3-0-0-3 | LOG-501 |
6 | LOG-602 | Logistics and Sustainability | 3-0-0-3 | - |
6 | LOG-603 | Digital Supply Chain Transformation | 3-0-0-3 | - |
6 | LOG-604 | Capstone Project | 0-0-8-8 | LOG-501, LOG-502 |
7 | LOG-701 | Logistics Research Methodology | 3-0-0-3 | - |
7 | LOG-702 | Thesis Proposal | 0-0-4-4 | - |
8 | LOG-801 | Final Thesis | 0-0-8-8 | - |
Advanced Departmental Elective Courses:
- Data Analytics for Supply Chains: This course focuses on applying statistical methods and machine learning techniques to analyze supply chain data, improving forecasting accuracy and operational efficiency.
- Sustainable Logistics: Students explore eco-friendly practices, carbon footprint reduction strategies, and green transportation methods to promote environmental responsibility in logistics.
- Blockchain and Supply Chain: This course delves into how blockchain technology can enhance transparency, traceability, and security within supply chain networks.
- AI in Logistics: Covers the application of artificial intelligence in logistics operations, including predictive maintenance, route optimization, and autonomous vehicle integration.
- Logistics Forecasting Techniques: Provides an in-depth study of various forecasting methods used in logistics, from time series analysis to demand planning models.
- Digital Supply Chain Transformation: Explores how digital technologies such as IoT, cloud computing, and AI are transforming traditional supply chain practices.
- Humanitarian Logistics: Addresses logistics challenges in disaster relief and humanitarian aid delivery, emphasizing coordination with government agencies, NGOs, and international organizations.
- International Trade and Customs: This course covers customs regulations, international shipping laws, and cross-border logistics management to prepare students for global trade roles.
- Supply Chain Risk Management: Focuses on identifying, assessing, and mitigating risks within supply chains, including geopolitical threats, natural disasters, and cyber-attacks.
- Smart Cities and Urban Logistics: Students learn how logistics can be integrated into urban planning to create efficient, sustainable, and livable cities, with a focus on last-mile delivery solutions and smart infrastructure.
Project-Based Learning Philosophy:
Our department strongly believes in experiential learning through project-based methodologies. Students engage in both mini-projects and final-year capstone projects throughout their academic journey. Mini-projects, typically undertaken in the third and fourth semesters, are designed to reinforce core concepts taught in class while allowing students to explore real-world applications.
The structure of these projects involves forming teams of 3-5 students who work under the guidance of a faculty mentor. Each team selects a relevant topic within logistics that aligns with current industry trends or research interests. Projects are evaluated based on technical soundness, innovation, presentation quality, and peer feedback.
For the final-year thesis/capstone project, students are encouraged to collaborate with industry partners or pursue independent research topics under faculty supervision. The capstone project requires a comprehensive report, an oral presentation, and a demonstration of the implemented solution or research outcome. This culminating experience ensures that students demonstrate mastery over their chosen area of specialization and are prepared for professional roles or further studies.