• Introduction to AI and Machine Learning: Understanding the fundamentals of AI and Machine Learning, their applications, and potential in supply chain management.
• Data Analytics for Supply Chain: Learning data analysis techniques and tools to extract insights from supply chain data, and how to use these insights to make informed decisions.
• AI-Driven Demand Forecasting: Exploring how AI and Machine Learning can improve demand forecasting accuracy, reduce lead times, and optimize inventory levels.
• AI-Powered Inventory Management: Examining the role of AI in inventory management, including autonomous inventory ordering, dynamic pricing, and real-time inventory tracking.
• AI-Driven Supply Chain Visibility: Understanding how AI can provide real-time visibility into the supply chain, including tracking goods in transit, monitoring supplier performance, and detecting potential disruptions.
• AI in Warehouse Management: Learning about the use of AI and robotics in warehouse automation, including automated picking, sorting, and packaging.
• Ethics and AI in Supply Chain: Exploring the ethical considerations of using AI in supply chain management, including data privacy, bias, and transparency.
• Implementing AI in Supply Chain: Examining the practical considerations of implementing AI in supply chain management, including integration with existing systems, change management, and talent acquisition.

• AI-Driven Supply Chain Risk Management: Understanding how AI can help organizations anticipate and mitigate supply chain risks by detecting patterns and anomalies in data.
• AI-Driven Supply Chain Optimization: Exploring how AI can optimize supply chain operations by identifying the most efficient routes, modes of transportation, and delivery schedules.