Course Structure Overview

The Supply Chain program is structured over 8 semesters, combining foundational courses with specialized electives and practical experiences. Below is a detailed table of all courses across the duration:

Advanced Departmental Elective Courses

These courses offer advanced insights into specialized areas within Supply Chain management and are designed to deepen student expertise:

• Data Mining for SCM: This course explores how big data technologies can be applied to supply chain problems. Students learn about data preprocessing, clustering algorithms, regression models, and predictive analytics tools such as Python, R, and Weka.
• Machine Learning in Logistics: Students study machine learning applications in route optimization, demand forecasting, and warehouse automation. Topics include neural networks, decision trees, ensemble methods, and reinforcement learning.
• Supply Chain Optimization Using AI: Focused on developing intelligent systems that optimize supply chain operations using artificial intelligence techniques. Includes algorithm design, simulation, and practical implementation using platforms like TensorFlow and PyTorch.
• Sustainable Procurement: This course delves into ethical sourcing practices, environmental impact assessment, and corporate social responsibility in procurement. Students examine case studies of successful sustainable sourcing initiatives across industries.
• Eco-Design in Supply Chain: Explores how product design decisions affect supply chain performance from an environmental perspective. Emphasis is placed on life cycle analysis, eco-labeling, and circular economy principles.
• Corporate Social Responsibility in SCM: Examines the role of CSR in shaping supply chain policies and practices. Students analyze real-world examples of companies integrating ethical considerations into their logistics strategies.
• Agricultural Marketing: Covers marketing principles specific to agricultural products, including price formation, distribution channels, branding strategies, and market access for smallholder farmers.
• Rural Supply Chain Development: Focuses on designing supply chains tailored for rural environments. Topics include infrastructure challenges, local sourcing, microfinance integration, and government support mechanisms.
• Food Security and Logistics: Addresses the intersection of food safety, nutritional outcomes, and logistical efficiency in global food systems. Students explore food loss reduction strategies and policy frameworks for improving access to nutritious food.
• Blockchain-Based Traceability: Introduces blockchain technology as a tool for enhancing transparency and traceability in supply chains. Students learn about smart contracts, decentralized databases, and their applications in verifying authenticity of goods.

Project-Based Learning Philosophy

The Supply Chain program at College of Agribusiness Management is built on the foundation of project-based learning, which emphasizes experiential education through real-world problem-solving. This approach ensures that students not only understand theoretical concepts but also develop practical skills necessary for industry success.

Mini-projects are introduced in the third year and span across two semesters. These projects involve working in teams under faculty supervision on challenges posed by industry partners or academic research initiatives. Students must present their findings at the end of each semester, receiving feedback from both peers and mentors to refine their approach.

The final-year capstone project is a significant undertaking that allows students to demonstrate mastery over key competencies learned throughout their program. The process begins with a proposal phase where students identify an area of interest within the supply chain domain and propose a research question or solution framework. Once approved, they work closely with a faculty advisor on conducting literature reviews, collecting data, designing experiments, and analyzing results.

Students are encouraged to choose projects aligned with their chosen specialization track. For example, someone interested in digital supply chain analytics might focus on developing a dashboard for tracking inventory levels in real-time using IoT sensors. Another student pursuing sustainable sourcing could explore how local suppliers can be integrated into global supply networks while minimizing carbon emissions.

Evaluation criteria include project scope, methodology, data quality, presentation effectiveness, and peer collaboration. The final deliverables are typically a detailed report, a presentation to faculty and industry experts, and a demonstration of the implemented solution or model.